/* * Copyright 1993-2024 NVIDIA Corporation. All rights reserved. * * NOTICE TO LICENSEE: * * This source code and/or documentation ("Licensed Deliverables") are * subject to NVIDIA intellectual property rights under U.S. and * international Copyright laws. * * These Licensed Deliverables contained herein is PROPRIETARY and * CONFIDENTIAL to NVIDIA and is being provided under the terms and * conditions of a form of NVIDIA software license agreement by and * between NVIDIA and Licensee ("License Agreement") or electronically * accepted by Licensee. Notwithstanding any terms or conditions to * the contrary in the License Agreement, reproduction or disclosure * of the Licensed Deliverables to any third party without the express * written consent of NVIDIA is prohibited. * * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE * LICENSE AGREEMENT, NVIDIA MAKES NO REPRESENTATION ABOUT THE * SUITABILITY OF THESE LICENSED DELIVERABLES FOR ANY PURPOSE. IT IS * PROVIDED "AS IS" WITHOUT EXPRESS OR IMPLIED WARRANTY OF ANY KIND. * NVIDIA DISCLAIMS ALL WARRANTIES WITH REGARD TO THESE LICENSED * DELIVERABLES, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY, * NONINFRINGEMENT, AND FITNESS FOR A PARTICULAR PURPOSE. * NOTWITHSTANDING ANY TERMS OR CONDITIONS TO THE CONTRARY IN THE * LICENSE AGREEMENT, IN NO EVENT SHALL NVIDIA BE LIABLE FOR ANY * SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, OR ANY * DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, * WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS * ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE * OF THESE LICENSED DELIVERABLES. * * U.S. Government End Users. These Licensed Deliverables are a * "commercial item" as that term is defined at 48 C.F.R. 2.101 (OCT * 1995), consisting of "commercial computer software" and "commercial * computer software documentation" as such terms are used in 48 * C.F.R. 12.212 (SEPT 1995) and is provided to the U.S. Government * only as a commercial end item. Consistent with 48 C.F.R.12.212 and * 48 C.F.R. 227.7202-1 through 227.7202-4 (JUNE 1995), all * U.S. Government End Users acquire the Licensed Deliverables with * only those rights set forth herein. * * Any use of the Licensed Deliverables in individual and commercial * software must include, in the user documentation and internal * comments to the code, the above Disclaimer and U.S. Government End * Users Notice. */ #if !defined(__CUDA_RUNTIME_API_H__) #define __CUDA_RUNTIME_API_H__ #if !defined(__CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__) #define __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__ #define __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_CUDA_RUNTIME_API_H__ #endif /** * \latexonly * \page sync_async API synchronization behavior * * \section memcpy_sync_async_behavior Memcpy * The API provides memcpy/memset functions in both synchronous and asynchronous forms, * the latter having an \e "Async" suffix. This is a misnomer as each function * may exhibit synchronous or asynchronous behavior depending on the arguments * passed to the function. In the reference documentation, each memcpy function is * categorized as \e synchronous or \e asynchronous, corresponding to the definitions * below. * * \subsection MemcpySynchronousBehavior Synchronous * *
    *
  1. For transfers from pageable host memory to device memory, a stream sync is performed * before the copy is initiated. The function will return once the pageable * buffer has been copied to the staging memory for DMA transfer to device memory, * but the DMA to final destination may not have completed. * *
  2. For transfers from pinned host memory to device memory, the function is synchronous * with respect to the host. * *
  3. For transfers from device to either pageable or pinned host memory, the function returns * only once the copy has completed. * *
  4. For transfers from device memory to device memory, no host-side synchronization is * performed. * *
  5. For transfers from any host memory to any host memory, the function is fully * synchronous with respect to the host. *
* * \subsection MemcpyAsynchronousBehavior Asynchronous * *
    *
  1. For transfers between device memory and pageable host memory, the function might * be synchronous with respect to host. * *
  2. For transfers from any host memory to any host memory, the function is fully * synchronous with respect to the host. * *
  3. If pageable memory must first be staged to pinned memory, the driver may * synchronize with the stream and stage the copy into pinned memory. * *
  4. For all other transfers, the function should be fully asynchronous. *
* * \section memset_sync_async_behavior Memset * The cudaMemset functions are asynchronous with respect to the host * except when the target memory is pinned host memory. The \e Async * versions are always asynchronous with respect to the host. * * \section kernel_launch_details Kernel Launches * Kernel launches are asynchronous with respect to the host. Details of * concurrent kernel execution and data transfers can be found in the CUDA * Programmers Guide. * * \endlatexonly */ /** * There are two levels for the runtime API. * * The C API (cuda_runtime_api.h) is * a C-style interface that does not require compiling with \p nvcc. * * The \ref CUDART_HIGHLEVEL "C++ API" (cuda_runtime.h) is a * C++-style interface built on top of the C API. It wraps some of the * C API routines, using overloading, references and default arguments. * These wrappers can be used from C++ code and can be compiled with any C++ * compiler. The C++ API also has some CUDA-specific wrappers that wrap * C API routines that deal with symbols, textures, and device functions. * These wrappers require the use of \p nvcc because they depend on code being * generated by the compiler. For example, the execution configuration syntax * to invoke kernels is only available in source code compiled with \p nvcc. */ /** CUDA Runtime API Version */ #define CUDART_VERSION 12080 #if defined(__CUDA_API_VER_MAJOR__) && defined(__CUDA_API_VER_MINOR__) # define __CUDART_API_VERSION ((__CUDA_API_VER_MAJOR__ * 1000) + (__CUDA_API_VER_MINOR__ * 10)) #else # define __CUDART_API_VERSION CUDART_VERSION #endif #ifndef __DOXYGEN_ONLY__ #include "crt/host_defines.h" #endif #include "builtin_types.h" #if !defined(__CUDACC_RTC_MINIMAL__) && ((defined(__CUDACC_RDC__) || defined(__CUDACC_EWP__) || !defined(__CUDACC_RTC__))) #include "cuda_device_runtime_api.h" #endif /* !defined(__CUDACC_RTC_MINIMAL__) && (defined(__CUDACC_RDC__) || defined(__CUDACC_EWP__) || !defined(__CUDACC_RTC__)) */ #ifndef __CUDACC_RTC_MINIMAL__ #if defined(CUDA_API_PER_THREAD_DEFAULT_STREAM) || defined(__CUDA_API_VERSION_INTERNAL) #define __CUDART_API_PER_THREAD_DEFAULT_STREAM #define __CUDART_API_PTDS(api) api ## _ptds #define __CUDART_API_PTSZ(api) api ## _ptsz #else #define __CUDART_API_PTDS(api) api #define __CUDART_API_PTSZ(api) api #endif #define cudaSignalExternalSemaphoresAsync __CUDART_API_PTSZ(cudaSignalExternalSemaphoresAsync_v2) #define cudaWaitExternalSemaphoresAsync __CUDART_API_PTSZ(cudaWaitExternalSemaphoresAsync_v2) #define cudaStreamGetCaptureInfo __CUDART_API_PTSZ(cudaStreamGetCaptureInfo_v2) #define cudaGetDeviceProperties cudaGetDeviceProperties_v2 #if defined(__CUDART_API_PER_THREAD_DEFAULT_STREAM) #define cudaMemcpy __CUDART_API_PTDS(cudaMemcpy) #define cudaMemcpyToSymbol __CUDART_API_PTDS(cudaMemcpyToSymbol) #define cudaMemcpyFromSymbol __CUDART_API_PTDS(cudaMemcpyFromSymbol) #define cudaMemcpy2D __CUDART_API_PTDS(cudaMemcpy2D) #define cudaMemcpyToArray __CUDART_API_PTDS(cudaMemcpyToArray) #define cudaMemcpy2DToArray __CUDART_API_PTDS(cudaMemcpy2DToArray) #define cudaMemcpyFromArray __CUDART_API_PTDS(cudaMemcpyFromArray) #define cudaMemcpy2DFromArray __CUDART_API_PTDS(cudaMemcpy2DFromArray) #define cudaMemcpyArrayToArray __CUDART_API_PTDS(cudaMemcpyArrayToArray) #define cudaMemcpy2DArrayToArray __CUDART_API_PTDS(cudaMemcpy2DArrayToArray) #define cudaMemcpy3D __CUDART_API_PTDS(cudaMemcpy3D) #define cudaMemcpy3DPeer __CUDART_API_PTDS(cudaMemcpy3DPeer) #define cudaMemset __CUDART_API_PTDS(cudaMemset) #define cudaMemset2D __CUDART_API_PTDS(cudaMemset2D) #define cudaMemset3D __CUDART_API_PTDS(cudaMemset3D) #define cudaGraphInstantiateWithParams __CUDART_API_PTSZ(cudaGraphInstantiateWithParams) #define cudaGraphUpload __CUDART_API_PTSZ(cudaGraphUpload) #define cudaGraphLaunch __CUDART_API_PTSZ(cudaGraphLaunch) #define cudaStreamBeginCapture __CUDART_API_PTSZ(cudaStreamBeginCapture) #define cudaStreamBeginCaptureToGraph __CUDART_API_PTSZ(cudaStreamBeginCaptureToGraph) #define cudaStreamEndCapture __CUDART_API_PTSZ(cudaStreamEndCapture) #define cudaStreamGetCaptureInfo_v3 __CUDART_API_PTSZ(cudaStreamGetCaptureInfo_v3) #define cudaStreamUpdateCaptureDependencies __CUDART_API_PTSZ(cudaStreamUpdateCaptureDependencies) #define cudaStreamUpdateCaptureDependencies_v2 __CUDART_API_PTSZ(cudaStreamUpdateCaptureDependencies_v2) #define cudaStreamIsCapturing __CUDART_API_PTSZ(cudaStreamIsCapturing) #define cudaMemcpyAsync __CUDART_API_PTSZ(cudaMemcpyAsync) #define cudaMemcpyToSymbolAsync __CUDART_API_PTSZ(cudaMemcpyToSymbolAsync) #define cudaMemcpyFromSymbolAsync __CUDART_API_PTSZ(cudaMemcpyFromSymbolAsync) #define cudaMemcpy2DAsync __CUDART_API_PTSZ(cudaMemcpy2DAsync) #define cudaMemcpyToArrayAsync __CUDART_API_PTSZ(cudaMemcpyToArrayAsync) #define cudaMemcpy2DToArrayAsync __CUDART_API_PTSZ(cudaMemcpy2DToArrayAsync) #define cudaMemcpyFromArrayAsync __CUDART_API_PTSZ(cudaMemcpyFromArrayAsync) #define cudaMemcpy2DFromArrayAsync __CUDART_API_PTSZ(cudaMemcpy2DFromArrayAsync) #define cudaMemcpy3DAsync __CUDART_API_PTSZ(cudaMemcpy3DAsync) #define cudaMemcpy3DPeerAsync __CUDART_API_PTSZ(cudaMemcpy3DPeerAsync) #define cudaMemcpyBatchAsync __CUDART_API_PTSZ(cudaMemcpyBatchAsync) #define cudaMemcpy3DBatchAsync __CUDART_API_PTSZ(cudaMemcpy3DBatchAsync) #define cudaMemsetAsync __CUDART_API_PTSZ(cudaMemsetAsync) #define cudaMemset2DAsync __CUDART_API_PTSZ(cudaMemset2DAsync) #define cudaMemset3DAsync __CUDART_API_PTSZ(cudaMemset3DAsync) #define cudaStreamQuery __CUDART_API_PTSZ(cudaStreamQuery) #define cudaStreamGetDevice __CUDART_API_PTSZ(cudaStreamGetDevice) #define cudaStreamGetFlags __CUDART_API_PTSZ(cudaStreamGetFlags) #define cudaStreamGetId __CUDART_API_PTSZ(cudaStreamGetId) #define cudaStreamGetPriority __CUDART_API_PTSZ(cudaStreamGetPriority) #define cudaEventRecord __CUDART_API_PTSZ(cudaEventRecord) #define cudaEventRecordWithFlags __CUDART_API_PTSZ(cudaEventRecordWithFlags) #define cudaStreamWaitEvent __CUDART_API_PTSZ(cudaStreamWaitEvent) #define cudaStreamAddCallback __CUDART_API_PTSZ(cudaStreamAddCallback) #define cudaStreamAttachMemAsync __CUDART_API_PTSZ(cudaStreamAttachMemAsync) #define cudaStreamSynchronize __CUDART_API_PTSZ(cudaStreamSynchronize) #define cudaLaunchKernel __CUDART_API_PTSZ(cudaLaunchKernel) #define cudaLaunchKernelExC __CUDART_API_PTSZ(cudaLaunchKernelExC) #define cudaLaunchHostFunc __CUDART_API_PTSZ(cudaLaunchHostFunc) #define cudaMemPrefetchAsync __CUDART_API_PTSZ(cudaMemPrefetchAsync) #define cudaMemPrefetchAsync_v2 __CUDART_API_PTSZ(cudaMemPrefetchAsync_v2) #define cudaLaunchCooperativeKernel __CUDART_API_PTSZ(cudaLaunchCooperativeKernel) #define cudaStreamCopyAttributes __CUDART_API_PTSZ(cudaStreamCopyAttributes) #define cudaStreamGetAttribute __CUDART_API_PTSZ(cudaStreamGetAttribute) #define cudaStreamSetAttribute __CUDART_API_PTSZ(cudaStreamSetAttribute) #define cudaMallocAsync __CUDART_API_PTSZ(cudaMallocAsync) #define cudaFreeAsync __CUDART_API_PTSZ(cudaFreeAsync) #define cudaMallocFromPoolAsync __CUDART_API_PTSZ(cudaMallocFromPoolAsync) #define cudaGetDriverEntryPoint __CUDART_API_PTSZ(cudaGetDriverEntryPoint) #define cudaGetDriverEntryPointByVersion __CUDART_API_PTSZ(cudaGetDriverEntryPointByVersion) #endif #endif /* __CUDACC_RTC_MINIMAL__ */ /** \cond impl_private */ #if !defined(__dv) #if defined(__cplusplus) #define __dv(v) \ = v #else /* __cplusplus */ #define __dv(v) #endif /* __cplusplus */ #endif /* !__dv */ /** \endcond impl_private */ #if (defined(_NVHPC_CUDA) || !defined(__CUDA_ARCH__) || (__CUDA_ARCH__ >= 350)) /** Visible to SM>=3.5 and "__host__ __device__" only **/ #define CUDART_DEVICE __device__ #else #define CUDART_DEVICE #endif /** CUDART_DEVICE */ #if !defined(__CUDACC_RTC__) #define EXCLUDE_FROM_RTC /** \cond impl_private */ #if defined(__DOXYGEN_ONLY__) || defined(CUDA_ENABLE_DEPRECATED) #define __CUDA_DEPRECATED #elif defined(_MSC_VER) #define __CUDA_DEPRECATED __declspec(deprecated) #elif defined(__GNUC__) #define __CUDA_DEPRECATED __attribute__((deprecated)) #else #define __CUDA_DEPRECATED #endif /** \endcond impl_private */ #if defined(__cplusplus) extern "C" { #endif /* __cplusplus */ /** * \defgroup CUDART_DEVICE Device Management * * ___MANBRIEF___ device management functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the device management functions of the CUDA runtime * application programming interface. * * @{ */ /** * \brief Destroy all allocations and reset all state on the current device * in the current process. * * Explicitly destroys and cleans up all resources associated with the current * device in the current process. It is the caller's responsibility to ensure * that the resources are not accessed or passed in subsequent API calls and * doing so will result in undefined behavior. These resources include CUDA types * ::cudaStream_t, ::cudaEvent_t, ::cudaArray_t, ::cudaMipmappedArray_t, ::cudaPitchedPtr, * ::cudaTextureObject_t, ::cudaSurfaceObject_t, ::textureReference, ::surfaceReference, * ::cudaExternalMemory_t, ::cudaExternalSemaphore_t and ::cudaGraphicsResource_t. * These resources also include memory allocations by ::cudaMalloc, ::cudaMallocHost, * ::cudaMallocManaged and ::cudaMallocPitch. * Any subsequent API call to this device will reinitialize the device. * * Note that this function will reset the device immediately. It is the caller's * responsibility to ensure that the device is not being accessed by any * other host threads from the process when this function is called. * * \note ::cudaDeviceReset() will not destroy memory allocations by ::cudaMallocAsync() and * ::cudaMallocFromPoolAsync(). These memory allocations need to be destroyed explicitly. * \note If a non-primary ::CUcontext is current to the thread, ::cudaDeviceReset() * will destroy only the internal CUDA RT state for that ::CUcontext. * * \return * ::cudaSuccess * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaDeviceSynchronize */ extern __host__ cudaError_t CUDARTAPI cudaDeviceReset(void); /** * \brief Wait for compute device to finish * * Blocks until the device has completed all preceding requested tasks. * ::cudaDeviceSynchronize() returns an error if one of the preceding tasks * has failed. If the ::cudaDeviceScheduleBlockingSync flag was set for * this device, the host thread will block until the device has finished * its work. * * \return * ::cudaSuccess * \note_device_sync_deprecated * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaDeviceReset, * ::cuCtxSynchronize */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaDeviceSynchronize(void); /** * \brief Set resource limits * * Setting \p limit to \p value is a request by the application to update * the current limit maintained by the device. The driver is free to * modify the requested value to meet h/w requirements (this could be * clamping to minimum or maximum values, rounding up to nearest element * size, etc). The application can use ::cudaDeviceGetLimit() to find out * exactly what the limit has been set to. * * Setting each ::cudaLimit has its own specific restrictions, so each is * discussed here. * * - ::cudaLimitStackSize controls the stack size in bytes of each GPU thread. * * - ::cudaLimitPrintfFifoSize controls the size in bytes of the shared FIFO * used by the ::printf() device system call. Setting * ::cudaLimitPrintfFifoSize must not be performed after launching any kernel * that uses the ::printf() device system call - in such case * ::cudaErrorInvalidValue will be returned. * * - ::cudaLimitMallocHeapSize controls the size in bytes of the heap used by * the ::malloc() and ::free() device system calls. Setting * ::cudaLimitMallocHeapSize must not be performed after launching any kernel * that uses the ::malloc() or ::free() device system calls - in such case * ::cudaErrorInvalidValue will be returned. * * - ::cudaLimitDevRuntimeSyncDepth controls the maximum nesting depth of a * grid at which a thread can safely call ::cudaDeviceSynchronize(). Setting * this limit must be performed before any launch of a kernel that uses the * device runtime and calls ::cudaDeviceSynchronize() above the default sync * depth, two levels of grids. Calls to ::cudaDeviceSynchronize() will fail * with error code ::cudaErrorSyncDepthExceeded if the limitation is * violated. This limit can be set smaller than the default or up the maximum * launch depth of 24. When setting this limit, keep in mind that additional * levels of sync depth require the runtime to reserve large amounts of * device memory which can no longer be used for user allocations. If these * reservations of device memory fail, ::cudaDeviceSetLimit will return * ::cudaErrorMemoryAllocation, and the limit can be reset to a lower value. * This limit is only applicable to devices of compute capability < 9.0. * Attempting to set this limit on devices of other compute capability will * results in error ::cudaErrorUnsupportedLimit being returned. * * - ::cudaLimitDevRuntimePendingLaunchCount controls the maximum number of * outstanding device runtime launches that can be made from the current * device. A grid is outstanding from the point of launch up until the grid * is known to have been completed. Device runtime launches which violate * this limitation fail and return ::cudaErrorLaunchPendingCountExceeded when * ::cudaGetLastError() is called after launch. If more pending launches than * the default (2048 launches) are needed for a module using the device * runtime, this limit can be increased. Keep in mind that being able to * sustain additional pending launches will require the runtime to reserve * larger amounts of device memory upfront which can no longer be used for * allocations. If these reservations fail, ::cudaDeviceSetLimit will return * ::cudaErrorMemoryAllocation, and the limit can be reset to a lower value. * This limit is only applicable to devices of compute capability 3.5 and * higher. Attempting to set this limit on devices of compute capability less * than 3.5 will result in the error ::cudaErrorUnsupportedLimit being * returned. * * - ::cudaLimitMaxL2FetchGranularity controls the L2 cache fetch granularity. * Values can range from 0B to 128B. This is purely a performance hint and * it can be ignored or clamped depending on the platform. * * - ::cudaLimitPersistingL2CacheSize controls size in bytes available * for persisting L2 cache. This is purely a performance hint and it * can be ignored or clamped depending on the platform. * * \param limit - Limit to set * \param value - Size of limit * * \return * ::cudaSuccess, * ::cudaErrorUnsupportedLimit, * ::cudaErrorInvalidValue, * ::cudaErrorMemoryAllocation * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaDeviceGetLimit, * ::cuCtxSetLimit */ extern __host__ cudaError_t CUDARTAPI cudaDeviceSetLimit(enum cudaLimit limit, size_t value); /** * \brief Return resource limits * * Returns in \p *pValue the current size of \p limit. The following ::cudaLimit values are supported. * - ::cudaLimitStackSize is the stack size in bytes of each GPU thread. * - ::cudaLimitPrintfFifoSize is the size in bytes of the shared FIFO used by the * ::printf() device system call. * - ::cudaLimitMallocHeapSize is the size in bytes of the heap used by the * ::malloc() and ::free() device system calls. * - ::cudaLimitDevRuntimeSyncDepth is the maximum grid depth at which a * thread can isssue the device runtime call ::cudaDeviceSynchronize() * to wait on child grid launches to complete. This functionality is removed * for devices of compute capability >= 9.0, and hence will return error * ::cudaErrorUnsupportedLimit on such devices. * - ::cudaLimitDevRuntimePendingLaunchCount is the maximum number of outstanding * device runtime launches. * - ::cudaLimitMaxL2FetchGranularity is the L2 cache fetch granularity. * - ::cudaLimitPersistingL2CacheSize is the persisting L2 cache size in bytes. * * \param limit - Limit to query * \param pValue - Returned size of the limit * * \return * ::cudaSuccess, * ::cudaErrorUnsupportedLimit, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaDeviceSetLimit, * ::cuCtxGetLimit */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaDeviceGetLimit(size_t *pValue, enum cudaLimit limit); /** * \brief Returns the maximum number of elements allocatable in a 1D linear texture for a given element size. * * Returns in \p maxWidthInElements the maximum number of elements allocatable in a 1D linear texture * for given format descriptor \p fmtDesc. * * \param maxWidthInElements - Returns maximum number of texture elements allocatable for given \p fmtDesc. * \param fmtDesc - Texture format description. * * \return * ::cudaSuccess, * ::cudaErrorUnsupportedLimit, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cuDeviceGetTexture1DLinearMaxWidth */ #if __CUDART_API_VERSION >= 11010 extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaDeviceGetTexture1DLinearMaxWidth(size_t *maxWidthInElements, const struct cudaChannelFormatDesc *fmtDesc, int device); #endif /** * \brief Returns the preferred cache configuration for the current device. * * On devices where the L1 cache and shared memory use the same hardware * resources, this returns through \p pCacheConfig the preferred cache * configuration for the current device. This is only a preference. The * runtime will use the requested configuration if possible, but it is free to * choose a different configuration if required to execute functions. * * This will return a \p pCacheConfig of ::cudaFuncCachePreferNone on devices * where the size of the L1 cache and shared memory are fixed. * * The supported cache configurations are: * - ::cudaFuncCachePreferNone: no preference for shared memory or L1 (default) * - ::cudaFuncCachePreferShared: prefer larger shared memory and smaller L1 cache * - ::cudaFuncCachePreferL1: prefer larger L1 cache and smaller shared memory * - ::cudaFuncCachePreferEqual: prefer equal size L1 cache and shared memory * * \param pCacheConfig - Returned cache configuration * * \return * ::cudaSuccess * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaDeviceSetCacheConfig, * \ref ::cudaFuncSetCacheConfig(const void*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C API)", * \ref ::cudaFuncSetCacheConfig(T*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C++ API)", * ::cuCtxGetCacheConfig */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaDeviceGetCacheConfig(enum cudaFuncCache *pCacheConfig); /** * \brief Returns numerical values that correspond to the least and * greatest stream priorities. * * Returns in \p *leastPriority and \p *greatestPriority the numerical values that correspond * to the least and greatest stream priorities respectively. Stream priorities * follow a convention where lower numbers imply greater priorities. The range of * meaningful stream priorities is given by [\p *greatestPriority, \p *leastPriority]. * If the user attempts to create a stream with a priority value that is * outside the the meaningful range as specified by this API, the priority is * automatically clamped down or up to either \p *leastPriority or \p *greatestPriority * respectively. See ::cudaStreamCreateWithPriority for details on creating a * priority stream. * A NULL may be passed in for \p *leastPriority or \p *greatestPriority if the value * is not desired. * * This function will return '0' in both \p *leastPriority and \p *greatestPriority if * the current context's device does not support stream priorities * (see ::cudaDeviceGetAttribute). * * \param leastPriority - Pointer to an int in which the numerical value for least * stream priority is returned * \param greatestPriority - Pointer to an int in which the numerical value for greatest * stream priority is returned * * \return * ::cudaSuccess * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaStreamCreateWithPriority, * ::cudaStreamGetPriority, * ::cuCtxGetStreamPriorityRange */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaDeviceGetStreamPriorityRange(int *leastPriority, int *greatestPriority); /** * \brief Sets the preferred cache configuration for the current device. * * On devices where the L1 cache and shared memory use the same hardware * resources, this sets through \p cacheConfig the preferred cache * configuration for the current device. This is only a preference. The * runtime will use the requested configuration if possible, but it is free to * choose a different configuration if required to execute the function. Any * function preference set via * \ref ::cudaFuncSetCacheConfig(const void*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C API)" * or * \ref ::cudaFuncSetCacheConfig(T*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C++ API)" * will be preferred over this device-wide setting. Setting the device-wide * cache configuration to ::cudaFuncCachePreferNone will cause subsequent * kernel launches to prefer to not change the cache configuration unless * required to launch the kernel. * * This setting does nothing on devices where the size of the L1 cache and * shared memory are fixed. * * Launching a kernel with a different preference than the most recent * preference setting may insert a device-side synchronization point. * * The supported cache configurations are: * - ::cudaFuncCachePreferNone: no preference for shared memory or L1 (default) * - ::cudaFuncCachePreferShared: prefer larger shared memory and smaller L1 cache * - ::cudaFuncCachePreferL1: prefer larger L1 cache and smaller shared memory * - ::cudaFuncCachePreferEqual: prefer equal size L1 cache and shared memory * * \param cacheConfig - Requested cache configuration * * \return * ::cudaSuccess * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaDeviceGetCacheConfig, * \ref ::cudaFuncSetCacheConfig(const void*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C API)", * \ref ::cudaFuncSetCacheConfig(T*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C++ API)", * ::cuCtxSetCacheConfig */ extern __host__ cudaError_t CUDARTAPI cudaDeviceSetCacheConfig(enum cudaFuncCache cacheConfig); /** * \brief Returns a handle to a compute device * * Returns in \p *device a device ordinal given a PCI bus ID string. * * \param device - Returned device ordinal * * \param pciBusId - String in one of the following forms: * [domain]:[bus]:[device].[function] * [domain]:[bus]:[device] * [bus]:[device].[function] * where \p domain, \p bus, \p device, and \p function are all hexadecimal values * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidDevice * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaDeviceGetPCIBusId, * ::cuDeviceGetByPCIBusId */ extern __host__ cudaError_t CUDARTAPI cudaDeviceGetByPCIBusId(int *device, const char *pciBusId); /** * \brief Returns a PCI Bus Id string for the device * * Returns an ASCII string identifying the device \p dev in the NULL-terminated * string pointed to by \p pciBusId. \p len specifies the maximum length of the * string that may be returned. * * \param pciBusId - Returned identifier string for the device in the following format * [domain]:[bus]:[device].[function] * where \p domain, \p bus, \p device, and \p function are all hexadecimal values. * pciBusId should be large enough to store 13 characters including the NULL-terminator. * * \param len - Maximum length of string to store in \p name * * \param device - Device to get identifier string for * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidDevice * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaDeviceGetByPCIBusId, * ::cuDeviceGetPCIBusId */ extern __host__ cudaError_t CUDARTAPI cudaDeviceGetPCIBusId(char *pciBusId, int len, int device); /** * \brief Gets an interprocess handle for a previously allocated event * * Takes as input a previously allocated event. This event must have been * created with the ::cudaEventInterprocess and ::cudaEventDisableTiming * flags set. This opaque handle may be copied into other processes and * opened with ::cudaIpcOpenEventHandle to allow efficient hardware * synchronization between GPU work in different processes. * * After the event has been been opened in the importing process, * ::cudaEventRecord, ::cudaEventSynchronize, ::cudaStreamWaitEvent and * ::cudaEventQuery may be used in either process. Performing operations * on the imported event after the exported event has been freed * with ::cudaEventDestroy will result in undefined behavior. * * IPC functionality is restricted to devices with support for unified * addressing on Linux and Windows operating systems. * IPC functionality on Windows is supported for compatibility purposes * but not recommended as it comes with performance cost. * Users can test their device for IPC functionality by calling * ::cudaDeviceGetAttribute with ::cudaDevAttrIpcEventSupport * * \param handle - Pointer to a user allocated cudaIpcEventHandle * in which to return the opaque event handle * \param event - Event allocated with ::cudaEventInterprocess and * ::cudaEventDisableTiming flags. * * \return * ::cudaSuccess, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorMemoryAllocation, * ::cudaErrorMapBufferObjectFailed, * ::cudaErrorNotSupported, * ::cudaErrorInvalidValue * \note_init_rt * \note_callback * * \sa * ::cudaEventCreate, * ::cudaEventDestroy, * ::cudaEventSynchronize, * ::cudaEventQuery, * ::cudaStreamWaitEvent, * ::cudaIpcOpenEventHandle, * ::cudaIpcGetMemHandle, * ::cudaIpcOpenMemHandle, * ::cudaIpcCloseMemHandle, * ::cuIpcGetEventHandle */ extern __host__ cudaError_t CUDARTAPI cudaIpcGetEventHandle(cudaIpcEventHandle_t *handle, cudaEvent_t event); /** * \brief Opens an interprocess event handle for use in the current process * * Opens an interprocess event handle exported from another process with * ::cudaIpcGetEventHandle. This function returns a ::cudaEvent_t that behaves like * a locally created event with the ::cudaEventDisableTiming flag specified. * This event must be freed with ::cudaEventDestroy. * * Performing operations on the imported event after the exported event has * been freed with ::cudaEventDestroy will result in undefined behavior. * * IPC functionality is restricted to devices with support for unified * addressing on Linux and Windows operating systems. * IPC functionality on Windows is supported for compatibility purposes * but not recommended as it comes with performance cost. * Users can test their device for IPC functionality by calling * ::cudaDeviceGetAttribute with ::cudaDevAttrIpcEventSupport * * \param event - Returns the imported event * \param handle - Interprocess handle to open * * \returns * ::cudaSuccess, * ::cudaErrorMapBufferObjectFailed, * ::cudaErrorNotSupported, * ::cudaErrorInvalidValue, * ::cudaErrorDeviceUninitialized * \note_init_rt * \note_callback * * \sa * ::cudaEventCreate, * ::cudaEventDestroy, * ::cudaEventSynchronize, * ::cudaEventQuery, * ::cudaStreamWaitEvent, * ::cudaIpcGetEventHandle, * ::cudaIpcGetMemHandle, * ::cudaIpcOpenMemHandle, * ::cudaIpcCloseMemHandle, * ::cuIpcOpenEventHandle */ extern __host__ cudaError_t CUDARTAPI cudaIpcOpenEventHandle(cudaEvent_t *event, cudaIpcEventHandle_t handle); /** * \brief Gets an interprocess memory handle for an existing device memory * allocation * * Takes a pointer to the base of an existing device memory allocation created * with ::cudaMalloc and exports it for use in another process. This is a * lightweight operation and may be called multiple times on an allocation * without adverse effects. * * If a region of memory is freed with ::cudaFree and a subsequent call * to ::cudaMalloc returns memory with the same device address, * ::cudaIpcGetMemHandle will return a unique handle for the * new memory. * * IPC functionality is restricted to devices with support for unified * addressing on Linux and Windows operating systems. * IPC functionality on Windows is supported for compatibility purposes * but not recommended as it comes with performance cost. * Users can test their device for IPC functionality by calling * ::cudaDeviceGetAttribute with ::cudaDevAttrIpcEventSupport * * \param handle - Pointer to user allocated ::cudaIpcMemHandle to return * the handle in. * \param devPtr - Base pointer to previously allocated device memory * * \returns * ::cudaSuccess, * ::cudaErrorMemoryAllocation, * ::cudaErrorMapBufferObjectFailed, * ::cudaErrorNotSupported, * ::cudaErrorInvalidValue * \note_init_rt * \note_callback * * \sa * ::cudaMalloc, * ::cudaFree, * ::cudaIpcGetEventHandle, * ::cudaIpcOpenEventHandle, * ::cudaIpcOpenMemHandle, * ::cudaIpcCloseMemHandle, * ::cuIpcGetMemHandle */ extern __host__ cudaError_t CUDARTAPI cudaIpcGetMemHandle(cudaIpcMemHandle_t *handle, void *devPtr); /** * \brief Opens an interprocess memory handle exported from another process * and returns a device pointer usable in the local process. * * Maps memory exported from another process with ::cudaIpcGetMemHandle into * the current device address space. For contexts on different devices * ::cudaIpcOpenMemHandle can attempt to enable peer access between the * devices as if the user called ::cudaDeviceEnablePeerAccess. This behavior is * controlled by the ::cudaIpcMemLazyEnablePeerAccess flag. * ::cudaDeviceCanAccessPeer can determine if a mapping is possible. * * ::cudaIpcOpenMemHandle can open handles to devices that may not be visible * in the process calling the API. * * Contexts that may open ::cudaIpcMemHandles are restricted in the following way. * ::cudaIpcMemHandles from each device in a given process may only be opened * by one context per device per other process. * * If the memory handle has already been opened by the current context, the * reference count on the handle is incremented by 1 and the existing device pointer * is returned. * * Memory returned from ::cudaIpcOpenMemHandle must be freed with * ::cudaIpcCloseMemHandle. * * Calling ::cudaFree on an exported memory region before calling * ::cudaIpcCloseMemHandle in the importing context will result in undefined * behavior. * * IPC functionality is restricted to devices with support for unified * addressing on Linux and Windows operating systems. * IPC functionality on Windows is supported for compatibility purposes * but not recommended as it comes with performance cost. * Users can test their device for IPC functionality by calling * ::cudaDeviceGetAttribute with ::cudaDevAttrIpcEventSupport * * \param devPtr - Returned device pointer * \param handle - ::cudaIpcMemHandle to open * \param flags - Flags for this operation. Must be specified as ::cudaIpcMemLazyEnablePeerAccess * * \returns * ::cudaSuccess, * ::cudaErrorMapBufferObjectFailed, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorDeviceUninitialized, * ::cudaErrorTooManyPeers, * ::cudaErrorNotSupported, * ::cudaErrorInvalidValue * \note_init_rt * \note_callback * * \note No guarantees are made about the address returned in \p *devPtr. * In particular, multiple processes may not receive the same address for the same \p handle. * * \sa * ::cudaMalloc, * ::cudaFree, * ::cudaIpcGetEventHandle, * ::cudaIpcOpenEventHandle, * ::cudaIpcGetMemHandle, * ::cudaIpcCloseMemHandle, * ::cudaDeviceEnablePeerAccess, * ::cudaDeviceCanAccessPeer, * ::cuIpcOpenMemHandle */ extern __host__ cudaError_t CUDARTAPI cudaIpcOpenMemHandle(void **devPtr, cudaIpcMemHandle_t handle, unsigned int flags); /** * \brief Attempts to close memory mapped with cudaIpcOpenMemHandle * * Decrements the reference count of the memory returnd by ::cudaIpcOpenMemHandle by 1. * When the reference count reaches 0, this API unmaps the memory. The original allocation * in the exporting process as well as imported mappings in other processes * will be unaffected. * * Any resources used to enable peer access will be freed if this is the * last mapping using them. * * IPC functionality is restricted to devices with support for unified * addressing on Linux and Windows operating systems. * IPC functionality on Windows is supported for compatibility purposes * but not recommended as it comes with performance cost. * Users can test their device for IPC functionality by calling * ::cudaDeviceGetAttribute with ::cudaDevAttrIpcEventSupport * * \param devPtr - Device pointer returned by ::cudaIpcOpenMemHandle * * \returns * ::cudaSuccess, * ::cudaErrorMapBufferObjectFailed, * ::cudaErrorNotSupported, * ::cudaErrorInvalidValue * \note_init_rt * \note_callback * * \sa * ::cudaMalloc, * ::cudaFree, * ::cudaIpcGetEventHandle, * ::cudaIpcOpenEventHandle, * ::cudaIpcGetMemHandle, * ::cudaIpcOpenMemHandle, * ::cuIpcCloseMemHandle */ extern __host__ cudaError_t CUDARTAPI cudaIpcCloseMemHandle(void *devPtr); /** * \brief Blocks until remote writes are visible to the specified scope * * Blocks until remote writes to the target context via mappings created * through GPUDirect RDMA APIs, like nvidia_p2p_get_pages (see * https://docs.nvidia.com/cuda/gpudirect-rdma for more information), are * visible to the specified scope. * * If the scope equals or lies within the scope indicated by * ::cudaDevAttrGPUDirectRDMAWritesOrdering, the call will be a no-op and * can be safely omitted for performance. This can be determined by * comparing the numerical values between the two enums, with smaller * scopes having smaller values. * * Users may query support for this API via ::cudaDevAttrGPUDirectRDMAFlushWritesOptions. * * \param target - The target of the operation, see cudaFlushGPUDirectRDMAWritesTarget * \param scope - The scope of the operation, see cudaFlushGPUDirectRDMAWritesScope * * \return * ::cudaSuccess, * ::cudaErrorNotSupported, * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cuFlushGPUDirectRDMAWrites */ #if __CUDART_API_VERSION >= 11030 extern __host__ cudaError_t CUDARTAPI cudaDeviceFlushGPUDirectRDMAWrites(enum cudaFlushGPUDirectRDMAWritesTarget target, enum cudaFlushGPUDirectRDMAWritesScope scope); #endif /** * \brief Registers a callback function to receive async notifications * * Registers \p callbackFunc to receive async notifications. * * The \p userData parameter is passed to the callback function at async notification time. * Likewise, \p callback is also passed to the callback function to distinguish between * multiple registered callbacks. * * The callback function being registered should be designed to return quickly (~10ms). * Any long running tasks should be queued for execution on an application thread. * * Callbacks may not call cudaDeviceRegisterAsyncNotification or cudaDeviceUnregisterAsyncNotification. * Doing so will result in ::cudaErrorNotPermitted. Async notification callbacks execute * in an undefined order and may be serialized. * * Returns in \p *callback a handle representing the registered callback instance. * * \param device - The device on which to register the callback * \param callbackFunc - The function to register as a callback * \param userData - A generic pointer to user data. This is passed into the callback function. * \param callback - A handle representing the registered callback instance * * \return * ::cudaSuccess * ::cudaErrorNotSupported * ::cudaErrorInvalidDevice * ::cudaErrorInvalidValue * ::cudaErrorNotPermitted * ::cudaErrorUnknown * \notefnerr * * \sa * ::cudaDeviceUnregisterAsyncNotification */ extern __host__ cudaError_t CUDARTAPI cudaDeviceRegisterAsyncNotification(int device, cudaAsyncCallback callbackFunc, void* userData, cudaAsyncCallbackHandle_t* callback); /** * \brief Unregisters an async notification callback * * Unregisters \p callback so that the corresponding callback function will stop receiving * async notifications. * * \param device - The device from which to remove \p callback. * \param callback - The callback instance to unregister from receiving async notifications. * * \return * ::cudaSuccess * ::cudaErrorNotSupported * ::cudaErrorInvalidDevice * ::cudaErrorInvalidValue * ::cudaErrorNotPermitted * ::cudaErrorUnknown * \notefnerr * * \sa * ::cudaDeviceRegisterAsyncNotification */ extern __host__ cudaError_t CUDARTAPI cudaDeviceUnregisterAsyncNotification(int device, cudaAsyncCallbackHandle_t callback); /** @} */ /* END CUDART_DEVICE */ /** * \defgroup CUDART_DEVICE_DEPRECATED Device Management [DEPRECATED] * * ___MANBRIEF___ deprecated device management functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the deprecated device management functions of the CUDA runtime * application programming interface. * * @{ */ /** * \brief Returns the shared memory configuration for the current device. * * \deprecated * * This function will return in \p pConfig the current size of shared memory banks * on the current device. On devices with configurable shared memory banks, * ::cudaDeviceSetSharedMemConfig can be used to change this setting, so that all * subsequent kernel launches will by default use the new bank size. When * ::cudaDeviceGetSharedMemConfig is called on devices without configurable shared * memory, it will return the fixed bank size of the hardware. * * The returned bank configurations can be either: * - ::cudaSharedMemBankSizeFourByte - shared memory bank width is four bytes. * - ::cudaSharedMemBankSizeEightByte - shared memory bank width is eight bytes. * * \param pConfig - Returned cache configuration * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaDeviceSetCacheConfig, * ::cudaDeviceGetCacheConfig, * ::cudaDeviceSetSharedMemConfig, * ::cudaFuncSetCacheConfig, * ::cuCtxGetSharedMemConfig */ extern __CUDA_DEPRECATED __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaDeviceGetSharedMemConfig(enum cudaSharedMemConfig *pConfig); /** * \brief Sets the shared memory configuration for the current device. * * \deprecated * * On devices with configurable shared memory banks, this function will set * the shared memory bank size which is used for all subsequent kernel launches. * Any per-function setting of shared memory set via ::cudaFuncSetSharedMemConfig * will override the device wide setting. * * Changing the shared memory configuration between launches may introduce * a device side synchronization point. * * Changing the shared memory bank size will not increase shared memory usage * or affect occupancy of kernels, but may have major effects on performance. * Larger bank sizes will allow for greater potential bandwidth to shared memory, * but will change what kinds of accesses to shared memory will result in bank * conflicts. * * This function will do nothing on devices with fixed shared memory bank size. * * The supported bank configurations are: * - ::cudaSharedMemBankSizeDefault: set bank width the device default (currently, * four bytes) * - ::cudaSharedMemBankSizeFourByte: set shared memory bank width to be four bytes * natively. * - ::cudaSharedMemBankSizeEightByte: set shared memory bank width to be eight * bytes natively. * * \param config - Requested cache configuration * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaDeviceSetCacheConfig, * ::cudaDeviceGetCacheConfig, * ::cudaDeviceGetSharedMemConfig, * ::cudaFuncSetCacheConfig, * ::cuCtxSetSharedMemConfig */ extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaDeviceSetSharedMemConfig(enum cudaSharedMemConfig config); /** @} */ /* END CUDART_DEVICE_DEPRECATED */ /** * \defgroup CUDART_THREAD_DEPRECATED Thread Management [DEPRECATED] * * ___MANBRIEF___ deprecated thread management functions of the CUDA runtime * API (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes deprecated thread management functions of the CUDA runtime * application programming interface. * * @{ */ /** * \brief Exit and clean up from CUDA launches * * \deprecated * * Note that this function is deprecated because its name does not * reflect its behavior. Its functionality is identical to the * non-deprecated function ::cudaDeviceReset(), which should be used * instead. * * Explicitly destroys all cleans up all resources associated with the current * device in the current process. Any subsequent API call to this device will * reinitialize the device. * * Note that this function will reset the device immediately. It is the caller's * responsibility to ensure that the device is not being accessed by any * other host threads from the process when this function is called. * * \return * ::cudaSuccess * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaDeviceReset */ extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaThreadExit(void); /** * \brief Wait for compute device to finish * * \deprecated * * Note that this function is deprecated because its name does not * reflect its behavior. Its functionality is similar to the * non-deprecated function ::cudaDeviceSynchronize(), which should be used * instead. * * Blocks until the device has completed all preceding requested tasks. * ::cudaThreadSynchronize() returns an error if one of the preceding tasks * has failed. If the ::cudaDeviceScheduleBlockingSync flag was set for * this device, the host thread will block until the device has finished * its work. * * \return * ::cudaSuccess * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaDeviceSynchronize */ extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaThreadSynchronize(void); /** * \brief Set resource limits * * \deprecated * * Note that this function is deprecated because its name does not * reflect its behavior. Its functionality is identical to the * non-deprecated function ::cudaDeviceSetLimit(), which should be used * instead. * * Setting \p limit to \p value is a request by the application to update * the current limit maintained by the device. The driver is free to * modify the requested value to meet h/w requirements (this could be * clamping to minimum or maximum values, rounding up to nearest element * size, etc). The application can use ::cudaThreadGetLimit() to find out * exactly what the limit has been set to. * * Setting each ::cudaLimit has its own specific restrictions, so each is * discussed here. * * - ::cudaLimitStackSize controls the stack size of each GPU thread. * * - ::cudaLimitPrintfFifoSize controls the size of the shared FIFO * used by the ::printf() device system call. * Setting ::cudaLimitPrintfFifoSize must be performed before * launching any kernel that uses the ::printf() device * system call, otherwise ::cudaErrorInvalidValue will be returned. * * - ::cudaLimitMallocHeapSize controls the size of the heap used * by the ::malloc() and ::free() device system calls. Setting * ::cudaLimitMallocHeapSize must be performed before launching * any kernel that uses the ::malloc() or ::free() device system calls, * otherwise ::cudaErrorInvalidValue will be returned. * * \param limit - Limit to set * \param value - Size in bytes of limit * * \return * ::cudaSuccess, * ::cudaErrorUnsupportedLimit, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaDeviceSetLimit */ extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaThreadSetLimit(enum cudaLimit limit, size_t value); /** * \brief Returns resource limits * * \deprecated * * Note that this function is deprecated because its name does not * reflect its behavior. Its functionality is identical to the * non-deprecated function ::cudaDeviceGetLimit(), which should be used * instead. * * Returns in \p *pValue the current size of \p limit. The supported * ::cudaLimit values are: * - ::cudaLimitStackSize: stack size of each GPU thread; * - ::cudaLimitPrintfFifoSize: size of the shared FIFO used by the * ::printf() device system call. * - ::cudaLimitMallocHeapSize: size of the heap used by the * ::malloc() and ::free() device system calls; * * \param limit - Limit to query * \param pValue - Returned size in bytes of limit * * \return * ::cudaSuccess, * ::cudaErrorUnsupportedLimit, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaDeviceGetLimit */ extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaThreadGetLimit(size_t *pValue, enum cudaLimit limit); /** * \brief Returns the preferred cache configuration for the current device. * * \deprecated * * Note that this function is deprecated because its name does not * reflect its behavior. Its functionality is identical to the * non-deprecated function ::cudaDeviceGetCacheConfig(), which should be * used instead. * * On devices where the L1 cache and shared memory use the same hardware * resources, this returns through \p pCacheConfig the preferred cache * configuration for the current device. This is only a preference. The * runtime will use the requested configuration if possible, but it is free to * choose a different configuration if required to execute functions. * * This will return a \p pCacheConfig of ::cudaFuncCachePreferNone on devices * where the size of the L1 cache and shared memory are fixed. * * The supported cache configurations are: * - ::cudaFuncCachePreferNone: no preference for shared memory or L1 (default) * - ::cudaFuncCachePreferShared: prefer larger shared memory and smaller L1 cache * - ::cudaFuncCachePreferL1: prefer larger L1 cache and smaller shared memory * * \param pCacheConfig - Returned cache configuration * * \return * ::cudaSuccess * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaDeviceGetCacheConfig */ extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaThreadGetCacheConfig(enum cudaFuncCache *pCacheConfig); /** * \brief Sets the preferred cache configuration for the current device. * * \deprecated * * Note that this function is deprecated because its name does not * reflect its behavior. Its functionality is identical to the * non-deprecated function ::cudaDeviceSetCacheConfig(), which should be * used instead. * * On devices where the L1 cache and shared memory use the same hardware * resources, this sets through \p cacheConfig the preferred cache * configuration for the current device. This is only a preference. The * runtime will use the requested configuration if possible, but it is free to * choose a different configuration if required to execute the function. Any * function preference set via * \ref ::cudaFuncSetCacheConfig(const void*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C API)" * or * \ref ::cudaFuncSetCacheConfig(T*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C++ API)" * will be preferred over this device-wide setting. Setting the device-wide * cache configuration to ::cudaFuncCachePreferNone will cause subsequent * kernel launches to prefer to not change the cache configuration unless * required to launch the kernel. * * This setting does nothing on devices where the size of the L1 cache and * shared memory are fixed. * * Launching a kernel with a different preference than the most recent * preference setting may insert a device-side synchronization point. * * The supported cache configurations are: * - ::cudaFuncCachePreferNone: no preference for shared memory or L1 (default) * - ::cudaFuncCachePreferShared: prefer larger shared memory and smaller L1 cache * - ::cudaFuncCachePreferL1: prefer larger L1 cache and smaller shared memory * * \param cacheConfig - Requested cache configuration * * \return * ::cudaSuccess * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaDeviceSetCacheConfig */ extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaThreadSetCacheConfig(enum cudaFuncCache cacheConfig); /** @} */ /* END CUDART_THREAD_DEPRECATED */ /** * \defgroup CUDART_ERROR Error Handling * * ___MANBRIEF___ error handling functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the error handling functions of the CUDA runtime * application programming interface. * * @{ */ /** * \brief Returns the last error from a runtime call * * Returns the last error that has been produced by any of the runtime calls * in the same instance of the CUDA Runtime library in the host thread and * resets it to ::cudaSuccess. * * Note: Multiple instances of the CUDA Runtime library can be present in an * application when using a library that statically links the CUDA Runtime. * * \return * ::cudaSuccess, * ::cudaErrorMissingConfiguration, * ::cudaErrorMemoryAllocation, * ::cudaErrorInitializationError, * ::cudaErrorLaunchFailure, * ::cudaErrorLaunchTimeout, * ::cudaErrorLaunchOutOfResources, * ::cudaErrorInvalidDeviceFunction, * ::cudaErrorInvalidConfiguration, * ::cudaErrorInvalidDevice, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidPitchValue, * ::cudaErrorInvalidSymbol, * ::cudaErrorUnmapBufferObjectFailed, * ::cudaErrorInvalidDevicePointer, * ::cudaErrorInvalidTexture, * ::cudaErrorInvalidTextureBinding, * ::cudaErrorInvalidChannelDescriptor, * ::cudaErrorInvalidMemcpyDirection, * ::cudaErrorInvalidFilterSetting, * ::cudaErrorInvalidNormSetting, * ::cudaErrorUnknown, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorInsufficientDriver, * ::cudaErrorNoDevice, * ::cudaErrorSetOnActiveProcess, * ::cudaErrorStartupFailure, * ::cudaErrorInvalidPtx, * ::cudaErrorUnsupportedPtxVersion, * ::cudaErrorNoKernelImageForDevice, * ::cudaErrorJitCompilerNotFound, * ::cudaErrorJitCompilationDisabled * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaPeekAtLastError, ::cudaGetErrorName, ::cudaGetErrorString, ::cudaError */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaGetLastError(void); /** * \brief Returns the last error from a runtime call * * Returns the last error that has been produced by any of the runtime calls * in the same instance of the CUDA Runtime library in the host thread. This * call does not reset the error to ::cudaSuccess like ::cudaGetLastError(). * * Note: Multiple instances of the CUDA Runtime library can be present in an * application when using a library that statically links the CUDA Runtime. * * \return * ::cudaSuccess, * ::cudaErrorMissingConfiguration, * ::cudaErrorMemoryAllocation, * ::cudaErrorInitializationError, * ::cudaErrorLaunchFailure, * ::cudaErrorLaunchTimeout, * ::cudaErrorLaunchOutOfResources, * ::cudaErrorInvalidDeviceFunction, * ::cudaErrorInvalidConfiguration, * ::cudaErrorInvalidDevice, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidPitchValue, * ::cudaErrorInvalidSymbol, * ::cudaErrorUnmapBufferObjectFailed, * ::cudaErrorInvalidDevicePointer, * ::cudaErrorInvalidTexture, * ::cudaErrorInvalidTextureBinding, * ::cudaErrorInvalidChannelDescriptor, * ::cudaErrorInvalidMemcpyDirection, * ::cudaErrorInvalidFilterSetting, * ::cudaErrorInvalidNormSetting, * ::cudaErrorUnknown, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorInsufficientDriver, * ::cudaErrorNoDevice, * ::cudaErrorSetOnActiveProcess, * ::cudaErrorStartupFailure, * ::cudaErrorInvalidPtx, * ::cudaErrorUnsupportedPtxVersion, * ::cudaErrorNoKernelImageForDevice, * ::cudaErrorJitCompilerNotFound, * ::cudaErrorJitCompilationDisabled * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaGetLastError, ::cudaGetErrorName, ::cudaGetErrorString, ::cudaError */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaPeekAtLastError(void); /** * \brief Returns the string representation of an error code enum name * * Returns a string containing the name of an error code in the enum. If the error * code is not recognized, "unrecognized error code" is returned. * * \param error - Error code to convert to string * * \return * \p char* pointer to a NULL-terminated string * * \sa ::cudaGetErrorString, ::cudaGetLastError, ::cudaPeekAtLastError, ::cudaError, * ::cuGetErrorName */ extern __host__ __cudart_builtin__ const char* CUDARTAPI cudaGetErrorName(cudaError_t error); /** * \brief Returns the description string for an error code * * Returns the description string for an error code. If the error * code is not recognized, "unrecognized error code" is returned. * * \param error - Error code to convert to string * * \return * \p char* pointer to a NULL-terminated string * * \sa ::cudaGetErrorName, ::cudaGetLastError, ::cudaPeekAtLastError, ::cudaError, * ::cuGetErrorString */ extern __host__ __cudart_builtin__ const char* CUDARTAPI cudaGetErrorString(cudaError_t error); /** @} */ /* END CUDART_ERROR */ /** * \addtogroup CUDART_DEVICE * * @{ */ /** * \brief Returns the number of compute-capable devices * * Returns in \p *count the number of devices with compute capability greater * or equal to 2.0 that are available for execution. * * \param count - Returns the number of devices with compute capability * greater or equal to 2.0 * * \return * ::cudaSuccess * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaGetDevice, ::cudaSetDevice, ::cudaGetDeviceProperties, * ::cudaChooseDevice, * ::cudaInitDevice, * ::cuDeviceGetCount */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaGetDeviceCount(int *count); /** * \brief Returns information about the compute-device * * Returns in \p *prop the properties of device \p dev. The ::cudaDeviceProp * structure is defined as: * \code struct cudaDeviceProp { char name[256]; cudaUUID_t uuid; size_t totalGlobalMem; size_t sharedMemPerBlock; int regsPerBlock; int warpSize; size_t memPitch; int maxThreadsPerBlock; int maxThreadsDim[3]; int maxGridSize[3]; int clockRate; size_t totalConstMem; int major; int minor; size_t textureAlignment; size_t texturePitchAlignment; int deviceOverlap; int multiProcessorCount; int kernelExecTimeoutEnabled; int integrated; int canMapHostMemory; int computeMode; int maxTexture1D; int maxTexture1DMipmap; int maxTexture1DLinear; int maxTexture2D[2]; int maxTexture2DMipmap[2]; int maxTexture2DLinear[3]; int maxTexture2DGather[2]; int maxTexture3D[3]; int maxTexture3DAlt[3]; int maxTextureCubemap; int maxTexture1DLayered[2]; int maxTexture2DLayered[3]; int maxTextureCubemapLayered[2]; int maxSurface1D; int maxSurface2D[2]; int maxSurface3D[3]; int maxSurface1DLayered[2]; int maxSurface2DLayered[3]; int maxSurfaceCubemap; int maxSurfaceCubemapLayered[2]; size_t surfaceAlignment; int concurrentKernels; int ECCEnabled; int pciBusID; int pciDeviceID; int pciDomainID; int tccDriver; int asyncEngineCount; int unifiedAddressing; int memoryClockRate; int memoryBusWidth; int l2CacheSize; int persistingL2CacheMaxSize; int maxThreadsPerMultiProcessor; int streamPrioritiesSupported; int globalL1CacheSupported; int localL1CacheSupported; size_t sharedMemPerMultiprocessor; int regsPerMultiprocessor; int managedMemory; int isMultiGpuBoard; int multiGpuBoardGroupID; int singleToDoublePrecisionPerfRatio; int pageableMemoryAccess; int concurrentManagedAccess; int computePreemptionSupported; int canUseHostPointerForRegisteredMem; int cooperativeLaunch; int cooperativeMultiDeviceLaunch; int pageableMemoryAccessUsesHostPageTables; int directManagedMemAccessFromHost; int accessPolicyMaxWindowSize; } \endcode * where: * - \ref ::cudaDeviceProp::name "name[256]" is an ASCII string identifying * the device. * - \ref ::cudaDeviceProp::uuid "uuid" is a 16-byte unique identifier. * - \ref ::cudaDeviceProp::totalGlobalMem "totalGlobalMem" is the total * amount of global memory available on the device in bytes. * - \ref ::cudaDeviceProp::sharedMemPerBlock "sharedMemPerBlock" is the * maximum amount of shared memory available to a thread block in bytes. * - \ref ::cudaDeviceProp::regsPerBlock "regsPerBlock" is the maximum number * of 32-bit registers available to a thread block. * - \ref ::cudaDeviceProp::warpSize "warpSize" is the warp size in threads. * - \ref ::cudaDeviceProp::memPitch "memPitch" is the maximum pitch in * bytes allowed by the memory copy functions that involve memory regions * allocated through ::cudaMallocPitch(). * - \ref ::cudaDeviceProp::maxThreadsPerBlock "maxThreadsPerBlock" is the * maximum number of threads per block. * - \ref ::cudaDeviceProp::maxThreadsDim "maxThreadsDim[3]" contains the * maximum size of each dimension of a block. * - \ref ::cudaDeviceProp::maxGridSize "maxGridSize[3]" contains the * maximum size of each dimension of a grid. * - \ref ::cudaDeviceProp::clockRate "clockRate" is the clock frequency in * kilohertz. * - \ref ::cudaDeviceProp::totalConstMem "totalConstMem" is the total amount * of constant memory available on the device in bytes. * - \ref ::cudaDeviceProp::major "major", * \ref ::cudaDeviceProp::minor "minor" are the major and minor revision * numbers defining the device's compute capability. * - \ref ::cudaDeviceProp::textureAlignment "textureAlignment" is the * alignment requirement; texture base addresses that are aligned to * \ref ::cudaDeviceProp::textureAlignment "textureAlignment" bytes do not * need an offset applied to texture fetches. * - \ref ::cudaDeviceProp::texturePitchAlignment "texturePitchAlignment" is the * pitch alignment requirement for 2D texture references that are bound to * pitched memory. * - \ref ::cudaDeviceProp::deviceOverlap "deviceOverlap" is 1 if the device * can concurrently copy memory between host and device while executing a * kernel, or 0 if not. Deprecated, use instead asyncEngineCount. * - \ref ::cudaDeviceProp::multiProcessorCount "multiProcessorCount" is the * number of multiprocessors on the device. * - \ref ::cudaDeviceProp::kernelExecTimeoutEnabled "kernelExecTimeoutEnabled" * is 1 if there is a run time limit for kernels executed on the device, or * 0 if not. * - \ref ::cudaDeviceProp::integrated "integrated" is 1 if the device is an * integrated (motherboard) GPU and 0 if it is a discrete (card) component. * - \ref ::cudaDeviceProp::canMapHostMemory "canMapHostMemory" is 1 if the * device can map host memory into the CUDA address space for use with * ::cudaHostAlloc()/::cudaHostGetDevicePointer(), or 0 if not. * - \ref ::cudaDeviceProp::computeMode "computeMode" is the compute mode * that the device is currently in. Available modes are as follows: * - cudaComputeModeDefault: Default mode - Device is not restricted and * multiple threads can use ::cudaSetDevice() with this device. * - cudaComputeModeProhibited: Compute-prohibited mode - No threads can use * ::cudaSetDevice() with this device. * - cudaComputeModeExclusiveProcess: Compute-exclusive-process mode - Many * threads in one process will be able to use ::cudaSetDevice() with this device. *
When an occupied exclusive mode device is chosen with ::cudaSetDevice, * all subsequent non-device management runtime functions will return * ::cudaErrorDevicesUnavailable. * - \ref ::cudaDeviceProp::maxTexture1D "maxTexture1D" is the maximum 1D * texture size. * - \ref ::cudaDeviceProp::maxTexture1DMipmap "maxTexture1DMipmap" is the maximum * 1D mipmapped texture texture size. * - \ref ::cudaDeviceProp::maxTexture1DLinear "maxTexture1DLinear" is the maximum * 1D texture size for textures bound to linear memory. * - \ref ::cudaDeviceProp::maxTexture2D "maxTexture2D[2]" contains the maximum * 2D texture dimensions. * - \ref ::cudaDeviceProp::maxTexture2DMipmap "maxTexture2DMipmap[2]" contains the * maximum 2D mipmapped texture dimensions. * - \ref ::cudaDeviceProp::maxTexture2DLinear "maxTexture2DLinear[3]" contains the * maximum 2D texture dimensions for 2D textures bound to pitch linear memory. * - \ref ::cudaDeviceProp::maxTexture2DGather "maxTexture2DGather[2]" contains the * maximum 2D texture dimensions if texture gather operations have to be performed. * - \ref ::cudaDeviceProp::maxTexture3D "maxTexture3D[3]" contains the maximum * 3D texture dimensions. * - \ref ::cudaDeviceProp::maxTexture3DAlt "maxTexture3DAlt[3]" * contains the maximum alternate 3D texture dimensions. * - \ref ::cudaDeviceProp::maxTextureCubemap "maxTextureCubemap" is the * maximum cubemap texture width or height. * - \ref ::cudaDeviceProp::maxTexture1DLayered "maxTexture1DLayered[2]" contains * the maximum 1D layered texture dimensions. * - \ref ::cudaDeviceProp::maxTexture2DLayered "maxTexture2DLayered[3]" contains * the maximum 2D layered texture dimensions. * - \ref ::cudaDeviceProp::maxTextureCubemapLayered "maxTextureCubemapLayered[2]" * contains the maximum cubemap layered texture dimensions. * - \ref ::cudaDeviceProp::maxSurface1D "maxSurface1D" is the maximum 1D * surface size. * - \ref ::cudaDeviceProp::maxSurface2D "maxSurface2D[2]" contains the maximum * 2D surface dimensions. * - \ref ::cudaDeviceProp::maxSurface3D "maxSurface3D[3]" contains the maximum * 3D surface dimensions. * - \ref ::cudaDeviceProp::maxSurface1DLayered "maxSurface1DLayered[2]" contains * the maximum 1D layered surface dimensions. * - \ref ::cudaDeviceProp::maxSurface2DLayered "maxSurface2DLayered[3]" contains * the maximum 2D layered surface dimensions. * - \ref ::cudaDeviceProp::maxSurfaceCubemap "maxSurfaceCubemap" is the maximum * cubemap surface width or height. * - \ref ::cudaDeviceProp::maxSurfaceCubemapLayered "maxSurfaceCubemapLayered[2]" * contains the maximum cubemap layered surface dimensions. * - \ref ::cudaDeviceProp::surfaceAlignment "surfaceAlignment" specifies the * alignment requirements for surfaces. * - \ref ::cudaDeviceProp::concurrentKernels "concurrentKernels" is 1 if the * device supports executing multiple kernels within the same context * simultaneously, or 0 if not. It is not guaranteed that multiple kernels * will be resident on the device concurrently so this feature should not be * relied upon for correctness. * - \ref ::cudaDeviceProp::ECCEnabled "ECCEnabled" is 1 if the device has ECC * support turned on, or 0 if not. * - \ref ::cudaDeviceProp::pciBusID "pciBusID" is the PCI bus identifier of * the device. * - \ref ::cudaDeviceProp::pciDeviceID "pciDeviceID" is the PCI device * (sometimes called slot) identifier of the device. * - \ref ::cudaDeviceProp::pciDomainID "pciDomainID" is the PCI domain identifier * of the device. * - \ref ::cudaDeviceProp::tccDriver "tccDriver" is 1 if the device is using a * TCC driver or 0 if not. * - \ref ::cudaDeviceProp::asyncEngineCount "asyncEngineCount" is 1 when the * device can concurrently copy memory between host and device while executing * a kernel. It is 2 when the device can concurrently copy memory between host * and device in both directions and execute a kernel at the same time. It is * 0 if neither of these is supported. * - \ref ::cudaDeviceProp::unifiedAddressing "unifiedAddressing" is 1 if the device * shares a unified address space with the host and 0 otherwise. * - \ref ::cudaDeviceProp::memoryClockRate "memoryClockRate" is the peak memory * clock frequency in kilohertz. * - \ref ::cudaDeviceProp::memoryBusWidth "memoryBusWidth" is the memory bus width * in bits. * - \ref ::cudaDeviceProp::l2CacheSize "l2CacheSize" is L2 cache size in bytes. * - \ref ::cudaDeviceProp::persistingL2CacheMaxSize "persistingL2CacheMaxSize" is L2 cache's maximum persisting lines size in bytes. * - \ref ::cudaDeviceProp::maxThreadsPerMultiProcessor "maxThreadsPerMultiProcessor" * is the number of maximum resident threads per multiprocessor. * - \ref ::cudaDeviceProp::streamPrioritiesSupported "streamPrioritiesSupported" * is 1 if the device supports stream priorities, or 0 if it is not supported. * - \ref ::cudaDeviceProp::globalL1CacheSupported "globalL1CacheSupported" * is 1 if the device supports caching of globals in L1 cache, or 0 if it is not supported. * - \ref ::cudaDeviceProp::localL1CacheSupported "localL1CacheSupported" * is 1 if the device supports caching of locals in L1 cache, or 0 if it is not supported. * - \ref ::cudaDeviceProp::sharedMemPerMultiprocessor "sharedMemPerMultiprocessor" is the * maximum amount of shared memory available to a multiprocessor in bytes; this amount is * shared by all thread blocks simultaneously resident on a multiprocessor. * - \ref ::cudaDeviceProp::regsPerMultiprocessor "regsPerMultiprocessor" is the maximum number * of 32-bit registers available to a multiprocessor; this number is shared * by all thread blocks simultaneously resident on a multiprocessor. * - \ref ::cudaDeviceProp::managedMemory "managedMemory" * is 1 if the device supports allocating managed memory on this system, or 0 if it is not supported. * - \ref ::cudaDeviceProp::isMultiGpuBoard "isMultiGpuBoard" * is 1 if the device is on a multi-GPU board (e.g. Gemini cards), and 0 if not; * - \ref ::cudaDeviceProp::multiGpuBoardGroupID "multiGpuBoardGroupID" is a unique identifier * for a group of devices associated with the same board. * Devices on the same multi-GPU board will share the same identifier. * - \ref ::cudaDeviceProp::hostNativeAtomicSupported "hostNativeAtomicSupported" * is 1 if the link between the device and the host supports native atomic operations, or 0 if it is not supported. * - \ref ::cudaDeviceProp::singleToDoublePrecisionPerfRatio "singleToDoublePrecisionPerfRatio" * is the ratio of single precision performance (in floating-point operations per second) * to double precision performance. * - \ref ::cudaDeviceProp::pageableMemoryAccess "pageableMemoryAccess" is 1 if the device supports * coherently accessing pageable memory without calling cudaHostRegister on it, and 0 otherwise. * - \ref ::cudaDeviceProp::concurrentManagedAccess "concurrentManagedAccess" is 1 if the device can * coherently access managed memory concurrently with the CPU, and 0 otherwise. * - \ref ::cudaDeviceProp::computePreemptionSupported "computePreemptionSupported" is 1 if the device * supports Compute Preemption, and 0 otherwise. * - \ref ::cudaDeviceProp::canUseHostPointerForRegisteredMem "canUseHostPointerForRegisteredMem" is 1 if * the device can access host registered memory at the same virtual address as the CPU, and 0 otherwise. * - \ref ::cudaDeviceProp::cooperativeLaunch "cooperativeLaunch" is 1 if the device supports launching * cooperative kernels via ::cudaLaunchCooperativeKernel, and 0 otherwise. * - \ref ::cudaDeviceProp::cooperativeMultiDeviceLaunch "cooperativeMultiDeviceLaunch" is 1 if the device * supports launching cooperative kernels via ::cudaLaunchCooperativeKernelMultiDevice, and 0 otherwise. * - \ref ::cudaDeviceProp::sharedMemPerBlockOptin "sharedMemPerBlockOptin" * is the per device maximum shared memory per block usable by special opt in * - \ref ::cudaDeviceProp::pageableMemoryAccessUsesHostPageTables "pageableMemoryAccessUsesHostPageTables" is 1 if the device accesses * pageable memory via the host's page tables, and 0 otherwise. * - \ref ::cudaDeviceProp::directManagedMemAccessFromHost "directManagedMemAccessFromHost" is 1 if the host can directly access managed * memory on the device without migration, and 0 otherwise. * - \ref ::cudaDeviceProp::maxBlocksPerMultiProcessor "maxBlocksPerMultiProcessor" is the maximum number of thread blocks * that can reside on a multiprocessor. * - \ref ::cudaDeviceProp::accessPolicyMaxWindowSize "accessPolicyMaxWindowSize" is * the maximum value of ::cudaAccessPolicyWindow::num_bytes. * - \ref ::cudaDeviceProp::reservedSharedMemPerBlock "reservedSharedMemPerBlock" * is the shared memory reserved by CUDA driver per block in bytes * - \ref ::cudaDeviceProp::hostRegisterSupported "hostRegisterSupported" * is 1 if the device supports host memory registration via ::cudaHostRegister, and 0 otherwise. * - \ref ::cudaDeviceProp::sparseCudaArraySupported "sparseCudaArraySupported" * is 1 if the device supports sparse CUDA arrays and sparse CUDA mipmapped arrays, 0 otherwise * - \ref ::cudaDeviceProp::hostRegisterReadOnlySupported "hostRegisterReadOnlySupported" * is 1 if the device supports using the ::cudaHostRegister flag cudaHostRegisterReadOnly to register memory that must be mapped as * read-only to the GPU * - \ref ::cudaDeviceProp::timelineSemaphoreInteropSupported "timelineSemaphoreInteropSupported" * is 1 if external timeline semaphore interop is supported on the device, 0 otherwise * - \ref ::cudaDeviceProp::memoryPoolsSupported "memoryPoolsSupported" * is 1 if the device supports using the cudaMallocAsync and cudaMemPool family of APIs, 0 otherwise * - \ref ::cudaDeviceProp::gpuDirectRDMASupported "gpuDirectRDMASupported" * is 1 if the device supports GPUDirect RDMA APIs, 0 otherwise * - \ref ::cudaDeviceProp::gpuDirectRDMAFlushWritesOptions "gpuDirectRDMAFlushWritesOptions" * is a bitmask to be interpreted according to the ::cudaFlushGPUDirectRDMAWritesOptions enum * - \ref ::cudaDeviceProp::gpuDirectRDMAWritesOrdering "gpuDirectRDMAWritesOrdering" * See the ::cudaGPUDirectRDMAWritesOrdering enum for numerical values * - \ref ::cudaDeviceProp::memoryPoolSupportedHandleTypes "memoryPoolSupportedHandleTypes" * is a bitmask of handle types supported with mempool-based IPC * - \ref ::cudaDeviceProp::deferredMappingCudaArraySupported "deferredMappingCudaArraySupported" * is 1 if the device supports deferred mapping CUDA arrays and CUDA mipmapped arrays * - \ref ::cudaDeviceProp::ipcEventSupported "ipcEventSupported" * is 1 if the device supports IPC Events, and 0 otherwise * - \ref ::cudaDeviceProp::unifiedFunctionPointers "unifiedFunctionPointers" * is 1 if the device support unified pointers, and 0 otherwise * \param prop - Properties for the specified device * \param device - Device number to get properties for * * \return * ::cudaSuccess, * ::cudaErrorInvalidDevice * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaGetDeviceCount, ::cudaGetDevice, ::cudaSetDevice, ::cudaChooseDevice, * ::cudaDeviceGetAttribute, * ::cudaInitDevice, * ::cuDeviceGetAttribute, * ::cuDeviceGetName */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaGetDeviceProperties(struct cudaDeviceProp *prop, int device); /** * \brief Returns information about the device * * Returns in \p *value the integer value of the attribute \p attr on device * \p device. The supported attributes are: * - ::cudaDevAttrMaxThreadsPerBlock: Maximum number of threads per block * - ::cudaDevAttrMaxBlockDimX: Maximum x-dimension of a block * - ::cudaDevAttrMaxBlockDimY: Maximum y-dimension of a block * - ::cudaDevAttrMaxBlockDimZ: Maximum z-dimension of a block * - ::cudaDevAttrMaxGridDimX: Maximum x-dimension of a grid * - ::cudaDevAttrMaxGridDimY: Maximum y-dimension of a grid * - ::cudaDevAttrMaxGridDimZ: Maximum z-dimension of a grid * - ::cudaDevAttrMaxSharedMemoryPerBlock: Maximum amount of shared memory * available to a thread block in bytes * - ::cudaDevAttrTotalConstantMemory: Memory available on device for * __constant__ variables in a CUDA C kernel in bytes * - ::cudaDevAttrWarpSize: Warp size in threads * - ::cudaDevAttrMaxPitch: Maximum pitch in bytes allowed by the memory copy * functions that involve memory regions allocated through ::cudaMallocPitch() * - ::cudaDevAttrMaxTexture1DWidth: Maximum 1D texture width * - ::cudaDevAttrMaxTexture1DLinearWidth: Maximum width for a 1D texture bound * to linear memory * - ::cudaDevAttrMaxTexture1DMipmappedWidth: Maximum mipmapped 1D texture width * - ::cudaDevAttrMaxTexture2DWidth: Maximum 2D texture width * - ::cudaDevAttrMaxTexture2DHeight: Maximum 2D texture height * - ::cudaDevAttrMaxTexture2DLinearWidth: Maximum width for a 2D texture * bound to linear memory * - ::cudaDevAttrMaxTexture2DLinearHeight: Maximum height for a 2D texture * bound to linear memory * - ::cudaDevAttrMaxTexture2DLinearPitch: Maximum pitch in bytes for a 2D * texture bound to linear memory * - ::cudaDevAttrMaxTexture2DMipmappedWidth: Maximum mipmapped 2D texture * width * - ::cudaDevAttrMaxTexture2DMipmappedHeight: Maximum mipmapped 2D texture * height * - ::cudaDevAttrMaxTexture3DWidth: Maximum 3D texture width * - ::cudaDevAttrMaxTexture3DHeight: Maximum 3D texture height * - ::cudaDevAttrMaxTexture3DDepth: Maximum 3D texture depth * - ::cudaDevAttrMaxTexture3DWidthAlt: Alternate maximum 3D texture width, * 0 if no alternate maximum 3D texture size is supported * - ::cudaDevAttrMaxTexture3DHeightAlt: Alternate maximum 3D texture height, * 0 if no alternate maximum 3D texture size is supported * - ::cudaDevAttrMaxTexture3DDepthAlt: Alternate maximum 3D texture depth, * 0 if no alternate maximum 3D texture size is supported * - ::cudaDevAttrMaxTextureCubemapWidth: Maximum cubemap texture width or * height * - ::cudaDevAttrMaxTexture1DLayeredWidth: Maximum 1D layered texture width * - ::cudaDevAttrMaxTexture1DLayeredLayers: Maximum layers in a 1D layered * texture * - ::cudaDevAttrMaxTexture2DLayeredWidth: Maximum 2D layered texture width * - ::cudaDevAttrMaxTexture2DLayeredHeight: Maximum 2D layered texture height * - ::cudaDevAttrMaxTexture2DLayeredLayers: Maximum layers in a 2D layered * texture * - ::cudaDevAttrMaxTextureCubemapLayeredWidth: Maximum cubemap layered * texture width or height * - ::cudaDevAttrMaxTextureCubemapLayeredLayers: Maximum layers in a cubemap * layered texture * - ::cudaDevAttrMaxSurface1DWidth: Maximum 1D surface width * - ::cudaDevAttrMaxSurface2DWidth: Maximum 2D surface width * - ::cudaDevAttrMaxSurface2DHeight: Maximum 2D surface height * - ::cudaDevAttrMaxSurface3DWidth: Maximum 3D surface width * - ::cudaDevAttrMaxSurface3DHeight: Maximum 3D surface height * - ::cudaDevAttrMaxSurface3DDepth: Maximum 3D surface depth * - ::cudaDevAttrMaxSurface1DLayeredWidth: Maximum 1D layered surface width * - ::cudaDevAttrMaxSurface1DLayeredLayers: Maximum layers in a 1D layered * surface * - ::cudaDevAttrMaxSurface2DLayeredWidth: Maximum 2D layered surface width * - ::cudaDevAttrMaxSurface2DLayeredHeight: Maximum 2D layered surface height * - ::cudaDevAttrMaxSurface2DLayeredLayers: Maximum layers in a 2D layered * surface * - ::cudaDevAttrMaxSurfaceCubemapWidth: Maximum cubemap surface width * - ::cudaDevAttrMaxSurfaceCubemapLayeredWidth: Maximum cubemap layered * surface width * - ::cudaDevAttrMaxSurfaceCubemapLayeredLayers: Maximum layers in a cubemap * layered surface * - ::cudaDevAttrMaxRegistersPerBlock: Maximum number of 32-bit registers * available to a thread block * - ::cudaDevAttrClockRate: Peak clock frequency in kilohertz * - ::cudaDevAttrTextureAlignment: Alignment requirement; texture base * addresses aligned to ::textureAlign bytes do not need an offset applied * to texture fetches * - ::cudaDevAttrTexturePitchAlignment: Pitch alignment requirement for 2D * texture references bound to pitched memory * - ::cudaDevAttrGpuOverlap: 1 if the device can concurrently copy memory * between host and device while executing a kernel, or 0 if not * - ::cudaDevAttrMultiProcessorCount: Number of multiprocessors on the device * - ::cudaDevAttrKernelExecTimeout: 1 if there is a run time limit for kernels * executed on the device, or 0 if not * - ::cudaDevAttrIntegrated: 1 if the device is integrated with the memory * subsystem, or 0 if not * - ::cudaDevAttrCanMapHostMemory: 1 if the device can map host memory into * the CUDA address space, or 0 if not * - ::cudaDevAttrComputeMode: Compute mode is the compute mode that the device * is currently in. Available modes are as follows: * - ::cudaComputeModeDefault: Default mode - Device is not restricted and * multiple threads can use ::cudaSetDevice() with this device. * - ::cudaComputeModeProhibited: Compute-prohibited mode - No threads can use * ::cudaSetDevice() with this device. * - ::cudaComputeModeExclusiveProcess: Compute-exclusive-process mode - Many * threads in one process will be able to use ::cudaSetDevice() with this * device. * - ::cudaDevAttrConcurrentKernels: 1 if the device supports executing * multiple kernels within the same context simultaneously, or 0 if * not. It is not guaranteed that multiple kernels will be resident on the * device concurrently so this feature should not be relied upon for * correctness. * - ::cudaDevAttrEccEnabled: 1 if error correction is enabled on the device, * 0 if error correction is disabled or not supported by the device * - ::cudaDevAttrPciBusId: PCI bus identifier of the device * - ::cudaDevAttrPciDeviceId: PCI device (also known as slot) identifier of * the device * - ::cudaDevAttrTccDriver: 1 if the device is using a TCC driver. TCC is only * available on Tesla hardware running Windows Vista or later. * - ::cudaDevAttrMemoryClockRate: Peak memory clock frequency in kilohertz * - ::cudaDevAttrGlobalMemoryBusWidth: Global memory bus width in bits * - ::cudaDevAttrL2CacheSize: Size of L2 cache in bytes. 0 if the device * doesn't have L2 cache. * - ::cudaDevAttrMaxThreadsPerMultiProcessor: Maximum resident threads per * multiprocessor * - ::cudaDevAttrUnifiedAddressing: 1 if the device shares a unified address * space with the host, or 0 if not * - ::cudaDevAttrComputeCapabilityMajor: Major compute capability version * number * - ::cudaDevAttrComputeCapabilityMinor: Minor compute capability version * number * - ::cudaDevAttrStreamPrioritiesSupported: 1 if the device supports stream * priorities, or 0 if not * - ::cudaDevAttrGlobalL1CacheSupported: 1 if device supports caching globals * in L1 cache, 0 if not * - ::cudaDevAttrLocalL1CacheSupported: 1 if device supports caching locals * in L1 cache, 0 if not * - ::cudaDevAttrMaxSharedMemoryPerMultiprocessor: Maximum amount of shared memory * available to a multiprocessor in bytes; this amount is shared by all * thread blocks simultaneously resident on a multiprocessor * - ::cudaDevAttrMaxRegistersPerMultiprocessor: Maximum number of 32-bit registers * available to a multiprocessor; this number is shared by all thread blocks * simultaneously resident on a multiprocessor * - ::cudaDevAttrManagedMemory: 1 if device supports allocating * managed memory, 0 if not * - ::cudaDevAttrIsMultiGpuBoard: 1 if device is on a multi-GPU board, 0 if not * - ::cudaDevAttrMultiGpuBoardGroupID: Unique identifier for a group of devices on the * same multi-GPU board * - ::cudaDevAttrHostNativeAtomicSupported: 1 if the link between the device and the * host supports native atomic operations * - ::cudaDevAttrSingleToDoublePrecisionPerfRatio: Ratio of single precision performance * (in floating-point operations per second) to double precision performance * - ::cudaDevAttrPageableMemoryAccess: 1 if the device supports coherently accessing * pageable memory without calling cudaHostRegister on it, and 0 otherwise * - ::cudaDevAttrConcurrentManagedAccess: 1 if the device can coherently access managed * memory concurrently with the CPU, and 0 otherwise * - ::cudaDevAttrComputePreemptionSupported: 1 if the device supports * Compute Preemption, 0 if not * - ::cudaDevAttrCanUseHostPointerForRegisteredMem: 1 if the device can access host * registered memory at the same virtual address as the CPU, and 0 otherwise * - ::cudaDevAttrCooperativeLaunch: 1 if the device supports launching cooperative kernels * via ::cudaLaunchCooperativeKernel, and 0 otherwise * - ::cudaDevAttrCooperativeMultiDeviceLaunch: 1 if the device supports launching cooperative * kernels via ::cudaLaunchCooperativeKernelMultiDevice, and 0 otherwise * - ::cudaDevAttrCanFlushRemoteWrites: 1 if the device supports flushing of outstanding * remote writes, and 0 otherwise * - ::cudaDevAttrHostRegisterSupported: 1 if the device supports host memory registration * via ::cudaHostRegister, and 0 otherwise * - ::cudaDevAttrPageableMemoryAccessUsesHostPageTables: 1 if the device accesses pageable memory via the * host's page tables, and 0 otherwise * - ::cudaDevAttrDirectManagedMemAccessFromHost: 1 if the host can directly access managed memory on the device * without migration, and 0 otherwise * - ::cudaDevAttrMaxSharedMemoryPerBlockOptin: Maximum per block shared memory size on the device. This value can * be opted into when using ::cudaFuncSetAttribute * - ::cudaDevAttrMaxBlocksPerMultiprocessor: Maximum number of thread blocks that can reside on a multiprocessor * - ::cudaDevAttrMaxPersistingL2CacheSize: Maximum L2 persisting lines capacity setting in bytes * - ::cudaDevAttrMaxAccessPolicyWindowSize: Maximum value of cudaAccessPolicyWindow::num_bytes * - ::cudaDevAttrReservedSharedMemoryPerBlock: Shared memory reserved by CUDA driver per block in bytes * - ::cudaDevAttrSparseCudaArraySupported: 1 if the device supports sparse CUDA arrays and sparse CUDA mipmapped arrays. * - ::cudaDevAttrHostRegisterReadOnlySupported: Device supports using the ::cudaHostRegister flag cudaHostRegisterReadOnly * to register memory that must be mapped as read-only to the GPU * - ::cudaDevAttrMemoryPoolsSupported: 1 if the device supports using the cudaMallocAsync and cudaMemPool family of APIs, and 0 otherwise * - ::cudaDevAttrGPUDirectRDMASupported: 1 if the device supports GPUDirect RDMA APIs, and 0 otherwise * - ::cudaDevAttrGPUDirectRDMAFlushWritesOptions: bitmask to be interpreted according to the ::cudaFlushGPUDirectRDMAWritesOptions enum * - ::cudaDevAttrGPUDirectRDMAWritesOrdering: see the ::cudaGPUDirectRDMAWritesOrdering enum for numerical values * - ::cudaDevAttrMemoryPoolSupportedHandleTypes: Bitmask of handle types supported with mempool based IPC * - ::cudaDevAttrDeferredMappingCudaArraySupported : 1 if the device supports deferred mapping CUDA arrays and CUDA mipmapped arrays. * - ::cudaDevAttrIpcEventSupport: 1 if the device supports IPC Events. * - ::cudaDevAttrNumaConfig: NUMA configuration of a device: value is of type ::cudaDeviceNumaConfig enum * - ::cudaDevAttrNumaId: NUMA node ID of the GPU memory * - ::cudaDevAttrGpuPciDeviceId: The combined 16-bit PCI device ID and 16-bit PCI vendor ID. * - ::cudaDevAttrGpuPciSubsystemId: The combined 16-bit PCI subsystem ID and 16-bit PCI vendor subsystem ID. * * \param value - Returned device attribute value * \param attr - Device attribute to query * \param device - Device number to query * * \return * ::cudaSuccess, * ::cudaErrorInvalidDevice, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaGetDeviceCount, ::cudaGetDevice, ::cudaSetDevice, ::cudaChooseDevice, * ::cudaGetDeviceProperties, * ::cudaInitDevice, * ::cuDeviceGetAttribute */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaDeviceGetAttribute(int *value, enum cudaDeviceAttr attr, int device); /** * \brief Returns the default mempool of a device * * The default mempool of a device contains device memory from that device. * * \return * ::cudaSuccess, * ::cudaErrorInvalidDevice, * ::cudaErrorInvalidValue * ::cudaErrorNotSupported * \notefnerr * \note_init_rt * \note_callback * * \sa ::cuDeviceGetDefaultMemPool, ::cudaMallocAsync, ::cudaMemPoolTrimTo, ::cudaMemPoolGetAttribute, ::cudaDeviceSetMemPool, ::cudaMemPoolSetAttribute, ::cudaMemPoolSetAccess */ extern __host__ cudaError_t CUDARTAPI cudaDeviceGetDefaultMemPool(cudaMemPool_t *memPool, int device); /** * \brief Sets the current memory pool of a device * * The memory pool must be local to the specified device. * Unless a mempool is specified in the ::cudaMallocAsync call, * ::cudaMallocAsync allocates from the current mempool of the provided stream's device. * By default, a device's current memory pool is its default memory pool. * * \note Use ::cudaMallocFromPoolAsync to specify asynchronous allocations from a device different * than the one the stream runs on. * * \returns * ::cudaSuccess, * ::cudaErrorInvalidValue * ::cudaErrorInvalidDevice * ::cudaErrorNotSupported * \notefnerr * \note_callback * * \sa ::cuDeviceSetMemPool, ::cudaDeviceGetMemPool, ::cudaDeviceGetDefaultMemPool, ::cudaMemPoolCreate, ::cudaMemPoolDestroy, ::cudaMallocFromPoolAsync */ extern __host__ cudaError_t CUDARTAPI cudaDeviceSetMemPool(int device, cudaMemPool_t memPool); /** * \brief Gets the current mempool for a device * * Returns the last pool provided to ::cudaDeviceSetMemPool for this device * or the device's default memory pool if ::cudaDeviceSetMemPool has never been called. * By default the current mempool is the default mempool for a device, * otherwise the returned pool must have been set with ::cuDeviceSetMemPool or ::cudaDeviceSetMemPool. * * \returns * ::cudaSuccess, * ::cudaErrorInvalidValue * ::cudaErrorNotSupported * \notefnerr * \note_init_rt * \note_callback * * \sa ::cuDeviceGetMemPool, ::cudaDeviceGetDefaultMemPool, ::cudaDeviceSetMemPool */ extern __host__ cudaError_t CUDARTAPI cudaDeviceGetMemPool(cudaMemPool_t *memPool, int device); /** * \brief Return NvSciSync attributes that this device can support. * * Returns in \p nvSciSyncAttrList, the properties of NvSciSync that * this CUDA device, \p dev can support. The returned \p nvSciSyncAttrList * can be used to create an NvSciSync that matches this device's capabilities. * * If NvSciSyncAttrKey_RequiredPerm field in \p nvSciSyncAttrList is * already set this API will return ::cudaErrorInvalidValue. * * The applications should set \p nvSciSyncAttrList to a valid * NvSciSyncAttrList failing which this API will return * ::cudaErrorInvalidHandle. * * The \p flags controls how applications intends to use * the NvSciSync created from the \p nvSciSyncAttrList. The valid flags are: * - ::cudaNvSciSyncAttrSignal, specifies that the applications intends to * signal an NvSciSync on this CUDA device. * - ::cudaNvSciSyncAttrWait, specifies that the applications intends to * wait on an NvSciSync on this CUDA device. * * At least one of these flags must be set, failing which the API * returns ::cudaErrorInvalidValue. Both the flags are orthogonal * to one another: a developer may set both these flags that allows to * set both wait and signal specific attributes in the same \p nvSciSyncAttrList. * * Note that this API updates the input \p nvSciSyncAttrList with values equivalent * to the following public attribute key-values: * NvSciSyncAttrKey_RequiredPerm is set to * - NvSciSyncAccessPerm_SignalOnly if ::cudaNvSciSyncAttrSignal is set in \p flags. * - NvSciSyncAccessPerm_WaitOnly if ::cudaNvSciSyncAttrWait is set in \p flags. * - NvSciSyncAccessPerm_WaitSignal if both ::cudaNvSciSyncAttrWait and * ::cudaNvSciSyncAttrSignal are set in \p flags. * NvSciSyncAttrKey_PrimitiveInfo is set to * - NvSciSyncAttrValPrimitiveType_SysmemSemaphore on any valid \p device. * - NvSciSyncAttrValPrimitiveType_Syncpoint if \p device is a Tegra device. * - NvSciSyncAttrValPrimitiveType_SysmemSemaphorePayload64b if \p device is GA10X+. * NvSciSyncAttrKey_GpuId is set to the same UUID that is returned in * \p cudaDeviceProp.uuid from ::cudaDeviceGetProperties for this \p device. * * \param nvSciSyncAttrList - Return NvSciSync attributes supported. * \param device - Valid Cuda Device to get NvSciSync attributes for. * \param flags - flags describing NvSciSync usage. * * \return * * ::cudaSuccess, * ::cudaErrorDeviceUninitialized, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidHandle, * ::cudaErrorInvalidDevice, * ::cudaErrorNotSupported, * ::cudaErrorMemoryAllocation * * \sa * ::cudaImportExternalSemaphore, * ::cudaDestroyExternalSemaphore, * ::cudaSignalExternalSemaphoresAsync, * ::cudaWaitExternalSemaphoresAsync */ extern __host__ cudaError_t CUDARTAPI cudaDeviceGetNvSciSyncAttributes(void *nvSciSyncAttrList, int device, int flags); /** * \brief Queries attributes of the link between two devices. * * Returns in \p *value the value of the requested attribute \p attrib of the * link between \p srcDevice and \p dstDevice. The supported attributes are: * - ::cudaDevP2PAttrPerformanceRank: A relative value indicating the * performance of the link between two devices. Lower value means better * performance (0 being the value used for most performant link). * - ::cudaDevP2PAttrAccessSupported: 1 if peer access is enabled. * - ::cudaDevP2PAttrNativeAtomicSupported: 1 if native atomic operations over * the link are supported. * - ::cudaDevP2PAttrCudaArrayAccessSupported: 1 if accessing CUDA arrays over * the link is supported. * * Returns ::cudaErrorInvalidDevice if \p srcDevice or \p dstDevice are not valid * or if they represent the same device. * * Returns ::cudaErrorInvalidValue if \p attrib is not valid or if \p value is * a null pointer. * * \param value - Returned value of the requested attribute * \param attrib - The requested attribute of the link between \p srcDevice and \p dstDevice. * \param srcDevice - The source device of the target link. * \param dstDevice - The destination device of the target link. * * \return * ::cudaSuccess, * ::cudaErrorInvalidDevice, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaDeviceEnablePeerAccess, * ::cudaDeviceDisablePeerAccess, * ::cudaDeviceCanAccessPeer, * ::cuDeviceGetP2PAttribute */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaDeviceGetP2PAttribute(int *value, enum cudaDeviceP2PAttr attr, int srcDevice, int dstDevice); /** * \brief Select compute-device which best matches criteria * * Returns in \p *device the device which has properties that best match * \p *prop. * * \param device - Device with best match * \param prop - Desired device properties * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaGetDeviceCount, ::cudaGetDevice, ::cudaSetDevice, * ::cudaGetDeviceProperties, * ::cudaInitDevice */ extern __host__ cudaError_t CUDARTAPI cudaChooseDevice(int *device, const struct cudaDeviceProp *prop); /** * \brief Initialize device to be used for GPU executions * * This function will initialize the CUDA Runtime structures and primary context on \p device when called, * but the context will not be made current to \p device. * * When ::cudaInitDeviceFlagsAreValid is set in \p flags, deviceFlags are applied to the requested device. * The values of deviceFlags match those of the flags parameters in ::cudaSetDeviceFlags. * The effect may be verified by ::cudaGetDeviceFlags. * * This function will return an error if the device is in ::cudaComputeModeExclusiveProcess * and is occupied by another process or if the device is in ::cudaComputeModeProhibited. * * \param device - Device on which the runtime will initialize itself. * \param deviceFlags - Parameters for device operation. * \param flags - Flags for controlling the device initialization. * * \return * ::cudaSuccess, * ::cudaErrorInvalidDevice, * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaGetDeviceCount, ::cudaGetDevice, ::cudaGetDeviceProperties, * ::cudaChooseDevice, ::cudaSetDevice * ::cuCtxSetCurrent */ extern __host__ cudaError_t CUDARTAPI cudaInitDevice(int device, unsigned int deviceFlags, unsigned int flags); /** * \brief Set device to be used for GPU executions * * Sets \p device as the current device for the calling host thread. * Valid device id's are 0 to (::cudaGetDeviceCount() - 1). * * Any device memory subsequently allocated from this host thread * using ::cudaMalloc(), ::cudaMallocPitch() or ::cudaMallocArray() * will be physically resident on \p device. Any host memory allocated * from this host thread using ::cudaMallocHost() or ::cudaHostAlloc() * or ::cudaHostRegister() will have its lifetime associated with * \p device. Any streams or events created from this host thread will * be associated with \p device. Any kernels launched from this host * thread using the <<<>>> operator or ::cudaLaunchKernel() will be executed * on \p device. * * This call may be made from any host thread, to any device, and at * any time. This function will do no synchronization with the previous * or new device, * and should only take significant time when it initializes the runtime's context state. * This call will bind the primary context of the specified device to the calling thread and all the * subsequent memory allocations, stream and event creations, and kernel launches * will be associated with the primary context. * This function will also immediately initialize the runtime state on the primary context, * and the context will be current on \p device immediately. This function will return an * error if the device is in ::cudaComputeModeExclusiveProcess and is occupied by another * process or if the device is in ::cudaComputeModeProhibited. * * It is not required to call ::cudaInitDevice before using this function. * \param device - Device on which the active host thread should execute the * device code. * * \return * ::cudaSuccess, * ::cudaErrorInvalidDevice, * ::cudaErrorDeviceUnavailable, * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaGetDeviceCount, ::cudaGetDevice, ::cudaGetDeviceProperties, * ::cudaChooseDevice, * ::cudaInitDevice, * ::cuCtxSetCurrent */ extern __host__ cudaError_t CUDARTAPI cudaSetDevice(int device); /** * \brief Returns which device is currently being used * * Returns in \p *device the current device for the calling host thread. * * \param device - Returns the device on which the active host thread * executes the device code. * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorDeviceUnavailable, * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaGetDeviceCount, ::cudaSetDevice, ::cudaGetDeviceProperties, * ::cudaChooseDevice, * ::cuCtxGetCurrent */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaGetDevice(int *device); /** * \brief Set a list of devices that can be used for CUDA * * Sets a list of devices for CUDA execution in priority order using * \p device_arr. The parameter \p len specifies the number of elements in the * list. CUDA will try devices from the list sequentially until it finds one * that works. If this function is not called, or if it is called with a \p len * of 0, then CUDA will go back to its default behavior of trying devices * sequentially from a default list containing all of the available CUDA * devices in the system. If a specified device ID in the list does not exist, * this function will return ::cudaErrorInvalidDevice. If \p len is not 0 and * \p device_arr is NULL or if \p len exceeds the number of devices in * the system, then ::cudaErrorInvalidValue is returned. * * \param device_arr - List of devices to try * \param len - Number of devices in specified list * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidDevice * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaGetDeviceCount, ::cudaSetDevice, ::cudaGetDeviceProperties, * ::cudaSetDeviceFlags, * ::cudaChooseDevice */ extern __host__ cudaError_t CUDARTAPI cudaSetValidDevices(int *device_arr, int len); /** * \brief Sets flags to be used for device executions * * Records \p flags as the flags for the current device. If the current device * has been set and that device has already been initialized, the previous flags * are overwritten. If the current device has not been initialized, it is * initialized with the provided flags. If no device has been made current to * the calling thread, a default device is selected and initialized with the * provided flags. * * The three LSBs of the \p flags parameter can be used to control how the CPU * thread interacts with the OS scheduler when waiting for results from the * device. * * - ::cudaDeviceScheduleAuto: The default value if the \p flags parameter is * zero, uses a heuristic based on the number of active CUDA contexts in the * process \p C and the number of logical processors in the system \p P. If * \p C \> \p P, then CUDA will yield to other OS threads when waiting for the * device, otherwise CUDA will not yield while waiting for results and * actively spin on the processor. Additionally, on Tegra devices, * ::cudaDeviceScheduleAuto uses a heuristic based on the power profile of * the platform and may choose ::cudaDeviceScheduleBlockingSync for low-powered * devices. * - ::cudaDeviceScheduleSpin: Instruct CUDA to actively spin when waiting for * results from the device. This can decrease latency when waiting for the * device, but may lower the performance of CPU threads if they are performing * work in parallel with the CUDA thread. * - ::cudaDeviceScheduleYield: Instruct CUDA to yield its thread when waiting * for results from the device. This can increase latency when waiting for the * device, but can increase the performance of CPU threads performing work in * parallel with the device. * - ::cudaDeviceScheduleBlockingSync: Instruct CUDA to block the CPU thread * on a synchronization primitive when waiting for the device to finish work. * - ::cudaDeviceBlockingSync: Instruct CUDA to block the CPU thread on a * synchronization primitive when waiting for the device to finish work.
* \ref deprecated "Deprecated:" This flag was deprecated as of CUDA 4.0 and * replaced with ::cudaDeviceScheduleBlockingSync. * - ::cudaDeviceMapHost: This flag enables allocating pinned * host memory that is accessible to the device. It is implicit for the * runtime but may be absent if a context is created using the driver API. * If this flag is not set, ::cudaHostGetDevicePointer() will always return * a failure code. * - ::cudaDeviceLmemResizeToMax: Instruct CUDA to not reduce local memory * after resizing local memory for a kernel. This can prevent thrashing by * local memory allocations when launching many kernels with high local * memory usage at the cost of potentially increased memory usage.
* \ref deprecated "Deprecated:" This flag is deprecated and the behavior enabled * by this flag is now the default and cannot be disabled. * - ::cudaDeviceSyncMemops: Ensures that synchronous memory operations initiated * on this context will always synchronize. See further documentation in the * section titled "API Synchronization behavior" to learn more about cases when * synchronous memory operations can exhibit asynchronous behavior. * * \param flags - Parameters for device operation * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaGetDeviceFlags, ::cudaGetDeviceCount, ::cudaGetDevice, ::cudaGetDeviceProperties, * ::cudaSetDevice, ::cudaSetValidDevices, * ::cudaInitDevice, * ::cudaChooseDevice, * ::cuDevicePrimaryCtxSetFlags */ extern __host__ cudaError_t CUDARTAPI cudaSetDeviceFlags( unsigned int flags ); /** * \brief Gets the flags for the current device * * * Returns in \p flags the flags for the current device. If there is a current * device for the calling thread, the flags for the device are returned. If * there is no current device, the flags for the first device are returned, * which may be the default flags. Compare to the behavior of * ::cudaSetDeviceFlags. * * Typically, the flags returned should match the behavior that will be seen * if the calling thread uses a device after this call, without any change to * the flags or current device inbetween by this or another thread. Note that * if the device is not initialized, it is possible for another thread to * change the flags for the current device before it is initialized. * Additionally, when using exclusive mode, if this thread has not requested a * specific device, it may use a device other than the first device, contrary * to the assumption made by this function. * * If a context has been created via the driver API and is current to the * calling thread, the flags for that context are always returned. * * Flags returned by this function may specifically include ::cudaDeviceMapHost * even though it is not accepted by ::cudaSetDeviceFlags because it is * implicit in runtime API flags. The reason for this is that the current * context may have been created via the driver API in which case the flag is * not implicit and may be unset. * * \param flags - Pointer to store the device flags * * \return * ::cudaSuccess, * ::cudaErrorInvalidDevice * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaGetDevice, ::cudaGetDeviceProperties, * ::cudaSetDevice, ::cudaSetDeviceFlags, * ::cudaInitDevice, * ::cuCtxGetFlags, * ::cuDevicePrimaryCtxGetState */ extern __host__ cudaError_t CUDARTAPI cudaGetDeviceFlags( unsigned int *flags ); /** @} */ /* END CUDART_DEVICE */ /** * \defgroup CUDART_STREAM Stream Management * * ___MANBRIEF___ stream management functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the stream management functions of the CUDA runtime * application programming interface. * * @{ */ /** * \brief Create an asynchronous stream * * Creates a new asynchronous stream on the context that is current to the calling host thread. * If no context is current to the calling host thread, then the primary context for a device * is selected, made current to the calling thread, and initialized before creating a stream on it. * * \param pStream - Pointer to new stream identifier * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaStreamCreateWithPriority, * ::cudaStreamCreateWithFlags, * ::cudaStreamGetPriority, * ::cudaStreamGetFlags, * ::cudaStreamGetDevice, * ::cudaStreamQuery, * ::cudaStreamSynchronize, * ::cudaStreamWaitEvent, * ::cudaStreamAddCallback, * ::cudaSetDevice, * ::cudaStreamDestroy, * ::cuStreamCreate */ extern __host__ cudaError_t CUDARTAPI cudaStreamCreate(cudaStream_t *pStream); /** * \brief Create an asynchronous stream * * Creates a new asynchronous stream on the context that is current to the calling host thread. * If no context is current to the calling host thread, then the primary context for a device * is selected, made current to the calling thread, and initialized before creating a stream on it. * The \p flags argument determines the behaviors of the stream. Valid values for \p flags are * - ::cudaStreamDefault: Default stream creation flag. * - ::cudaStreamNonBlocking: Specifies that work running in the created * stream may run concurrently with work in stream 0 (the NULL stream), and that * the created stream should perform no implicit synchronization with stream 0. * * \param pStream - Pointer to new stream identifier * \param flags - Parameters for stream creation * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaStreamCreate, * ::cudaStreamCreateWithPriority, * ::cudaStreamGetFlags, * ::cudaStreamGetDevice, * ::cudaStreamQuery, * ::cudaStreamSynchronize, * ::cudaStreamWaitEvent, * ::cudaStreamAddCallback, * ::cudaSetDevice, * ::cudaStreamDestroy, * ::cuStreamCreate */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamCreateWithFlags(cudaStream_t *pStream, unsigned int flags); /** * \brief Create an asynchronous stream with the specified priority * * Creates a stream with the specified priority and returns a handle in \p pStream. * The stream is created on the context that is current to the calling host thread. * If no context is current to the calling host thread, then the primary context for a device * is selected, made current to the calling thread, and initialized before creating a stream on it. * This affects the scheduling priority of work in the stream. Priorities provide a * hint to preferentially run work with higher priority when possible, but do * not preempt already-running work or provide any other functional guarantee on * execution order. * * \p priority follows a convention where lower numbers represent higher priorities. * '0' represents default priority. The range of meaningful numerical priorities can * be queried using ::cudaDeviceGetStreamPriorityRange. If the specified priority is * outside the numerical range returned by ::cudaDeviceGetStreamPriorityRange, * it will automatically be clamped to the lowest or the highest number in the range. * * \param pStream - Pointer to new stream identifier * \param flags - Flags for stream creation. See ::cudaStreamCreateWithFlags for a list of valid flags that can be passed * \param priority - Priority of the stream. Lower numbers represent higher priorities. * See ::cudaDeviceGetStreamPriorityRange for more information about * the meaningful stream priorities that can be passed. * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \note Stream priorities are supported only on GPUs * with compute capability 3.5 or higher. * * \note In the current implementation, only compute kernels launched in * priority streams are affected by the stream's priority. Stream priorities have * no effect on host-to-device and device-to-host memory operations. * * \sa ::cudaStreamCreate, * ::cudaStreamCreateWithFlags, * ::cudaDeviceGetStreamPriorityRange, * ::cudaStreamGetPriority, * ::cudaStreamQuery, * ::cudaStreamWaitEvent, * ::cudaStreamAddCallback, * ::cudaStreamSynchronize, * ::cudaSetDevice, * ::cudaStreamDestroy, * ::cuStreamCreateWithPriority */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamCreateWithPriority(cudaStream_t *pStream, unsigned int flags, int priority); /** * \brief Query the priority of a stream * * Query the priority of a stream. The priority is returned in in \p priority. * Note that if the stream was created with a priority outside the meaningful * numerical range returned by ::cudaDeviceGetStreamPriorityRange, * this function returns the clamped priority. * See ::cudaStreamCreateWithPriority for details about priority clamping. * * \param hStream - Handle to the stream to be queried * \param priority - Pointer to a signed integer in which the stream's priority is returned * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaStreamCreateWithPriority, * ::cudaDeviceGetStreamPriorityRange, * ::cudaStreamGetFlags, * ::cudaStreamGetDevice, * ::cuStreamGetPriority */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamGetPriority(cudaStream_t hStream, int *priority); /** * \brief Query the flags of a stream * * Query the flags of a stream. The flags are returned in \p flags. * See ::cudaStreamCreateWithFlags for a list of valid flags. * * \param hStream - Handle to the stream to be queried * \param flags - Pointer to an unsigned integer in which the stream's flags are returned * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle * \note_null_stream * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaStreamCreateWithPriority, * ::cudaStreamCreateWithFlags, * ::cudaStreamGetPriority, * ::cudaStreamGetDevice, * ::cuStreamGetFlags */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamGetFlags(cudaStream_t hStream, unsigned int *flags); /** * \brief Query the Id of a stream * * Query the Id of a stream. The Id is returned in \p streamId. * The Id is unique for the life of the program. * * The stream handle \p hStream can refer to any of the following: * * * \param hStream - Handle to the stream to be queried * \param streamId - Pointer to an unsigned long long in which the stream Id is returned * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle * \note_null_stream * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaStreamCreateWithPriority, * ::cudaStreamCreateWithFlags, * ::cudaStreamGetPriority, * ::cudaStreamGetFlags, * ::cuStreamGetId */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamGetId(cudaStream_t hStream, unsigned long long *streamId); /** * \brief Query the device of a stream * * Returns in \p *device the device of the stream. * * \param hStream - Handle to the stream to be queried * \param device - Returns the device to which the stream belongs * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorDeviceUnavailable, * \note_null_stream * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaSetDevice, * ::cudaGetDevice, * ::cudaStreamCreate, * ::cudaStreamGetPriority, * ::cudaStreamGetFlags, * ::cuStreamGetId */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamGetDevice(cudaStream_t hStream, int *device); /** * \brief Resets all persisting lines in cache to normal status. * * Resets all persisting lines in cache to normal status. * Takes effect on function return. * * \return * ::cudaSuccess, * \notefnerr * * \sa * ::cudaAccessPolicyWindow */ extern __host__ cudaError_t CUDARTAPI cudaCtxResetPersistingL2Cache(void); /** * \brief Copies attributes from source stream to destination stream. * * Copies attributes from source stream \p src to destination stream \p dst. * Both streams must have the same context. * * \param[out] dst Destination stream * \param[in] src Source stream * For attributes see ::cudaStreamAttrID * * \return * ::cudaSuccess, * ::cudaErrorNotSupported * \notefnerr * * \sa * ::cudaAccessPolicyWindow */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamCopyAttributes(cudaStream_t dst, cudaStream_t src); /** * \brief Queries stream attribute. * * Queries attribute \p attr from \p hStream and stores it in corresponding * member of \p value_out. * * \param[in] hStream * \param[in] attr * \param[out] value_out * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle * \notefnerr * * \sa * ::cudaAccessPolicyWindow */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamGetAttribute( cudaStream_t hStream, cudaStreamAttrID attr, cudaStreamAttrValue *value_out); /** * \brief Sets stream attribute. * * Sets attribute \p attr on \p hStream from corresponding attribute of * \p value. The updated attribute will be applied to subsequent work * submitted to the stream. It will not affect previously submitted work. * * \param[out] hStream * \param[in] attr * \param[in] value * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle * \notefnerr * * \sa * ::cudaAccessPolicyWindow */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamSetAttribute( cudaStream_t hStream, cudaStreamAttrID attr, const cudaStreamAttrValue *value); /** * \brief Destroys and cleans up an asynchronous stream * * Destroys and cleans up the asynchronous stream specified by \p stream. * * In case the device is still doing work in the stream \p stream * when ::cudaStreamDestroy() is called, the function will return immediately * and the resources associated with \p stream will be released automatically * once the device has completed all work in \p stream. * * \param stream - Stream identifier * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle * \note_null_stream * \notefnerr * \note_init_rt * \note_callback * \note_destroy_ub * * \sa ::cudaStreamCreate, * ::cudaStreamCreateWithFlags, * ::cudaStreamQuery, * ::cudaStreamWaitEvent, * ::cudaStreamSynchronize, * ::cudaStreamAddCallback, * ::cuStreamDestroy */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamDestroy(cudaStream_t stream); /** * \brief Make a compute stream wait on an event * * Makes all future work submitted to \p stream wait for all work captured in * \p event. See ::cudaEventRecord() for details on what is captured by an event. * The synchronization will be performed efficiently on the device when applicable. * \p event may be from a different device than \p stream. * * flags include: * - ::cudaEventWaitDefault: Default event creation flag. * - ::cudaEventWaitExternal: Event is captured in the graph as an external * event node when performing stream capture. * * \param stream - Stream to wait * \param event - Event to wait on * \param flags - Parameters for the operation(See above) * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle * \note_null_stream * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaStreamCreate, ::cudaStreamCreateWithFlags, ::cudaStreamQuery, ::cudaStreamSynchronize, ::cudaStreamAddCallback, ::cudaStreamDestroy, * ::cuStreamWaitEvent */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamWaitEvent(cudaStream_t stream, cudaEvent_t event, unsigned int flags __dv(0)); /** * Type of stream callback functions. * \param stream The stream as passed to ::cudaStreamAddCallback, may be NULL. * \param status ::cudaSuccess or any persistent error on the stream. * \param userData User parameter provided at registration. */ typedef void (CUDART_CB *cudaStreamCallback_t)(cudaStream_t stream, cudaError_t status, void *userData); /** * \brief Add a callback to a compute stream * * \note This function is slated for eventual deprecation and removal. If * you do not require the callback to execute in case of a device error, * consider using ::cudaLaunchHostFunc. Additionally, this function is not * supported with ::cudaStreamBeginCapture and ::cudaStreamEndCapture, unlike * ::cudaLaunchHostFunc. * * Adds a callback to be called on the host after all currently enqueued * items in the stream have completed. For each * cudaStreamAddCallback call, a callback will be executed exactly once. * The callback will block later work in the stream until it is finished. * * The callback may be passed ::cudaSuccess or an error code. In the event * of a device error, all subsequently executed callbacks will receive an * appropriate ::cudaError_t. * * Callbacks must not make any CUDA API calls. Attempting to use CUDA APIs * may result in ::cudaErrorNotPermitted. Callbacks must not perform any * synchronization that may depend on outstanding device work or other callbacks * that are not mandated to run earlier. Callbacks without a mandated order * (in independent streams) execute in undefined order and may be serialized. * * For the purposes of Unified Memory, callback execution makes a number of * guarantees: * * * \param stream - Stream to add callback to * \param callback - The function to call once preceding stream operations are complete * \param userData - User specified data to be passed to the callback function * \param flags - Reserved for future use, must be 0 * * \return * ::cudaSuccess, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorInvalidValue, * ::cudaErrorNotSupported * \note_null_stream * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaStreamCreate, ::cudaStreamCreateWithFlags, ::cudaStreamQuery, ::cudaStreamSynchronize, ::cudaStreamWaitEvent, ::cudaStreamDestroy, ::cudaMallocManaged, ::cudaStreamAttachMemAsync, * ::cudaLaunchHostFunc, ::cuStreamAddCallback */ extern __host__ cudaError_t CUDARTAPI cudaStreamAddCallback(cudaStream_t stream, cudaStreamCallback_t callback, void *userData, unsigned int flags); /** * \brief Waits for stream tasks to complete * * Blocks until \p stream has completed all operations. If the * ::cudaDeviceScheduleBlockingSync flag was set for this device, * the host thread will block until the stream is finished with * all of its tasks. * * \param stream - Stream identifier * * \return * ::cudaSuccess, * ::cudaErrorInvalidResourceHandle * \note_null_stream * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaStreamCreate, ::cudaStreamCreateWithFlags, ::cudaStreamQuery, ::cudaStreamWaitEvent, ::cudaStreamAddCallback, ::cudaStreamDestroy, * ::cuStreamSynchronize */ extern __host__ cudaError_t CUDARTAPI cudaStreamSynchronize(cudaStream_t stream); /** * \brief Queries an asynchronous stream for completion status * * Returns ::cudaSuccess if all operations in \p stream have * completed, or ::cudaErrorNotReady if not. * * For the purposes of Unified Memory, a return value of ::cudaSuccess * is equivalent to having called ::cudaStreamSynchronize(). * * \param stream - Stream identifier * * \return * ::cudaSuccess, * ::cudaErrorNotReady, * ::cudaErrorInvalidResourceHandle * \note_null_stream * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaStreamCreate, ::cudaStreamCreateWithFlags, ::cudaStreamWaitEvent, ::cudaStreamSynchronize, ::cudaStreamAddCallback, ::cudaStreamDestroy, * ::cuStreamQuery */ extern __host__ cudaError_t CUDARTAPI cudaStreamQuery(cudaStream_t stream); /** * \brief Attach memory to a stream asynchronously * * Enqueues an operation in \p stream to specify stream association of * \p length bytes of memory starting from \p devPtr. This function is a * stream-ordered operation, meaning that it is dependent on, and will * only take effect when, previous work in stream has completed. Any * previous association is automatically replaced. * * \p devPtr must point to an one of the following types of memories: * - managed memory declared using the __managed__ keyword or allocated with * ::cudaMallocManaged. * - a valid host-accessible region of system-allocated pageable memory. This * type of memory may only be specified if the device associated with the * stream reports a non-zero value for the device attribute * ::cudaDevAttrPageableMemoryAccess. * * For managed allocations, \p length must be either zero or the entire * allocation's size. Both indicate that the entire allocation's stream * association is being changed. Currently, it is not possible to change stream * association for a portion of a managed allocation. * * For pageable allocations, \p length must be non-zero. * * The stream association is specified using \p flags which must be * one of ::cudaMemAttachGlobal, ::cudaMemAttachHost or ::cudaMemAttachSingle. * The default value for \p flags is ::cudaMemAttachSingle * If the ::cudaMemAttachGlobal flag is specified, the memory can be accessed * by any stream on any device. * If the ::cudaMemAttachHost flag is specified, the program makes a guarantee * that it won't access the memory on the device from any stream on a device that * has a zero value for the device attribute ::cudaDevAttrConcurrentManagedAccess. * If the ::cudaMemAttachSingle flag is specified and \p stream is associated with * a device that has a zero value for the device attribute ::cudaDevAttrConcurrentManagedAccess, * the program makes a guarantee that it will only access the memory on the device * from \p stream. It is illegal to attach singly to the NULL stream, because the * NULL stream is a virtual global stream and not a specific stream. An error will * be returned in this case. * * When memory is associated with a single stream, the Unified Memory system will * allow CPU access to this memory region so long as all operations in \p stream * have completed, regardless of whether other streams are active. In effect, * this constrains exclusive ownership of the managed memory region by * an active GPU to per-stream activity instead of whole-GPU activity. * * Accessing memory on the device from streams that are not associated with * it will produce undefined results. No error checking is performed by the * Unified Memory system to ensure that kernels launched into other streams * do not access this region. * * It is a program's responsibility to order calls to ::cudaStreamAttachMemAsync * via events, synchronization or other means to ensure legal access to memory * at all times. Data visibility and coherency will be changed appropriately * for all kernels which follow a stream-association change. * * If \p stream is destroyed while data is associated with it, the association is * removed and the association reverts to the default visibility of the allocation * as specified at ::cudaMallocManaged. For __managed__ variables, the default * association is always ::cudaMemAttachGlobal. Note that destroying a stream is an * asynchronous operation, and as a result, the change to default association won't * happen until all work in the stream has completed. * * \param stream - Stream in which to enqueue the attach operation * \param devPtr - Pointer to memory (must be a pointer to managed memory or * to a valid host-accessible region of system-allocated * memory) * \param length - Length of memory (defaults to zero) * \param flags - Must be one of ::cudaMemAttachGlobal, ::cudaMemAttachHost or ::cudaMemAttachSingle (defaults to ::cudaMemAttachSingle) * * \return * ::cudaSuccess, * ::cudaErrorNotReady, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaStreamCreate, ::cudaStreamCreateWithFlags, ::cudaStreamWaitEvent, ::cudaStreamSynchronize, ::cudaStreamAddCallback, ::cudaStreamDestroy, ::cudaMallocManaged, * ::cuStreamAttachMemAsync */ #if defined(__cplusplus) extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamAttachMemAsync(cudaStream_t stream, void *devPtr, size_t length __dv(0), unsigned int flags = cudaMemAttachSingle); #else extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamAttachMemAsync(cudaStream_t stream, void *devPtr, size_t length __dv(0), unsigned int flags); #endif /** * \brief Begins graph capture on a stream * * Begin graph capture on \p stream. When a stream is in capture mode, all operations * pushed into the stream will not be executed, but will instead be captured into * a graph, which will be returned via ::cudaStreamEndCapture. Capture may not be initiated * if \p stream is ::cudaStreamLegacy. Capture must be ended on the same stream in which * it was initiated, and it may only be initiated if the stream is not already in capture * mode. The capture mode may be queried via ::cudaStreamIsCapturing. A unique id * representing the capture sequence may be queried via ::cudaStreamGetCaptureInfo. * * If \p mode is not ::cudaStreamCaptureModeRelaxed, ::cudaStreamEndCapture must be * called on this stream from the same thread. * * \note Kernels captured using this API must not use texture and surface references. * Reading or writing through any texture or surface reference is undefined * behavior. This restriction does not apply to texture and surface objects. * * \param stream - Stream in which to initiate capture * \param mode - Controls the interaction of this capture sequence with other API * calls that are potentially unsafe. For more details see * ::cudaThreadExchangeStreamCaptureMode. * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * * \sa * ::cudaStreamCreate, * ::cudaStreamIsCapturing, * ::cudaStreamEndCapture, * ::cudaThreadExchangeStreamCaptureMode */ extern __host__ cudaError_t CUDARTAPI cudaStreamBeginCapture(cudaStream_t stream, enum cudaStreamCaptureMode mode); /** * \brief Begins graph capture on a stream to an existing graph * * Begin graph capture on \p stream. When a stream is in capture mode, all operations * pushed into the stream will not be executed, but will instead be captured into * \p graph, which will be returned via ::cudaStreamEndCapture. * * Capture may not be initiated if \p stream is ::cudaStreamLegacy. Capture must be ended on the * same stream in which it was initiated, and it may only be initiated if the stream is not * already in capture mode. The capture mode may be queried via ::cudaStreamIsCapturing. A unique id * representing the capture sequence may be queried via ::cudaStreamGetCaptureInfo. * * If \p mode is not ::cudaStreamCaptureModeRelaxed, ::cudaStreamEndCapture must be * called on this stream from the same thread. * * \note Kernels captured using this API must not use texture and surface references. * Reading or writing through any texture or surface reference is undefined * behavior. This restriction does not apply to texture and surface objects. * * \param stream - Stream in which to initiate capture. * \param graph - Graph to capture into. * \param dependencies - Dependencies of the first node captured in the stream. Can be NULL if numDependencies is 0. * \param dependencyData - Optional array of data associated with each dependency. * \param numDependencies - Number of dependencies. * \param mode - Controls the interaction of this capture sequence with other API * calls that are potentially unsafe. For more details see * ::cudaThreadExchangeStreamCaptureMode. * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * * \sa * ::cudaStreamCreate, * ::cudaStreamIsCapturing, * ::cudaStreamEndCapture, * ::cudaThreadExchangeStreamCaptureMode */ extern __host__ cudaError_t CUDARTAPI cudaStreamBeginCaptureToGraph(cudaStream_t stream, cudaGraph_t graph, const cudaGraphNode_t *dependencies, const cudaGraphEdgeData *dependencyData, size_t numDependencies, enum cudaStreamCaptureMode mode); /** * \brief Swaps the stream capture interaction mode for a thread * * Sets the calling thread's stream capture interaction mode to the value contained * in \p *mode, and overwrites \p *mode with the previous mode for the thread. To * facilitate deterministic behavior across function or module boundaries, callers * are encouraged to use this API in a push-pop fashion: \code cudaStreamCaptureMode mode = desiredMode; cudaThreadExchangeStreamCaptureMode(&mode); ... cudaThreadExchangeStreamCaptureMode(&mode); // restore previous mode * \endcode * * During stream capture (see ::cudaStreamBeginCapture), some actions, such as a call * to ::cudaMalloc, may be unsafe. In the case of ::cudaMalloc, the operation is * not enqueued asynchronously to a stream, and is not observed by stream capture. * Therefore, if the sequence of operations captured via ::cudaStreamBeginCapture * depended on the allocation being replayed whenever the graph is launched, the * captured graph would be invalid. * * Therefore, stream capture places restrictions on API calls that can be made within * or concurrently to a ::cudaStreamBeginCapture-::cudaStreamEndCapture sequence. This * behavior can be controlled via this API and flags to ::cudaStreamBeginCapture. * * A thread's mode is one of the following: * - \p cudaStreamCaptureModeGlobal: This is the default mode. If the local thread has * an ongoing capture sequence that was not initiated with * \p cudaStreamCaptureModeRelaxed at \p cuStreamBeginCapture, or if any other thread * has a concurrent capture sequence initiated with \p cudaStreamCaptureModeGlobal, * this thread is prohibited from potentially unsafe API calls. * - \p cudaStreamCaptureModeThreadLocal: If the local thread has an ongoing capture * sequence not initiated with \p cudaStreamCaptureModeRelaxed, it is prohibited * from potentially unsafe API calls. Concurrent capture sequences in other threads * are ignored. * - \p cudaStreamCaptureModeRelaxed: The local thread is not prohibited from potentially * unsafe API calls. Note that the thread is still prohibited from API calls which * necessarily conflict with stream capture, for example, attempting ::cudaEventQuery * on an event that was last recorded inside a capture sequence. * * \param mode - Pointer to mode value to swap with the current mode * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * * \sa * ::cudaStreamBeginCapture */ extern __host__ cudaError_t CUDARTAPI cudaThreadExchangeStreamCaptureMode(enum cudaStreamCaptureMode *mode); /** * \brief Ends capture on a stream, returning the captured graph * * End capture on \p stream, returning the captured graph via \p pGraph. * Capture must have been initiated on \p stream via a call to ::cudaStreamBeginCapture. * If capture was invalidated, due to a violation of the rules of stream capture, then * a NULL graph will be returned. * * If the \p mode argument to ::cudaStreamBeginCapture was not * ::cudaStreamCaptureModeRelaxed, this call must be from the same thread as * ::cudaStreamBeginCapture. * * \param stream - Stream to query * \param pGraph - The captured graph * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorStreamCaptureWrongThread * \notefnerr * * \sa * ::cudaStreamCreate, * ::cudaStreamBeginCapture, * ::cudaStreamIsCapturing, * ::cudaGraphDestroy */ extern __host__ cudaError_t CUDARTAPI cudaStreamEndCapture(cudaStream_t stream, cudaGraph_t *pGraph); /** * \brief Returns a stream's capture status * * Return the capture status of \p stream via \p pCaptureStatus. After a successful * call, \p *pCaptureStatus will contain one of the following: * - ::cudaStreamCaptureStatusNone: The stream is not capturing. * - ::cudaStreamCaptureStatusActive: The stream is capturing. * - ::cudaStreamCaptureStatusInvalidated: The stream was capturing but an error * has invalidated the capture sequence. The capture sequence must be terminated * with ::cudaStreamEndCapture on the stream where it was initiated in order to * continue using \p stream. * * Note that, if this is called on ::cudaStreamLegacy (the "null stream") while * a blocking stream on the same device is capturing, it will return * ::cudaErrorStreamCaptureImplicit and \p *pCaptureStatus is unspecified * after the call. The blocking stream capture is not invalidated. * * When a blocking stream is capturing, the legacy stream is in an * unusable state until the blocking stream capture is terminated. The legacy * stream is not supported for stream capture, but attempted use would have an * implicit dependency on the capturing stream(s). * * \param stream - Stream to query * \param pCaptureStatus - Returns the stream's capture status * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorStreamCaptureImplicit * \notefnerr * * \sa * ::cudaStreamCreate, * ::cudaStreamBeginCapture, * ::cudaStreamEndCapture */ extern __host__ cudaError_t CUDARTAPI cudaStreamIsCapturing(cudaStream_t stream, enum cudaStreamCaptureStatus *pCaptureStatus); /** * \brief Query a stream's capture state * * Query stream state related to stream capture. * * If called on ::cudaStreamLegacy (the "null stream") while a stream not created * with ::cudaStreamNonBlocking is capturing, returns ::cudaErrorStreamCaptureImplicit. * * Valid data (other than capture status) is returned only if both of the following are true: * - the call returns cudaSuccess * - the returned capture status is ::cudaStreamCaptureStatusActive * * \param stream - The stream to query * \param captureStatus_out - Location to return the capture status of the stream; required * \param id_out - Optional location to return an id for the capture sequence, which is * unique over the lifetime of the process * \param graph_out - Optional location to return the graph being captured into. All * operations other than destroy and node removal are permitted on the graph * while the capture sequence is in progress. This API does not transfer * ownership of the graph, which is transferred or destroyed at * ::cudaStreamEndCapture. Note that the graph handle may be invalidated before * end of capture for certain errors. Nodes that are or become * unreachable from the original stream at ::cudaStreamEndCapture due to direct * actions on the graph do not trigger ::cudaErrorStreamCaptureUnjoined. * \param dependencies_out - Optional location to store a pointer to an array of nodes. * The next node to be captured in the stream will depend on this set of nodes, * absent operations such as event wait which modify this set. The array pointer * is valid until the next API call which operates on the stream or until the * capture is terminated. The node handles may be copied out and are valid until * they or the graph is destroyed. The driver-owned array may also be passed * directly to APIs that operate on the graph (not the stream) without copying. * \param numDependencies_out - Optional location to store the size of the array * returned in dependencies_out. * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorStreamCaptureImplicit * \note_graph_thread_safety * \notefnerr * * \sa * ::cudaStreamGetCaptureInfo_v3, * ::cudaStreamBeginCapture, * ::cudaStreamIsCapturing, * ::cudaStreamUpdateCaptureDependencies */ extern __host__ cudaError_t CUDARTAPI cudaStreamGetCaptureInfo(cudaStream_t stream, enum cudaStreamCaptureStatus *captureStatus_out, unsigned long long *id_out __dv(0), cudaGraph_t *graph_out __dv(0), const cudaGraphNode_t **dependencies_out __dv(0), size_t *numDependencies_out __dv(0)); /** * \brief Query a stream's capture state (12.3+) * * Query stream state related to stream capture. * * If called on ::cudaStreamLegacy (the "null stream") while a stream not created * with ::cudaStreamNonBlocking is capturing, returns ::cudaErrorStreamCaptureImplicit. * * Valid data (other than capture status) is returned only if both of the following are true: * - the call returns cudaSuccess * - the returned capture status is ::cudaStreamCaptureStatusActive * * If \p edgeData_out is non-NULL then \p dependencies_out must be as well. If * \p dependencies_out is non-NULL and \p edgeData_out is NULL, but there is non-zero edge * data for one or more of the current stream dependencies, the call will return * ::cudaErrorLossyQuery. * * \param stream - The stream to query * \param captureStatus_out - Location to return the capture status of the stream; required * \param id_out - Optional location to return an id for the capture sequence, which is * unique over the lifetime of the process * \param graph_out - Optional location to return the graph being captured into. All * operations other than destroy and node removal are permitted on the graph * while the capture sequence is in progress. This API does not transfer * ownership of the graph, which is transferred or destroyed at * ::cudaStreamEndCapture. Note that the graph handle may be invalidated before * end of capture for certain errors. Nodes that are or become * unreachable from the original stream at ::cudaStreamEndCapture due to direct * actions on the graph do not trigger ::cudaErrorStreamCaptureUnjoined. * \param dependencies_out - Optional location to store a pointer to an array of nodes. * The next node to be captured in the stream will depend on this set of nodes, * absent operations such as event wait which modify this set. The array pointer * is valid until the next API call which operates on the stream or until the * capture is terminated. The node handles may be copied out and are valid until * they or the graph is destroyed. The driver-owned array may also be passed * directly to APIs that operate on the graph (not the stream) without copying. * \param edgeData_out - Optional location to store a pointer to an array of graph edge * data. This array parallels \c dependencies_out; the next node to be added * has an edge to \c dependencies_out[i] with annotation \c edgeData_out[i] for * each \c i. The array pointer is valid until the next API call which operates * on the stream or until the capture is terminated. * \param numDependencies_out - Optional location to store the size of the array * returned in dependencies_out. * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorStreamCaptureImplicit, * ::cudaErrorLossyQuery * \note_graph_thread_safety * \notefnerr * * \sa * ::cudaStreamBeginCapture, * ::cudaStreamIsCapturing, * ::cudaStreamUpdateCaptureDependencies */ extern __host__ cudaError_t CUDARTAPI cudaStreamGetCaptureInfo_v3(cudaStream_t stream, enum cudaStreamCaptureStatus *captureStatus_out, unsigned long long *id_out __dv(0), cudaGraph_t *graph_out __dv(0), const cudaGraphNode_t **dependencies_out __dv(0), const cudaGraphEdgeData **edgeData_out __dv(0), size_t *numDependencies_out __dv(0)); /** * \brief Update the set of dependencies in a capturing stream (11.3+) * * Modifies the dependency set of a capturing stream. The dependency set is the set * of nodes that the next captured node in the stream will depend on. * * Valid flags are ::cudaStreamAddCaptureDependencies and * ::cudaStreamSetCaptureDependencies. These control whether the set passed to * the API is added to the existing set or replaces it. A flags value of 0 defaults * to ::cudaStreamAddCaptureDependencies. * * Nodes that are removed from the dependency set via this API do not result in * ::cudaErrorStreamCaptureUnjoined if they are unreachable from the stream at * ::cudaStreamEndCapture. * * Returns ::cudaErrorIllegalState if the stream is not capturing. * * This API is new in CUDA 11.3. Developers requiring compatibility across minor * versions of the CUDA driver to 11.0 should not use this API or provide a fallback. * * \param stream - The stream to update * \param dependencies - The set of dependencies to add * \param numDependencies - The size of the dependencies array * \param flags - See above * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorIllegalState * \notefnerr * * \sa * ::cudaStreamBeginCapture, * ::cudaStreamGetCaptureInfo, */ extern __host__ cudaError_t CUDARTAPI cudaStreamUpdateCaptureDependencies(cudaStream_t stream, cudaGraphNode_t *dependencies, size_t numDependencies, unsigned int flags __dv(0)); /** * \brief Update the set of dependencies in a capturing stream (12.3+) * * Modifies the dependency set of a capturing stream. The dependency set is the set * of nodes that the next captured node in the stream will depend on. * * Valid flags are ::cudaStreamAddCaptureDependencies and * ::cudaStreamSetCaptureDependencies. These control whether the set passed to * the API is added to the existing set or replaces it. A flags value of 0 defaults * to ::cudaStreamAddCaptureDependencies. * * Nodes that are removed from the dependency set via this API do not result in * ::cudaErrorStreamCaptureUnjoined if they are unreachable from the stream at * ::cudaStreamEndCapture. * * Returns ::cudaErrorIllegalState if the stream is not capturing. * * \param stream - The stream to update * \param dependencies - The set of dependencies to add * \param dependencyData - Optional array of data associated with each dependency. * \param numDependencies - The size of the dependencies array * \param flags - See above * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorIllegalState * \notefnerr * * \sa * ::cudaStreamBeginCapture, * ::cudaStreamGetCaptureInfo, */ extern __host__ cudaError_t CUDARTAPI cudaStreamUpdateCaptureDependencies_v2(cudaStream_t stream, cudaGraphNode_t *dependencies, const cudaGraphEdgeData *dependencyData, size_t numDependencies, unsigned int flags __dv(0)); /** @} */ /* END CUDART_STREAM */ /** * \defgroup CUDART_EVENT Event Management * * ___MANBRIEF___ event management functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the event management functions of the CUDA runtime * application programming interface. * * @{ */ /** * \brief Creates an event object * * Creates an event object for the current device using ::cudaEventDefault. * * \param event - Newly created event * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorLaunchFailure, * ::cudaErrorMemoryAllocation * \notefnerr * \note_init_rt * \note_callback * * \sa \ref ::cudaEventCreate(cudaEvent_t*, unsigned int) "cudaEventCreate (C++ API)", * ::cudaEventCreateWithFlags, ::cudaEventRecord, ::cudaEventQuery, * ::cudaEventSynchronize, ::cudaEventDestroy, ::cudaEventElapsedTime, * ::cudaStreamWaitEvent, * ::cuEventCreate */ extern __host__ cudaError_t CUDARTAPI cudaEventCreate(cudaEvent_t *event); /** * \brief Creates an event object with the specified flags * * Creates an event object for the current device with the specified flags. Valid * flags include: * - ::cudaEventDefault: Default event creation flag. * - ::cudaEventBlockingSync: Specifies that event should use blocking * synchronization. A host thread that uses ::cudaEventSynchronize() to wait * on an event created with this flag will block until the event actually * completes. * - ::cudaEventDisableTiming: Specifies that the created event does not need * to record timing data. Events created with this flag specified and * the ::cudaEventBlockingSync flag not specified will provide the best * performance when used with ::cudaStreamWaitEvent() and ::cudaEventQuery(). * - ::cudaEventInterprocess: Specifies that the created event may be used as an * interprocess event by ::cudaIpcGetEventHandle(). ::cudaEventInterprocess must * be specified along with ::cudaEventDisableTiming. * * \param event - Newly created event * \param flags - Flags for new event * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorLaunchFailure, * ::cudaErrorMemoryAllocation * \notefnerr * \note_init_rt * \note_callback * * \sa \ref ::cudaEventCreate(cudaEvent_t*) "cudaEventCreate (C API)", * ::cudaEventSynchronize, ::cudaEventDestroy, ::cudaEventElapsedTime, * ::cudaStreamWaitEvent, * ::cuEventCreate */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaEventCreateWithFlags(cudaEvent_t *event, unsigned int flags); /** * \brief Records an event * * Captures in \p event the contents of \p stream at the time of this call. * \p event and \p stream must be on the same CUDA context. * Calls such as ::cudaEventQuery() or ::cudaStreamWaitEvent() will then * examine or wait for completion of the work that was captured. Uses of * \p stream after this call do not modify \p event. See note on default * stream behavior for what is captured in the default case. * * ::cudaEventRecord() can be called multiple times on the same event and * will overwrite the previously captured state. Other APIs such as * ::cudaStreamWaitEvent() use the most recently captured state at the time * of the API call, and are not affected by later calls to * ::cudaEventRecord(). Before the first call to ::cudaEventRecord(), an * event represents an empty set of work, so for example ::cudaEventQuery() * would return ::cudaSuccess. * * \param event - Event to record * \param stream - Stream in which to record event * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorLaunchFailure * \note_null_stream * \notefnerr * \note_init_rt * \note_callback * \note_null_event * * \sa \ref ::cudaEventCreate(cudaEvent_t*) "cudaEventCreate (C API)", * ::cudaEventCreateWithFlags, ::cudaEventQuery, * ::cudaEventSynchronize, ::cudaEventDestroy, ::cudaEventElapsedTime, * ::cudaStreamWaitEvent, * ::cudaEventRecordWithFlags, * ::cuEventRecord */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaEventRecord(cudaEvent_t event, cudaStream_t stream __dv(0)); /** * \brief Records an event * * Captures in \p event the contents of \p stream at the time of this call. * \p event and \p stream must be on the same CUDA context. * Calls such as ::cudaEventQuery() or ::cudaStreamWaitEvent() will then * examine or wait for completion of the work that was captured. Uses of * \p stream after this call do not modify \p event. See note on default * stream behavior for what is captured in the default case. * * ::cudaEventRecordWithFlags() can be called multiple times on the same event and * will overwrite the previously captured state. Other APIs such as * ::cudaStreamWaitEvent() use the most recently captured state at the time * of the API call, and are not affected by later calls to * ::cudaEventRecordWithFlags(). Before the first call to ::cudaEventRecordWithFlags(), an * event represents an empty set of work, so for example ::cudaEventQuery() * would return ::cudaSuccess. * * flags include: * - ::cudaEventRecordDefault: Default event creation flag. * - ::cudaEventRecordExternal: Event is captured in the graph as an external * event node when performing stream capture. * * \param event - Event to record * \param stream - Stream in which to record event * \param flags - Parameters for the operation(See above) * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorLaunchFailure * \note_null_stream * \notefnerr * \note_init_rt * \note_callback * \note_null_event * * \sa \ref ::cudaEventCreate(cudaEvent_t*) "cudaEventCreate (C API)", * ::cudaEventCreateWithFlags, ::cudaEventQuery, * ::cudaEventSynchronize, ::cudaEventDestroy, ::cudaEventElapsedTime, * ::cudaStreamWaitEvent, * ::cudaEventRecord, * ::cuEventRecord, */ #if __CUDART_API_VERSION >= 11010 extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaEventRecordWithFlags(cudaEvent_t event, cudaStream_t stream __dv(0), unsigned int flags __dv(0)); #endif /** * \brief Queries an event's status * * Queries the status of all work currently captured by \p event. See * ::cudaEventRecord() for details on what is captured by an event. * * Returns ::cudaSuccess if all captured work has been completed, or * ::cudaErrorNotReady if any captured work is incomplete. * * For the purposes of Unified Memory, a return value of ::cudaSuccess * is equivalent to having called ::cudaEventSynchronize(). * * \param event - Event to query * * \return * ::cudaSuccess, * ::cudaErrorNotReady, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorLaunchFailure * \notefnerr * \note_init_rt * \note_callback * \note_null_event * * \sa \ref ::cudaEventCreate(cudaEvent_t*) "cudaEventCreate (C API)", * ::cudaEventCreateWithFlags, ::cudaEventRecord, * ::cudaEventSynchronize, ::cudaEventDestroy, ::cudaEventElapsedTime, * ::cuEventQuery */ extern __host__ cudaError_t CUDARTAPI cudaEventQuery(cudaEvent_t event); /** * \brief Waits for an event to complete * * Waits until the completion of all work currently captured in \p event. * See ::cudaEventRecord() for details on what is captured by an event. * * Waiting for an event that was created with the ::cudaEventBlockingSync * flag will cause the calling CPU thread to block until the event has * been completed by the device. If the ::cudaEventBlockingSync flag has * not been set, then the CPU thread will busy-wait until the event has * been completed by the device. * * \param event - Event to wait for * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorLaunchFailure * \notefnerr * \note_init_rt * \note_callback * \note_null_event * * \sa \ref ::cudaEventCreate(cudaEvent_t*) "cudaEventCreate (C API)", * ::cudaEventCreateWithFlags, ::cudaEventRecord, * ::cudaEventQuery, ::cudaEventDestroy, ::cudaEventElapsedTime, * ::cuEventSynchronize */ extern __host__ cudaError_t CUDARTAPI cudaEventSynchronize(cudaEvent_t event); /** * \brief Destroys an event object * * Destroys the event specified by \p event. * * An event may be destroyed before it is complete (i.e., while * ::cudaEventQuery() would return ::cudaErrorNotReady). In this case, the * call does not block on completion of the event, and any associated * resources will automatically be released asynchronously at completion. * * \param event - Event to destroy * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorLaunchFailure * \notefnerr * \note_init_rt * \note_callback * \note_destroy_ub * \note_null_event * * \sa \ref ::cudaEventCreate(cudaEvent_t*) "cudaEventCreate (C API)", * ::cudaEventCreateWithFlags, ::cudaEventQuery, * ::cudaEventSynchronize, ::cudaEventRecord, ::cudaEventElapsedTime, * ::cuEventDestroy */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaEventDestroy(cudaEvent_t event); /** * \brief Computes the elapsed time between events * * Computes the elapsed time between two events (in milliseconds with a * resolution of around 0.5 microseconds). * * If either event was last recorded in a non-NULL stream, the resulting time * may be greater than expected (even if both used the same stream handle). This * happens because the ::cudaEventRecord() operation takes place asynchronously * and there is no guarantee that the measured latency is actually just between * the two events. Any number of other different stream operations could execute * in between the two measured events, thus altering the timing in a significant * way. * * If ::cudaEventRecord() has not been called on either event, then * ::cudaErrorInvalidResourceHandle is returned. If ::cudaEventRecord() has been * called on both events but one or both of them has not yet been completed * (that is, ::cudaEventQuery() would return ::cudaErrorNotReady on at least one * of the events), ::cudaErrorNotReady is returned. If either event was created * with the ::cudaEventDisableTiming flag, then this function will return * ::cudaErrorInvalidResourceHandle. * * \param ms - Time between \p start and \p end in ms * \param start - Starting event * \param end - Ending event * * \return * ::cudaSuccess, * ::cudaErrorNotReady, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorLaunchFailure, * ::cudaErrorUnknown * \notefnerr * \note_init_rt * \note_callback * \note_null_event * * \sa \ref ::cudaEventCreate(cudaEvent_t*) "cudaEventCreate (C API)", * ::cudaEventCreateWithFlags, ::cudaEventQuery, * ::cudaEventSynchronize, ::cudaEventDestroy, ::cudaEventRecord, * ::cuEventElapsedTime */ extern __host__ cudaError_t CUDARTAPI cudaEventElapsedTime(float *ms, cudaEvent_t start, cudaEvent_t end); /** * \brief Computes the elapsed time between events * * Computes the elapsed time between two events (in milliseconds with a * resolution of around 0.5 microseconds). Note this API is not guaranteed * to return the latest errors for pending work. As such this API is intended to * serve as a elapsed time calculation only and polling for completion on the * events to be compared should be done with ::cudaEventQuery instead. * * If either event was last recorded in a non-NULL stream, the resulting time * may be greater than expected (even if both used the same stream handle). This * happens because the ::cudaEventRecord() operation takes place asynchronously * and there is no guarantee that the measured latency is actually just between * the two events. Any number of other different stream operations could execute * in between the two measured events, thus altering the timing in a significant * way. * * If ::cudaEventRecord() has not been called on either event, then * ::cudaErrorInvalidResourceHandle is returned. If ::cudaEventRecord() has been * called on both events but one or both of them has not yet been completed * (that is, ::cudaEventQuery() would return ::cudaErrorNotReady on at least one * of the events), ::cudaErrorNotReady is returned. If either event was created * with the ::cudaEventDisableTiming flag, then this function will return * ::cudaErrorInvalidResourceHandle. * * \param ms - Time between \p start and \p end in ms * \param start - Starting event * \param end - Ending event * * \return * ::cudaSuccess, * ::cudaErrorNotReady, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorLaunchFailure, * ::cudaErrorUnknown * \notefnerr * \note_init_rt * \note_callback * \note_null_event * * \sa \ref ::cudaEventCreate(cudaEvent_t*) "cudaEventCreate (C API)", * ::cudaEventCreateWithFlags, ::cudaEventQuery, * ::cudaEventSynchronize, ::cudaEventDestroy, ::cudaEventRecord, * ::cuEventElapsedTime */ extern __host__ cudaError_t CUDARTAPI cudaEventElapsedTime_v2(float *ms, cudaEvent_t start, cudaEvent_t end); /** @} */ /* END CUDART_EVENT */ /** * \defgroup CUDART_EXTRES_INTEROP External Resource Interoperability * * ___MANBRIEF___ External resource interoperability functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the external resource interoperability functions of the CUDA * runtime application programming interface. * * @{ */ /** * \brief Imports an external memory object * * Imports an externally allocated memory object and returns * a handle to that in \p extMem_out. * * The properties of the handle being imported must be described in * \p memHandleDesc. The ::cudaExternalMemoryHandleDesc structure * is defined as follows: * * \code typedef struct cudaExternalMemoryHandleDesc_st { cudaExternalMemoryHandleType type; union { int fd; struct { void *handle; const void *name; } win32; const void *nvSciBufObject; } handle; unsigned long long size; unsigned int flags; } cudaExternalMemoryHandleDesc; * \endcode * * where ::cudaExternalMemoryHandleDesc::type specifies the type * of handle being imported. ::cudaExternalMemoryHandleType is * defined as: * * \code typedef enum cudaExternalMemoryHandleType_enum { cudaExternalMemoryHandleTypeOpaqueFd = 1, cudaExternalMemoryHandleTypeOpaqueWin32 = 2, cudaExternalMemoryHandleTypeOpaqueWin32Kmt = 3, cudaExternalMemoryHandleTypeD3D12Heap = 4, cudaExternalMemoryHandleTypeD3D12Resource = 5, cudaExternalMemoryHandleTypeD3D11Resource = 6, cudaExternalMemoryHandleTypeD3D11ResourceKmt = 7, cudaExternalMemoryHandleTypeNvSciBuf = 8 } cudaExternalMemoryHandleType; * \endcode * * If ::cudaExternalMemoryHandleDesc::type is * ::cudaExternalMemoryHandleTypeOpaqueFd, then * ::cudaExternalMemoryHandleDesc::handle::fd must be a valid * file descriptor referencing a memory object. Ownership of * the file descriptor is transferred to the CUDA driver when the * handle is imported successfully. Performing any operations on the * file descriptor after it is imported results in undefined behavior. * * If ::cudaExternalMemoryHandleDesc::type is * ::cudaExternalMemoryHandleTypeOpaqueWin32, then exactly one * of ::cudaExternalMemoryHandleDesc::handle::win32::handle and * ::cudaExternalMemoryHandleDesc::handle::win32::name must not be * NULL. If ::cudaExternalMemoryHandleDesc::handle::win32::handle * is not NULL, then it must represent a valid shared NT handle that * references a memory object. Ownership of this handle is * not transferred to CUDA after the import operation, so the * application must release the handle using the appropriate system * call. If ::cudaExternalMemoryHandleDesc::handle::win32::name * is not NULL, then it must point to a NULL-terminated array of * UTF-16 characters that refers to a memory object. * * If ::cudaExternalMemoryHandleDesc::type is * ::cudaExternalMemoryHandleTypeOpaqueWin32Kmt, then * ::cudaExternalMemoryHandleDesc::handle::win32::handle must * be non-NULL and * ::cudaExternalMemoryHandleDesc::handle::win32::name * must be NULL. The handle specified must be a globally shared KMT * handle. This handle does not hold a reference to the underlying * object, and thus will be invalid when all references to the * memory object are destroyed. * * If ::cudaExternalMemoryHandleDesc::type is * ::cudaExternalMemoryHandleTypeD3D12Heap, then exactly one * of ::cudaExternalMemoryHandleDesc::handle::win32::handle and * ::cudaExternalMemoryHandleDesc::handle::win32::name must not be * NULL. If ::cudaExternalMemoryHandleDesc::handle::win32::handle * is not NULL, then it must represent a valid shared NT handle that * is returned by ID3D12Device::CreateSharedHandle when referring to a * ID3D12Heap object. This handle holds a reference to the underlying * object. If ::cudaExternalMemoryHandleDesc::handle::win32::name * is not NULL, then it must point to a NULL-terminated array of * UTF-16 characters that refers to a ID3D12Heap object. * * If ::cudaExternalMemoryHandleDesc::type is * ::cudaExternalMemoryHandleTypeD3D12Resource, then exactly one * of ::cudaExternalMemoryHandleDesc::handle::win32::handle and * ::cudaExternalMemoryHandleDesc::handle::win32::name must not be * NULL. If ::cudaExternalMemoryHandleDesc::handle::win32::handle * is not NULL, then it must represent a valid shared NT handle that * is returned by ID3D12Device::CreateSharedHandle when referring to a * ID3D12Resource object. This handle holds a reference to the * underlying object. If * ::cudaExternalMemoryHandleDesc::handle::win32::name * is not NULL, then it must point to a NULL-terminated array of * UTF-16 characters that refers to a ID3D12Resource object. * * If ::cudaExternalMemoryHandleDesc::type is * ::cudaExternalMemoryHandleTypeD3D11Resource,then exactly one * of ::cudaExternalMemoryHandleDesc::handle::win32::handle and * ::cudaExternalMemoryHandleDesc::handle::win32::name must not be * NULL. If ::cudaExternalMemoryHandleDesc::handle::win32::handle is * not NULL, then it must represent a valid shared NT handle that is * returned by IDXGIResource1::CreateSharedHandle when referring to a * ID3D11Resource object. If * ::cudaExternalMemoryHandleDesc::handle::win32::name * is not NULL, then it must point to a NULL-terminated array of * UTF-16 characters that refers to a ID3D11Resource object. * * If ::cudaExternalMemoryHandleDesc::type is * ::cudaExternalMemoryHandleTypeD3D11ResourceKmt, then * ::cudaExternalMemoryHandleDesc::handle::win32::handle must * be non-NULL and ::cudaExternalMemoryHandleDesc::handle::win32::name * must be NULL. The handle specified must be a valid shared KMT * handle that is returned by IDXGIResource::GetSharedHandle when * referring to a ID3D11Resource object. * * If ::cudaExternalMemoryHandleDesc::type is * ::cudaExternalMemoryHandleTypeNvSciBuf, then * ::cudaExternalMemoryHandleDesc::handle::nvSciBufObject must be NON-NULL * and reference a valid NvSciBuf object. * If the NvSciBuf object imported into CUDA is also mapped by other drivers, then the * application must use ::cudaWaitExternalSemaphoresAsync or ::cudaSignalExternalSemaphoresAsync * as approprriate barriers to maintain coherence between CUDA and the other drivers. * See ::cudaExternalSemaphoreWaitSkipNvSciBufMemSync and ::cudaExternalSemaphoreSignalSkipNvSciBufMemSync * for memory synchronization. * * The size of the memory object must be specified in * ::cudaExternalMemoryHandleDesc::size. * * Specifying the flag ::cudaExternalMemoryDedicated in * ::cudaExternalMemoryHandleDesc::flags indicates that the * resource is a dedicated resource. The definition of what a * dedicated resource is outside the scope of this extension. * This flag must be set if ::cudaExternalMemoryHandleDesc::type * is one of the following: * ::cudaExternalMemoryHandleTypeD3D12Resource * ::cudaExternalMemoryHandleTypeD3D11Resource * ::cudaExternalMemoryHandleTypeD3D11ResourceKmt * * \param extMem_out - Returned handle to an external memory object * \param memHandleDesc - Memory import handle descriptor * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorOperatingSystem * \notefnerr * \note_init_rt * \note_callback * * \note If the Vulkan memory imported into CUDA is mapped on the CPU then the * application must use vkInvalidateMappedMemoryRanges/vkFlushMappedMemoryRanges * as well as appropriate Vulkan pipeline barriers to maintain coherence between * CPU and GPU. For more information on these APIs, please refer to "Synchronization * and Cache Control" chapter from Vulkan specification. * * * \sa ::cudaDestroyExternalMemory, * ::cudaExternalMemoryGetMappedBuffer, * ::cudaExternalMemoryGetMappedMipmappedArray */ extern __host__ cudaError_t CUDARTAPI cudaImportExternalMemory(cudaExternalMemory_t *extMem_out, const struct cudaExternalMemoryHandleDesc *memHandleDesc); /** * \brief Maps a buffer onto an imported memory object * * Maps a buffer onto an imported memory object and returns a device * pointer in \p devPtr. * * The properties of the buffer being mapped must be described in * \p bufferDesc. The ::cudaExternalMemoryBufferDesc structure is * defined as follows: * * \code typedef struct cudaExternalMemoryBufferDesc_st { unsigned long long offset; unsigned long long size; unsigned int flags; } cudaExternalMemoryBufferDesc; * \endcode * * where ::cudaExternalMemoryBufferDesc::offset is the offset in * the memory object where the buffer's base address is. * ::cudaExternalMemoryBufferDesc::size is the size of the buffer. * ::cudaExternalMemoryBufferDesc::flags must be zero. * * The offset and size have to be suitably aligned to match the * requirements of the external API. Mapping two buffers whose ranges * overlap may or may not result in the same virtual address being * returned for the overlapped portion. In such cases, the application * must ensure that all accesses to that region from the GPU are * volatile. Otherwise writes made via one address are not guaranteed * to be visible via the other address, even if they're issued by the * same thread. It is recommended that applications map the combined * range instead of mapping separate buffers and then apply the * appropriate offsets to the returned pointer to derive the * individual buffers. * * The returned pointer \p devPtr must be freed using ::cudaFree. * * \param devPtr - Returned device pointer to buffer * \param extMem - Handle to external memory object * \param bufferDesc - Buffer descriptor * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaImportExternalMemory, * ::cudaDestroyExternalMemory, * ::cudaExternalMemoryGetMappedMipmappedArray */ extern __host__ cudaError_t CUDARTAPI cudaExternalMemoryGetMappedBuffer(void **devPtr, cudaExternalMemory_t extMem, const struct cudaExternalMemoryBufferDesc *bufferDesc); /** * \brief Maps a CUDA mipmapped array onto an external memory object * * Maps a CUDA mipmapped array onto an external object and returns a * handle to it in \p mipmap. * * The properties of the CUDA mipmapped array being mapped must be * described in \p mipmapDesc. The structure * ::cudaExternalMemoryMipmappedArrayDesc is defined as follows: * * \code typedef struct cudaExternalMemoryMipmappedArrayDesc_st { unsigned long long offset; cudaChannelFormatDesc formatDesc; cudaExtent extent; unsigned int flags; unsigned int numLevels; } cudaExternalMemoryMipmappedArrayDesc; * \endcode * * where ::cudaExternalMemoryMipmappedArrayDesc::offset is the * offset in the memory object where the base level of the mipmap * chain is. * ::cudaExternalMemoryMipmappedArrayDesc::formatDesc describes the * format of the data. * ::cudaExternalMemoryMipmappedArrayDesc::extent specifies the * dimensions of the base level of the mipmap chain. * ::cudaExternalMemoryMipmappedArrayDesc::flags are flags associated * with CUDA mipmapped arrays. For further details, please refer to * the documentation for ::cudaMalloc3DArray. Note that if the mipmapped * array is bound as a color target in the graphics API, then the flag * ::cudaArrayColorAttachment must be specified in * ::cudaExternalMemoryMipmappedArrayDesc::flags. * ::cudaExternalMemoryMipmappedArrayDesc::numLevels specifies * the total number of levels in the mipmap chain. * * The returned CUDA mipmapped array must be freed using ::cudaFreeMipmappedArray. * * \param mipmap - Returned CUDA mipmapped array * \param extMem - Handle to external memory object * \param mipmapDesc - CUDA array descriptor * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaImportExternalMemory, * ::cudaDestroyExternalMemory, * ::cudaExternalMemoryGetMappedBuffer * * \note If ::cudaExternalMemoryHandleDesc::type is * ::cudaExternalMemoryHandleTypeNvSciBuf, then * ::cudaExternalMemoryMipmappedArrayDesc::numLevels must not be greater than 1. */ extern __host__ cudaError_t CUDARTAPI cudaExternalMemoryGetMappedMipmappedArray(cudaMipmappedArray_t *mipmap, cudaExternalMemory_t extMem, const struct cudaExternalMemoryMipmappedArrayDesc *mipmapDesc); /** * \brief Destroys an external memory object. * * Destroys the specified external memory object. Any existing buffers * and CUDA mipmapped arrays mapped onto this object must no longer be * used and must be explicitly freed using ::cudaFree and * ::cudaFreeMipmappedArray respectively. * * \param extMem - External memory object to be destroyed * * \return * ::cudaSuccess, * ::cudaErrorInvalidResourceHandle * \notefnerr * \note_init_rt * \note_callback * \note_destroy_ub * * \sa ::cudaImportExternalMemory, * ::cudaExternalMemoryGetMappedBuffer, * ::cudaExternalMemoryGetMappedMipmappedArray */ extern __host__ cudaError_t CUDARTAPI cudaDestroyExternalMemory(cudaExternalMemory_t extMem); /** * \brief Imports an external semaphore * * Imports an externally allocated synchronization object and returns * a handle to that in \p extSem_out. * * The properties of the handle being imported must be described in * \p semHandleDesc. The ::cudaExternalSemaphoreHandleDesc is defined * as follows: * * \code typedef struct cudaExternalSemaphoreHandleDesc_st { cudaExternalSemaphoreHandleType type; union { int fd; struct { void *handle; const void *name; } win32; const void* NvSciSyncObj; } handle; unsigned int flags; } cudaExternalSemaphoreHandleDesc; * \endcode * * where ::cudaExternalSemaphoreHandleDesc::type specifies the type of * handle being imported. ::cudaExternalSemaphoreHandleType is defined * as: * * \code typedef enum cudaExternalSemaphoreHandleType_enum { cudaExternalSemaphoreHandleTypeOpaqueFd = 1, cudaExternalSemaphoreHandleTypeOpaqueWin32 = 2, cudaExternalSemaphoreHandleTypeOpaqueWin32Kmt = 3, cudaExternalSemaphoreHandleTypeD3D12Fence = 4, cudaExternalSemaphoreHandleTypeD3D11Fence = 5, cudaExternalSemaphoreHandleTypeNvSciSync = 6, cudaExternalSemaphoreHandleTypeKeyedMutex = 7, cudaExternalSemaphoreHandleTypeKeyedMutexKmt = 8, cudaExternalSemaphoreHandleTypeTimelineSemaphoreFd = 9, cudaExternalSemaphoreHandleTypeTimelineSemaphoreWin32 = 10 } cudaExternalSemaphoreHandleType; * \endcode * * If ::cudaExternalSemaphoreHandleDesc::type is * ::cudaExternalSemaphoreHandleTypeOpaqueFd, then * ::cudaExternalSemaphoreHandleDesc::handle::fd must be a valid file * descriptor referencing a synchronization object. Ownership of the * file descriptor is transferred to the CUDA driver when the handle * is imported successfully. Performing any operations on the file * descriptor after it is imported results in undefined behavior. * * If ::cudaExternalSemaphoreHandleDesc::type is * ::cudaExternalSemaphoreHandleTypeOpaqueWin32, then exactly one of * ::cudaExternalSemaphoreHandleDesc::handle::win32::handle and * ::cudaExternalSemaphoreHandleDesc::handle::win32::name must not be * NULL. If ::cudaExternalSemaphoreHandleDesc::handle::win32::handle * is not NULL, then it must represent a valid shared NT handle that * references a synchronization object. Ownership of this handle is * not transferred to CUDA after the import operation, so the * application must release the handle using the appropriate system * call. If ::cudaExternalSemaphoreHandleDesc::handle::win32::name is * not NULL, then it must name a valid synchronization object. * * If ::cudaExternalSemaphoreHandleDesc::type is * ::cudaExternalSemaphoreHandleTypeOpaqueWin32Kmt, then * ::cudaExternalSemaphoreHandleDesc::handle::win32::handle must be * non-NULL and ::cudaExternalSemaphoreHandleDesc::handle::win32::name * must be NULL. The handle specified must be a globally shared KMT * handle. This handle does not hold a reference to the underlying * object, and thus will be invalid when all references to the * synchronization object are destroyed. * * If ::cudaExternalSemaphoreHandleDesc::type is * ::cudaExternalSemaphoreHandleTypeD3D12Fence, then exactly one of * ::cudaExternalSemaphoreHandleDesc::handle::win32::handle and * ::cudaExternalSemaphoreHandleDesc::handle::win32::name must not be * NULL. If ::cudaExternalSemaphoreHandleDesc::handle::win32::handle * is not NULL, then it must represent a valid shared NT handle that * is returned by ID3D12Device::CreateSharedHandle when referring to a * ID3D12Fence object. This handle holds a reference to the underlying * object. If ::cudaExternalSemaphoreHandleDesc::handle::win32::name * is not NULL, then it must name a valid synchronization object that * refers to a valid ID3D12Fence object. * * If ::cudaExternalSemaphoreHandleDesc::type is * ::cudaExternalSemaphoreHandleTypeD3D11Fence, then exactly one of * ::cudaExternalSemaphoreHandleDesc::handle::win32::handle and * ::cudaExternalSemaphoreHandleDesc::handle::win32::name must not be * NULL. If ::cudaExternalSemaphoreHandleDesc::handle::win32::handle * is not NULL, then it must represent a valid shared NT handle that * is returned by ID3D11Fence::CreateSharedHandle. If * ::cudaExternalSemaphoreHandleDesc::handle::win32::name * is not NULL, then it must name a valid synchronization object that * refers to a valid ID3D11Fence object. * * If ::cudaExternalSemaphoreHandleDesc::type is * ::cudaExternalSemaphoreHandleTypeNvSciSync, then * ::cudaExternalSemaphoreHandleDesc::handle::nvSciSyncObj * represents a valid NvSciSyncObj. * * ::cudaExternalSemaphoreHandleTypeKeyedMutex, then exactly one of * ::cudaExternalSemaphoreHandleDesc::handle::win32::handle and * ::cudaExternalSemaphoreHandleDesc::handle::win32::name must not be * NULL. If ::cudaExternalSemaphoreHandleDesc::handle::win32::handle * is not NULL, then it represent a valid shared NT handle that * is returned by IDXGIResource1::CreateSharedHandle when referring to * a IDXGIKeyedMutex object. * * If ::cudaExternalSemaphoreHandleDesc::type is * ::cudaExternalSemaphoreHandleTypeKeyedMutexKmt, then * ::cudaExternalSemaphoreHandleDesc::handle::win32::handle must be * non-NULL and ::cudaExternalSemaphoreHandleDesc::handle::win32::name * must be NULL. The handle specified must represent a valid KMT * handle that is returned by IDXGIResource::GetSharedHandle when * referring to a IDXGIKeyedMutex object. * * If ::cudaExternalSemaphoreHandleDesc::type is * ::cudaExternalSemaphoreHandleTypeTimelineSemaphoreFd, then * ::cudaExternalSemaphoreHandleDesc::handle::fd must be a valid file * descriptor referencing a synchronization object. Ownership of the * file descriptor is transferred to the CUDA driver when the handle * is imported successfully. Performing any operations on the file * descriptor after it is imported results in undefined behavior. * * If ::cudaExternalSemaphoreHandleDesc::type is * ::cudaExternalSemaphoreHandleTypeTimelineSemaphoreWin32, then exactly one of * ::cudaExternalSemaphoreHandleDesc::handle::win32::handle and * ::cudaExternalSemaphoreHandleDesc::handle::win32::name must not be * NULL. If ::cudaExternalSemaphoreHandleDesc::handle::win32::handle * is not NULL, then it must represent a valid shared NT handle that * references a synchronization object. Ownership of this handle is * not transferred to CUDA after the import operation, so the * application must release the handle using the appropriate system * call. If ::cudaExternalSemaphoreHandleDesc::handle::win32::name is * not NULL, then it must name a valid synchronization object. * * \param extSem_out - Returned handle to an external semaphore * \param semHandleDesc - Semaphore import handle descriptor * * \return * ::cudaSuccess, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorOperatingSystem * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaDestroyExternalSemaphore, * ::cudaSignalExternalSemaphoresAsync, * ::cudaWaitExternalSemaphoresAsync */ extern __host__ cudaError_t CUDARTAPI cudaImportExternalSemaphore(cudaExternalSemaphore_t *extSem_out, const struct cudaExternalSemaphoreHandleDesc *semHandleDesc); /** * \brief Signals a set of external semaphore objects * * Enqueues a signal operation on a set of externally allocated * semaphore object in the specified stream. The operations will be * executed when all prior operations in the stream complete. * * The exact semantics of signaling a semaphore depends on the type of * the object. * * If the semaphore object is any one of the following types: * ::cudaExternalSemaphoreHandleTypeOpaqueFd, * ::cudaExternalSemaphoreHandleTypeOpaqueWin32, * ::cudaExternalSemaphoreHandleTypeOpaqueWin32Kmt * then signaling the semaphore will set it to the signaled state. * * If the semaphore object is any one of the following types: * ::cudaExternalSemaphoreHandleTypeD3D12Fence, * ::cudaExternalSemaphoreHandleTypeD3D11Fence, * ::cudaExternalSemaphoreHandleTypeTimelineSemaphoreFd, * ::cudaExternalSemaphoreHandleTypeTimelineSemaphoreWin32 * then the semaphore will be set to the value specified in * ::cudaExternalSemaphoreSignalParams::params::fence::value. * * If the semaphore object is of the type ::cudaExternalSemaphoreHandleTypeNvSciSync * this API sets ::cudaExternalSemaphoreSignalParams::params::nvSciSync::fence to a * value that can be used by subsequent waiters of the same NvSciSync object to * order operations with those currently submitted in \p stream. Such an update * will overwrite previous contents of * ::cudaExternalSemaphoreSignalParams::params::nvSciSync::fence. By default, * signaling such an external semaphore object causes appropriate memory synchronization * operations to be performed over all the external memory objects that are imported as * ::cudaExternalMemoryHandleTypeNvSciBuf. This ensures that any subsequent accesses * made by other importers of the same set of NvSciBuf memory object(s) are coherent. * These operations can be skipped by specifying the flag * ::cudaExternalSemaphoreSignalSkipNvSciBufMemSync, which can be used as a * performance optimization when data coherency is not required. But specifying this * flag in scenarios where data coherency is required results in undefined behavior. * Also, for semaphore object of the type ::cudaExternalSemaphoreHandleTypeNvSciSync, * if the NvSciSyncAttrList used to create the NvSciSyncObj had not set the flags in * ::cudaDeviceGetNvSciSyncAttributes to cudaNvSciSyncAttrSignal, this API will return * cudaErrorNotSupported. * * ::cudaExternalSemaphoreSignalParams::params::nvSciSync::fence associated with * semaphore object of the type ::cudaExternalSemaphoreHandleTypeNvSciSync can be * deterministic. For this the NvSciSyncAttrList used to create the semaphore object * must have value of NvSciSyncAttrKey_RequireDeterministicFences key set to true. * Deterministic fences allow users to enqueue a wait over the semaphore object even * before corresponding signal is enqueued. For such a semaphore object, CUDA guarantees * that each signal operation will increment the fence value by '1'. Users are expected * to track count of signals enqueued on the semaphore object and insert waits accordingly. * When such a semaphore object is signaled from multiple streams, due to concurrent * stream execution, it is possible that the order in which the semaphore gets signaled * is indeterministic. This could lead to waiters of the semaphore getting unblocked * incorrectly. Users are expected to handle such situations, either by not using the * same semaphore object with deterministic fence support enabled in different streams * or by adding explicit dependency amongst such streams so that the semaphore is * signaled in order. * * If the semaphore object is any one of the following types: * ::cudaExternalSemaphoreHandleTypeKeyedMutex, * ::cudaExternalSemaphoreHandleTypeKeyedMutexKmt, * then the keyed mutex will be released with the key specified in * ::cudaExternalSemaphoreSignalParams::params::keyedmutex::key. * * \param extSemArray - Set of external semaphores to be signaled * \param paramsArray - Array of semaphore parameters * \param numExtSems - Number of semaphores to signal * \param stream - Stream to enqueue the signal operations in * * \return * ::cudaSuccess, * ::cudaErrorInvalidResourceHandle * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaImportExternalSemaphore, * ::cudaDestroyExternalSemaphore, * ::cudaWaitExternalSemaphoresAsync */ extern __host__ cudaError_t CUDARTAPI cudaSignalExternalSemaphoresAsync(const cudaExternalSemaphore_t *extSemArray, const struct cudaExternalSemaphoreSignalParams *paramsArray, unsigned int numExtSems, cudaStream_t stream __dv(0)); /** * \brief Waits on a set of external semaphore objects * * Enqueues a wait operation on a set of externally allocated * semaphore object in the specified stream. The operations will be * executed when all prior operations in the stream complete. * * The exact semantics of waiting on a semaphore depends on the type * of the object. * * If the semaphore object is any one of the following types: * ::cudaExternalSemaphoreHandleTypeOpaqueFd, * ::cudaExternalSemaphoreHandleTypeOpaqueWin32, * ::cudaExternalSemaphoreHandleTypeOpaqueWin32Kmt * then waiting on the semaphore will wait until the semaphore reaches * the signaled state. The semaphore will then be reset to the * unsignaled state. Therefore for every signal operation, there can * only be one wait operation. * * If the semaphore object is any one of the following types: * ::cudaExternalSemaphoreHandleTypeD3D12Fence, * ::cudaExternalSemaphoreHandleTypeD3D11Fence, * ::cudaExternalSemaphoreHandleTypeTimelineSemaphoreFd, * ::cudaExternalSemaphoreHandleTypeTimelineSemaphoreWin32 * then waiting on the semaphore will wait until the value of the * semaphore is greater than or equal to * ::cudaExternalSemaphoreWaitParams::params::fence::value. * * If the semaphore object is of the type ::cudaExternalSemaphoreHandleTypeNvSciSync * then, waiting on the semaphore will wait until the * ::cudaExternalSemaphoreSignalParams::params::nvSciSync::fence is signaled by the * signaler of the NvSciSyncObj that was associated with this semaphore object. * By default, waiting on such an external semaphore object causes appropriate * memory synchronization operations to be performed over all external memory objects * that are imported as ::cudaExternalMemoryHandleTypeNvSciBuf. This ensures that * any subsequent accesses made by other importers of the same set of NvSciBuf memory * object(s) are coherent. These operations can be skipped by specifying the flag * ::cudaExternalSemaphoreWaitSkipNvSciBufMemSync, which can be used as a * performance optimization when data coherency is not required. But specifying this * flag in scenarios where data coherency is required results in undefined behavior. * Also, for semaphore object of the type ::cudaExternalSemaphoreHandleTypeNvSciSync, * if the NvSciSyncAttrList used to create the NvSciSyncObj had not set the flags in * ::cudaDeviceGetNvSciSyncAttributes to cudaNvSciSyncAttrWait, this API will return * cudaErrorNotSupported. * * If the semaphore object is any one of the following types: * ::cudaExternalSemaphoreHandleTypeKeyedMutex, * ::cudaExternalSemaphoreHandleTypeKeyedMutexKmt, * then the keyed mutex will be acquired when it is released with the key specified * in ::cudaExternalSemaphoreSignalParams::params::keyedmutex::key or * until the timeout specified by * ::cudaExternalSemaphoreSignalParams::params::keyedmutex::timeoutMs * has lapsed. The timeout interval can either be a finite value * specified in milliseconds or an infinite value. In case an infinite * value is specified the timeout never elapses. The windows INFINITE * macro must be used to specify infinite timeout * * \param extSemArray - External semaphores to be waited on * \param paramsArray - Array of semaphore parameters * \param numExtSems - Number of semaphores to wait on * \param stream - Stream to enqueue the wait operations in * * \return * ::cudaSuccess, * ::cudaErrorInvalidResourceHandle * ::cudaErrorTimeout * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaImportExternalSemaphore, * ::cudaDestroyExternalSemaphore, * ::cudaSignalExternalSemaphoresAsync */ extern __host__ cudaError_t CUDARTAPI cudaWaitExternalSemaphoresAsync(const cudaExternalSemaphore_t *extSemArray, const struct cudaExternalSemaphoreWaitParams *paramsArray, unsigned int numExtSems, cudaStream_t stream __dv(0)); /** * \brief Destroys an external semaphore * * Destroys an external semaphore object and releases any references * to the underlying resource. Any outstanding signals or waits must * have completed before the semaphore is destroyed. * * \param extSem - External semaphore to be destroyed * * \return * ::cudaSuccess, * ::cudaErrorInvalidResourceHandle * \notefnerr * \note_init_rt * \note_callback * \note_destroy_ub * * \sa ::cudaImportExternalSemaphore, * ::cudaSignalExternalSemaphoresAsync, * ::cudaWaitExternalSemaphoresAsync */ extern __host__ cudaError_t CUDARTAPI cudaDestroyExternalSemaphore(cudaExternalSemaphore_t extSem); /** @} */ /* END CUDART_EXTRES_INTEROP */ /** * \defgroup CUDART_EXECUTION Execution Control * * ___MANBRIEF___ execution control functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the execution control functions of the CUDA runtime * application programming interface. * * Some functions have overloaded C++ API template versions documented separately in the * \ref CUDART_HIGHLEVEL "C++ API Routines" module. * * @{ */ /** * \brief Launches a device function * * The function invokes kernel \p func on \p gridDim (\p gridDim.x × \p gridDim.y * × \p gridDim.z) grid of blocks. Each block contains \p blockDim (\p blockDim.x × * \p blockDim.y × \p blockDim.z) threads. * * If the kernel has N parameters the \p args should point to array of N pointers. * Each pointer, from args[0] to args[N - 1], point to the region * of memory from which the actual parameter will be copied. * * For templated functions, pass the function symbol as follows: * func_name * * \p sharedMem sets the amount of dynamic shared memory that will be available to * each thread block. * * \p stream specifies a stream the invocation is associated to. * * \param func - Device function symbol * \param gridDim - Grid dimentions * \param blockDim - Block dimentions * \param args - Arguments * \param sharedMem - Shared memory * \param stream - Stream identifier * * \return * ::cudaSuccess, * ::cudaErrorInvalidDeviceFunction, * ::cudaErrorInvalidConfiguration, * ::cudaErrorLaunchFailure, * ::cudaErrorLaunchTimeout, * ::cudaErrorLaunchOutOfResources, * ::cudaErrorSharedObjectInitFailed, * ::cudaErrorInvalidPtx, * ::cudaErrorUnsupportedPtxVersion, * ::cudaErrorNoKernelImageForDevice, * ::cudaErrorJitCompilerNotFound, * ::cudaErrorJitCompilationDisabled * \note_null_stream * \notefnerr * \note_init_rt * \note_callback * \note_cudaKernel_t * * \sa * \ref ::cudaLaunchKernel(const T *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream) "cudaLaunchKernel (C++ API)", * ::cuLaunchKernel */ extern __host__ cudaError_t CUDARTAPI cudaLaunchKernel(const void *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream); /** * \brief Launches a CUDA function with launch-time configuration * * Note that the functionally equivalent variadic template ::cudaLaunchKernelEx * is available for C++11 and newer. * * Invokes the kernel \p func on \p config->gridDim (\p config->gridDim.x * × \p config->gridDim.y × \p config->gridDim.z) grid of blocks. * Each block contains \p config->blockDim (\p config->blockDim.x × * \p config->blockDim.y × \p config->blockDim.z) threads. * * \p config->dynamicSmemBytes sets the amount of dynamic shared memory that * will be available to each thread block. * * \p config->stream specifies a stream the invocation is associated to. * * Configuration beyond grid and block dimensions, dynamic shared memory size, * and stream can be provided with the following two fields of \p config: * * \p config->attrs is an array of \p config->numAttrs contiguous * ::cudaLaunchAttribute elements. The value of this pointer is not considered * if \p config->numAttrs is zero. However, in that case, it is recommended to * set the pointer to NULL. * \p config->numAttrs is the number of attributes populating the first * \p config->numAttrs positions of the \p config->attrs array. * * If the kernel has N parameters the \p args should point to array of N * pointers. Each pointer, from args[0] to args[N - 1], point * to the region of memory from which the actual parameter will be copied. * * N.B. This function is so named to avoid unintentionally invoking the * templated version, \p cudaLaunchKernelEx, for kernels taking a single * void** or void* parameter. * * \param config - Launch configuration * \param func - Kernel to launch * \param args - Array of pointers to kernel parameters * * \return * ::cudaSuccess, * ::cudaErrorInvalidDeviceFunction, * ::cudaErrorInvalidConfiguration, * ::cudaErrorLaunchFailure, * ::cudaErrorLaunchTimeout, * ::cudaErrorLaunchOutOfResources, * ::cudaErrorSharedObjectInitFailed, * ::cudaErrorInvalidPtx, * ::cudaErrorUnsupportedPtxVersion, * ::cudaErrorNoKernelImageForDevice, * ::cudaErrorJitCompilerNotFound, * ::cudaErrorJitCompilationDisabled * \note_null_stream * \notefnerr * \note_init_rt * \note_callback * \note_cudaKernel_t * * \sa * \ref ::cudaLaunchKernelEx(const cudaLaunchConfig_t *config, void (*kernel)(ExpTypes...), ActTypes &&... args) "cudaLaunchKernelEx (C++ API)", * ::cuLaunchKernelEx */ extern __host__ cudaError_t CUDARTAPI cudaLaunchKernelExC(const cudaLaunchConfig_t *config, const void *func, void **args); /** * \brief Launches a device function where thread blocks can cooperate and synchronize as they execute * * The function invokes kernel \p func on \p gridDim (\p gridDim.x × \p gridDim.y * × \p gridDim.z) grid of blocks. Each block contains \p blockDim (\p blockDim.x × * \p blockDim.y × \p blockDim.z) threads. * * The device on which this kernel is invoked must have a non-zero value for * the device attribute ::cudaDevAttrCooperativeLaunch. * * The total number of blocks launched cannot exceed the maximum number of blocks per * multiprocessor as returned by ::cudaOccupancyMaxActiveBlocksPerMultiprocessor (or * ::cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlags) times the number of multiprocessors * as specified by the device attribute ::cudaDevAttrMultiProcessorCount. * * The kernel cannot make use of CUDA dynamic parallelism. * * If the kernel has N parameters the \p args should point to array of N pointers. * Each pointer, from args[0] to args[N - 1], point to the region * of memory from which the actual parameter will be copied. * * For templated functions, pass the function symbol as follows: * func_name * * \p sharedMem sets the amount of dynamic shared memory that will be available to * each thread block. * * \p stream specifies a stream the invocation is associated to. * * \param func - Device function symbol * \param gridDim - Grid dimentions * \param blockDim - Block dimentions * \param args - Arguments * \param sharedMem - Shared memory * \param stream - Stream identifier * * \return * ::cudaSuccess, * ::cudaErrorInvalidDeviceFunction, * ::cudaErrorInvalidConfiguration, * ::cudaErrorLaunchFailure, * ::cudaErrorLaunchTimeout, * ::cudaErrorLaunchOutOfResources, * ::cudaErrorCooperativeLaunchTooLarge, * ::cudaErrorSharedObjectInitFailed * \note_null_stream * \notefnerr * \note_init_rt * \note_callback * \note_cudaKernel_t * * \sa * \ref ::cudaLaunchCooperativeKernel(const T *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream) "cudaLaunchCooperativeKernel (C++ API)", * ::cudaLaunchCooperativeKernelMultiDevice, * ::cuLaunchCooperativeKernel */ extern __host__ cudaError_t CUDARTAPI cudaLaunchCooperativeKernel(const void *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream); /** * \brief Launches device functions on multiple devices where thread blocks can cooperate and synchronize as they execute * * \deprecated This function is deprecated as of CUDA 11.3. * * Invokes kernels as specified in the \p launchParamsList array where each element * of the array specifies all the parameters required to perform a single kernel launch. * These kernels can cooperate and synchronize as they execute. The size of the array is * specified by \p numDevices. * * No two kernels can be launched on the same device. All the devices targeted by this * multi-device launch must be identical. All devices must have a non-zero value for the * device attribute ::cudaDevAttrCooperativeMultiDeviceLaunch. * * The same kernel must be launched on all devices. Note that any __device__ or __constant__ * variables are independently instantiated on every device. It is the application's * responsiblity to ensure these variables are initialized and used appropriately. * * The size of the grids as specified in blocks, the size of the blocks themselves and the * amount of shared memory used by each thread block must also match across all launched kernels. * * The streams used to launch these kernels must have been created via either ::cudaStreamCreate * or ::cudaStreamCreateWithPriority or ::cudaStreamCreateWithPriority. The NULL stream or * ::cudaStreamLegacy or ::cudaStreamPerThread cannot be used. * * The total number of blocks launched per kernel cannot exceed the maximum number of blocks * per multiprocessor as returned by ::cudaOccupancyMaxActiveBlocksPerMultiprocessor (or * ::cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlags) times the number of multiprocessors * as specified by the device attribute ::cudaDevAttrMultiProcessorCount. Since the * total number of blocks launched per device has to match across all devices, the maximum * number of blocks that can be launched per device will be limited by the device with the * least number of multiprocessors. * * The kernel cannot make use of CUDA dynamic parallelism. * * The ::cudaLaunchParams structure is defined as: * \code struct cudaLaunchParams { void *func; dim3 gridDim; dim3 blockDim; void **args; size_t sharedMem; cudaStream_t stream; }; * \endcode * where: * - ::cudaLaunchParams::func specifies the kernel to be launched. This same functions must * be launched on all devices. For templated functions, pass the function symbol as follows: * func_name * - ::cudaLaunchParams::gridDim specifies the width, height and depth of the grid in blocks. * This must match across all kernels launched. * - ::cudaLaunchParams::blockDim is the width, height and depth of each thread block. This * must match across all kernels launched. * - ::cudaLaunchParams::args specifies the arguments to the kernel. If the kernel has * N parameters then ::cudaLaunchParams::args should point to array of N pointers. Each * pointer, from ::cudaLaunchParams::args[0] to ::cudaLaunchParams::args[N - 1], * point to the region of memory from which the actual parameter will be copied. * - ::cudaLaunchParams::sharedMem is the dynamic shared-memory size per thread block in bytes. * This must match across all kernels launched. * - ::cudaLaunchParams::stream is the handle to the stream to perform the launch in. This cannot * be the NULL stream or ::cudaStreamLegacy or ::cudaStreamPerThread. * * By default, the kernel won't begin execution on any GPU until all prior work in all the specified * streams has completed. This behavior can be overridden by specifying the flag * ::cudaCooperativeLaunchMultiDeviceNoPreSync. When this flag is specified, each kernel * will only wait for prior work in the stream corresponding to that GPU to complete before it begins * execution. * * Similarly, by default, any subsequent work pushed in any of the specified streams will not begin * execution until the kernels on all GPUs have completed. This behavior can be overridden by specifying * the flag ::cudaCooperativeLaunchMultiDeviceNoPostSync. When this flag is specified, * any subsequent work pushed in any of the specified streams will only wait for the kernel launched * on the GPU corresponding to that stream to complete before it begins execution. * * \param launchParamsList - List of launch parameters, one per device * \param numDevices - Size of the \p launchParamsList array * \param flags - Flags to control launch behavior * * \return * ::cudaSuccess, * ::cudaErrorInvalidDeviceFunction, * ::cudaErrorInvalidConfiguration, * ::cudaErrorLaunchFailure, * ::cudaErrorLaunchTimeout, * ::cudaErrorLaunchOutOfResources, * ::cudaErrorCooperativeLaunchTooLarge, * ::cudaErrorSharedObjectInitFailed * \note_null_stream * \notefnerr * \note_init_rt * \note_callback * * \sa * \ref ::cudaLaunchCooperativeKernel(const T *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream) "cudaLaunchCooperativeKernel (C++ API)", * ::cudaLaunchCooperativeKernel, * ::cuLaunchCooperativeKernelMultiDevice */ extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaLaunchCooperativeKernelMultiDevice(struct cudaLaunchParams *launchParamsList, unsigned int numDevices, unsigned int flags __dv(0)); /** * \brief Sets the preferred cache configuration for a device function * * On devices where the L1 cache and shared memory use the same hardware * resources, this sets through \p cacheConfig the preferred cache configuration * for the function specified via \p func. This is only a preference. The * runtime will use the requested configuration if possible, but it is free to * choose a different configuration if required to execute \p func. * * \p func is a device function symbol and must be declared as a * \c __global__ function. If the specified function does not exist, * then ::cudaErrorInvalidDeviceFunction is returned. For templated functions, * pass the function symbol as follows: func_name * * This setting does nothing on devices where the size of the L1 cache and * shared memory are fixed. * * Launching a kernel with a different preference than the most recent * preference setting may insert a device-side synchronization point. * * The supported cache configurations are: * - ::cudaFuncCachePreferNone: no preference for shared memory or L1 (default) * - ::cudaFuncCachePreferShared: prefer larger shared memory and smaller L1 cache * - ::cudaFuncCachePreferL1: prefer larger L1 cache and smaller shared memory * - ::cudaFuncCachePreferEqual: prefer equal size L1 cache and shared memory * * \param func - Device function symbol * \param cacheConfig - Requested cache configuration * * \return * ::cudaSuccess, * ::cudaErrorInvalidDeviceFunction * \notefnerr * \note_string_api_deprecation2 * \note_init_rt * \note_callback * * \note This API does not accept a ::cudaKernel_t casted as void*. If cache config modification * is required for a ::cudaKernel_t (or a __global__ function), it can be replaced with a call to * ::cudaFuncSetAttributes with the attribute ::cudaFuncAttributePreferredSharedMemoryCarveout * to specify a more granular L1 cache and shared memory split configuration. * * \sa * \ref ::cudaFuncSetCacheConfig(T*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C++ API)", * \ref ::cudaFuncGetAttributes(struct cudaFuncAttributes*, const void*) "cudaFuncGetAttributes (C API)", * \ref ::cudaLaunchKernel(const void *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream) "cudaLaunchKernel (C API)", * ::cuFuncSetCacheConfig */ extern __host__ cudaError_t CUDARTAPI cudaFuncSetCacheConfig(const void *func, enum cudaFuncCache cacheConfig); /** * \brief Find out attributes for a given function * * This function obtains the attributes of a function specified via \p func. * \p func is a device function symbol and must be declared as a * \c __global__ function. The fetched attributes are placed in \p attr. * If the specified function does not exist, then it is assumed to * be a ::cudaKernel_t and used as is. * For templated functions, pass the function symbol as follows: * func_name * * Note that some function attributes such as * \ref ::cudaFuncAttributes::maxThreadsPerBlock "maxThreadsPerBlock" * may vary based on the device that is currently being used. * * \param attr - Return pointer to function's attributes * \param func - Device function symbol * * \return * ::cudaSuccess, * ::cudaErrorInvalidDeviceFunction * \notefnerr * \note_string_api_deprecation2 * \note_init_rt * \note_callback * \note_cudaKernel_t * * \sa * \ref ::cudaFuncSetCacheConfig(const void*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C API)", * \ref ::cudaFuncGetAttributes(struct cudaFuncAttributes*, T*) "cudaFuncGetAttributes (C++ API)", * \ref ::cudaLaunchKernel(const void *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream) "cudaLaunchKernel (C API)", * ::cuFuncGetAttribute */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaFuncGetAttributes(struct cudaFuncAttributes *attr, const void *func); /** * \brief Set attributes for a given function * * This function sets the attributes of a function specified via \p func. * The parameter \p func must be a pointer to a function that executes * on the device. The parameter specified by \p func must be declared as a \p __global__ * function. The enumeration defined by \p attr is set to the value defined by \p value. * If the specified function does not exist, then it is assumed to * be a ::cudaKernel_t and used as is. * If the specified attribute cannot be written, or if the value is incorrect, * then ::cudaErrorInvalidValue is returned. * * Valid values for \p attr are: * - ::cudaFuncAttributeMaxDynamicSharedMemorySize - The requested maximum size in bytes of dynamically-allocated shared memory. The sum of this value and the function attribute ::sharedSizeBytes * cannot exceed the device attribute ::cudaDevAttrMaxSharedMemoryPerBlockOptin. The maximal size of requestable dynamic shared memory may differ by GPU architecture. * - ::cudaFuncAttributePreferredSharedMemoryCarveout - On devices where the L1 cache and shared memory use the same hardware resources, * this sets the shared memory carveout preference, in percent of the total shared memory. See ::cudaDevAttrMaxSharedMemoryPerMultiprocessor. * This is only a hint, and the driver can choose a different ratio if required to execute the function. * - ::cudaFuncAttributeRequiredClusterWidth: The required cluster width in * blocks. The width, height, and depth values must either all be 0 or all be * positive. The validity of the cluster dimensions is checked at launch time. * If the value is set during compile time, it cannot be set at runtime. * Setting it at runtime will return cudaErrorNotPermitted. * - ::cudaFuncAttributeRequiredClusterHeight: The required cluster height in * blocks. The width, height, and depth values must either all be 0 or all be * positive. The validity of the cluster dimensions is checked at launch time. * If the value is set during compile time, it cannot be set at runtime. * Setting it at runtime will return cudaErrorNotPermitted. * - ::cudaFuncAttributeRequiredClusterDepth: The required cluster depth in * blocks. The width, height, and depth values must either all be 0 or all be * positive. The validity of the cluster dimensions is checked at launch time. * If the value is set during compile time, it cannot be set at runtime. * Setting it at runtime will return cudaErrorNotPermitted. * - ::cudaFuncAttributeNonPortableClusterSizeAllowed: Indicates whether the * function can be launched with non-portable cluster size. 1 is allowed, 0 is * disallowed. * - ::cudaFuncAttributeClusterSchedulingPolicyPreference: The block * scheduling policy of a function. The value type is cudaClusterSchedulingPolicy. * * \param func - Function to get attributes of * \param attr - Attribute to set * \param value - Value to set * * \return * ::cudaSuccess, * ::cudaErrorInvalidDeviceFunction, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * \note_cudaKernel_t * * \ref ::cudaLaunchKernel(const T *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream) "cudaLaunchKernel (C++ API)", * \ref ::cudaFuncSetCacheConfig(T*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C++ API)", * \ref ::cudaFuncGetAttributes(struct cudaFuncAttributes*, const void*) "cudaFuncGetAttributes (C API)", */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaFuncSetAttribute(const void *func, enum cudaFuncAttribute attr, int value); /** * \brief Returns the function name for a device entry function pointer. * * Returns in \p **name the function name associated with the symbol \p func . * The function name is returned as a null-terminated string. This API may * return a mangled name if the function is not declared as having C linkage. * If \p **name is NULL, ::cudaErrorInvalidValue is returned. * If \p func is not a device entry function, then it is assumed to * be a ::cudaKernel_t and used as is. * * \param name - The returned name of the function * \param func - The function pointer to retrieve name for * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidDeviceFunction * \notefnerr * \note_init_rt * \note_callback * \note_cudaKernel_t * * \ref ::cudaFuncGetName(const char **name, const T *func) "cudaFuncGetName (C++ API)" */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaFuncGetName(const char **name, const void *func); /** * \brief Returns the offset and size of a kernel parameter in the device-side parameter layout. * * Queries the kernel parameter at \p paramIndex in \p func's list of parameters and returns * parameter information via \p paramOffset and \p paramSize. \p paramOffset returns the * offset of the parameter in the device-side parameter layout. \p paramSize returns the size * in bytes of the parameter. This information can be used to update kernel node parameters * from the device via ::cudaGraphKernelNodeSetParam() and ::cudaGraphKernelNodeUpdatesApply(). * \p paramIndex must be less than the number of parameters that \p func takes. * * \param func - The function to query * \param paramIndex - The parameter index to query * \param paramOffset - The offset into the device-side parameter layout at which the parameter resides * \param paramSize - The size of the parameter in the device-side parameter layout * * \return * ::CUDA_SUCCESS, * ::CUDA_ERROR_INVALID_VALUE, * \notefnerr * \note_cudaKernel_t */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaFuncGetParamInfo(const void *func, size_t paramIndex, size_t *paramOffset, size_t *paramSize); /** * \brief Converts a double argument to be executed on a device * * \param d - Double to convert * * \deprecated This function is deprecated as of CUDA 7.5 * * Converts the double value of \p d to an internal float representation if * the device does not support double arithmetic. If the device does natively * support doubles, then this function does nothing. * * \return * ::cudaSuccess * \notefnerr * \note_init_rt * \note_callback * * \sa * \ref ::cudaFuncSetCacheConfig(const void*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C API)", * \ref ::cudaFuncGetAttributes(struct cudaFuncAttributes*, const void*) "cudaFuncGetAttributes (C API)", * ::cudaSetDoubleForHost */ extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaSetDoubleForDevice(double *d); /** * \brief Converts a double argument after execution on a device * * \deprecated This function is deprecated as of CUDA 7.5 * * Converts the double value of \p d from a potentially internal float * representation if the device does not support double arithmetic. If the * device does natively support doubles, then this function does nothing. * * \param d - Double to convert * * \return * ::cudaSuccess * \notefnerr * \note_init_rt * \note_callback * * \sa * \ref ::cudaFuncSetCacheConfig(const void*, enum cudaFuncCache) "cudaFuncSetCacheConfig (C API)", * \ref ::cudaFuncGetAttributes(struct cudaFuncAttributes*, const void*) "cudaFuncGetAttributes (C API)", * ::cudaSetDoubleForDevice */ extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaSetDoubleForHost(double *d); /** * \brief Enqueues a host function call in a stream * * Enqueues a host function to run in a stream. The function will be called * after currently enqueued work and will block work added after it. * * The host function must not make any CUDA API calls. Attempting to use a * CUDA API may result in ::cudaErrorNotPermitted, but this is not required. * The host function must not perform any synchronization that may depend on * outstanding CUDA work not mandated to run earlier. Host functions without a * mandated order (such as in independent streams) execute in undefined order * and may be serialized. * * For the purposes of Unified Memory, execution makes a number of guarantees: *
    *
  • The stream is considered idle for the duration of the function's * execution. Thus, for example, the function may always use memory attached * to the stream it was enqueued in.
    • *
  • The start of execution of the function has the same effect as * synchronizing an event recorded in the same stream immediately prior to * the function. It thus synchronizes streams which have been "joined" * prior to the function.
    • *
  • Adding device work to any stream does not have the effect of making * the stream active until all preceding host functions and stream callbacks * have executed. Thus, for * example, a function might use global attached memory even if work has * been added to another stream, if the work has been ordered behind the * function call with an event.
    • *
  • Completion of the function does not cause a stream to become * active except as described above. The stream will remain idle * if no device work follows the function, and will remain idle across * consecutive host functions or stream callbacks without device work in * between. Thus, for example, * stream synchronization can be done by signaling from a host function at the * end of the stream.
    • *
* * Note that, in constrast to ::cuStreamAddCallback, the function will not be * called in the event of an error in the CUDA context. * * \param hStream - Stream to enqueue function call in * \param fn - The function to call once preceding stream operations are complete * \param userData - User-specified data to be passed to the function * * \return * ::cudaSuccess, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorInvalidValue, * ::cudaErrorNotSupported * \note_null_stream * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaStreamCreate, * ::cudaStreamQuery, * ::cudaStreamSynchronize, * ::cudaStreamWaitEvent, * ::cudaStreamDestroy, * ::cudaMallocManaged, * ::cudaStreamAttachMemAsync, * ::cudaStreamAddCallback, * ::cuLaunchHostFunc */ extern __host__ cudaError_t CUDARTAPI cudaLaunchHostFunc(cudaStream_t stream, cudaHostFn_t fn, void *userData); /** @} */ /* END CUDART_EXECUTION */ /** * \defgroup CUDART_EXECUTION_DEPRECATED Execution Control [DEPRECATED] * * ___MANBRIEF___ deprecated execution control functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the deprecated execution control functions of the CUDA runtime * application programming interface. * * Some functions have overloaded C++ API template versions documented separately in the * \ref CUDART_HIGHLEVEL "C++ API Routines" module. * * @{ */ /** * \brief Sets the shared memory configuration for a device function * * \deprecated * * On devices with configurable shared memory banks, this function will * force all subsequent launches of the specified device function to have * the given shared memory bank size configuration. On any given launch of the * function, the shared memory configuration of the device will be temporarily * changed if needed to suit the function's preferred configuration. Changes in * shared memory configuration between subsequent launches of functions, * may introduce a device side synchronization point. * * Any per-function setting of shared memory bank size set via * ::cudaFuncSetSharedMemConfig will override the device wide setting set by * ::cudaDeviceSetSharedMemConfig. * * Changing the shared memory bank size will not increase shared memory usage * or affect occupancy of kernels, but may have major effects on performance. * Larger bank sizes will allow for greater potential bandwidth to shared memory, * but will change what kinds of accesses to shared memory will result in bank * conflicts. * * This function will do nothing on devices with fixed shared memory bank size. * * For templated functions, pass the function symbol as follows: * func_name * * The supported bank configurations are: * - ::cudaSharedMemBankSizeDefault: use the device's shared memory configuration * when launching this function. * - ::cudaSharedMemBankSizeFourByte: set shared memory bank width to be * four bytes natively when launching this function. * - ::cudaSharedMemBankSizeEightByte: set shared memory bank width to be eight * bytes natively when launching this function. * * \param func - Device function symbol * \param config - Requested shared memory configuration * * \return * ::cudaSuccess, * ::cudaErrorInvalidDeviceFunction, * ::cudaErrorInvalidValue, * \notefnerr * \note_string_api_deprecation2 * \note_init_rt * \note_callback * * \sa ::cudaDeviceSetSharedMemConfig, * ::cudaDeviceGetSharedMemConfig, * ::cudaDeviceSetCacheConfig, * ::cudaDeviceGetCacheConfig, * ::cudaFuncSetCacheConfig, * ::cuFuncSetSharedMemConfig */ extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaFuncSetSharedMemConfig(const void *func, enum cudaSharedMemConfig config); /** @} */ /* END CUDART_EXECUTION_DEPRECATED */ /** * \defgroup CUDART_OCCUPANCY Occupancy * * ___MANBRIEF___ occupancy calculation functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the occupancy calculation functions of the CUDA runtime * application programming interface. * * Besides the occupancy calculator functions * (\ref ::cudaOccupancyMaxActiveBlocksPerMultiprocessor and \ref ::cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlags), * there are also C++ only occupancy-based launch configuration functions documented in * \ref CUDART_HIGHLEVEL "C++ API Routines" module. * * See * \ref ::cudaOccupancyMaxPotentialBlockSize(int*, int*, T, size_t, int) "cudaOccupancyMaxPotentialBlockSize (C++ API)", * \ref ::cudaOccupancyMaxPotentialBlockSizeWithFlags(int*, int*, T, size_t, int, unsigned int) "cudaOccupancyMaxPotentialBlockSize (C++ API)", * \ref ::cudaOccupancyMaxPotentialBlockSizeVariableSMem(int*, int*, T, UnaryFunction, int) "cudaOccupancyMaxPotentialBlockSizeVariableSMem (C++ API)", * \ref ::cudaOccupancyMaxPotentialBlockSizeVariableSMemWithFlags(int*, int*, T, UnaryFunction, int, unsigned int) "cudaOccupancyMaxPotentialBlockSizeVariableSMem (C++ API)" * \ref ::cudaOccupancyAvailableDynamicSMemPerBlock(size_t*, T, int, int) "cudaOccupancyAvailableDynamicSMemPerBlock (C++ API)", * * @{ */ /** * \brief Returns occupancy for a device function * * Returns in \p *numBlocks the maximum number of active blocks per * streaming multiprocessor for the device function. * * \param numBlocks - Returned occupancy * \param func - Kernel function for which occupancy is calculated * \param blockSize - Block size the kernel is intended to be launched with * \param dynamicSMemSize - Per-block dynamic shared memory usage intended, in bytes * * \return * ::cudaSuccess, * ::cudaErrorInvalidDevice, * ::cudaErrorInvalidDeviceFunction, * ::cudaErrorInvalidValue, * ::cudaErrorUnknown, * \notefnerr * \note_init_rt * \note_callback * \note_cudaKernel_t * * \sa ::cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlags, * \ref ::cudaOccupancyMaxPotentialBlockSize(int*, int*, T, size_t, int) "cudaOccupancyMaxPotentialBlockSize (C++ API)", * \ref ::cudaOccupancyMaxPotentialBlockSizeWithFlags(int*, int*, T, size_t, int, unsigned int) "cudaOccupancyMaxPotentialBlockSizeWithFlags (C++ API)", * \ref ::cudaOccupancyMaxPotentialBlockSizeVariableSMem(int*, int*, T, UnaryFunction, int) "cudaOccupancyMaxPotentialBlockSizeVariableSMem (C++ API)", * \ref ::cudaOccupancyMaxPotentialBlockSizeVariableSMemWithFlags(int*, int*, T, UnaryFunction, int, unsigned int) "cudaOccupancyMaxPotentialBlockSizeVariableSMemWithFlags (C++ API)", * \ref ::cudaOccupancyAvailableDynamicSMemPerBlock(size_t*, T, int, int) "cudaOccupancyAvailableDynamicSMemPerBlock (C++ API)", * ::cuOccupancyMaxActiveBlocksPerMultiprocessor */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaOccupancyMaxActiveBlocksPerMultiprocessor(int *numBlocks, const void *func, int blockSize, size_t dynamicSMemSize); /** * \brief Returns dynamic shared memory available per block when launching \p numBlocks blocks on SM. * * Returns in \p *dynamicSmemSize the maximum size of dynamic shared memory to allow \p numBlocks blocks per SM. * * \param dynamicSmemSize - Returned maximum dynamic shared memory * \param func - Kernel function for which occupancy is calculated * \param numBlocks - Number of blocks to fit on SM * \param blockSize - Size of the block * * \return * ::cudaSuccess, * ::cudaErrorInvalidDevice, * ::cudaErrorInvalidDeviceFunction, * ::cudaErrorInvalidValue, * ::cudaErrorUnknown, * \notefnerr * \note_init_rt * \note_callback * \note_cudaKernel_t * * \sa ::cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlags, * \ref ::cudaOccupancyMaxPotentialBlockSize(int*, int*, T, size_t, int) "cudaOccupancyMaxPotentialBlockSize (C++ API)", * \ref ::cudaOccupancyMaxPotentialBlockSizeWithFlags(int*, int*, T, size_t, int, unsigned int) "cudaOccupancyMaxPotentialBlockSizeWithFlags (C++ API)", * \ref ::cudaOccupancyMaxPotentialBlockSizeVariableSMem(int*, int*, T, UnaryFunction, int) "cudaOccupancyMaxPotentialBlockSizeVariableSMem (C++ API)", * \ref ::cudaOccupancyMaxPotentialBlockSizeVariableSMemWithFlags(int*, int*, T, UnaryFunction, int, unsigned int) "cudaOccupancyMaxPotentialBlockSizeVariableSMemWithFlags (C++ API)", * ::cudaOccupancyAvailableDynamicSMemPerBlock */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaOccupancyAvailableDynamicSMemPerBlock(size_t *dynamicSmemSize, const void *func, int numBlocks, int blockSize); /** * \brief Returns occupancy for a device function with the specified flags * * Returns in \p *numBlocks the maximum number of active blocks per * streaming multiprocessor for the device function. * * The \p flags parameter controls how special cases are handled. Valid flags include: * * - ::cudaOccupancyDefault: keeps the default behavior as * ::cudaOccupancyMaxActiveBlocksPerMultiprocessor * * - ::cudaOccupancyDisableCachingOverride: This flag suppresses the default behavior * on platform where global caching affects occupancy. On such platforms, if caching * is enabled, but per-block SM resource usage would result in zero occupancy, the * occupancy calculator will calculate the occupancy as if caching is disabled. * Setting this flag makes the occupancy calculator to return 0 in such cases. * More information can be found about this feature in the "Unified L1/Texture Cache" * section of the Maxwell tuning guide. * * \param numBlocks - Returned occupancy * \param func - Kernel function for which occupancy is calculated * \param blockSize - Block size the kernel is intended to be launched with * \param dynamicSMemSize - Per-block dynamic shared memory usage intended, in bytes * \param flags - Requested behavior for the occupancy calculator * * \return * ::cudaSuccess, * ::cudaErrorInvalidDevice, * ::cudaErrorInvalidDeviceFunction, * ::cudaErrorInvalidValue, * ::cudaErrorUnknown, * \notefnerr * \note_init_rt * \note_callback * \note_cudaKernel_t * * \sa ::cudaOccupancyMaxActiveBlocksPerMultiprocessor, * \ref ::cudaOccupancyMaxPotentialBlockSize(int*, int*, T, size_t, int) "cudaOccupancyMaxPotentialBlockSize (C++ API)", * \ref ::cudaOccupancyMaxPotentialBlockSizeWithFlags(int*, int*, T, size_t, int, unsigned int) "cudaOccupancyMaxPotentialBlockSizeWithFlags (C++ API)", * \ref ::cudaOccupancyMaxPotentialBlockSizeVariableSMem(int*, int*, T, UnaryFunction, int) "cudaOccupancyMaxPotentialBlockSizeVariableSMem (C++ API)", * \ref ::cudaOccupancyMaxPotentialBlockSizeVariableSMemWithFlags(int*, int*, T, UnaryFunction, int, unsigned int) "cudaOccupancyMaxPotentialBlockSizeVariableSMemWithFlags (C++ API)", * \ref ::cudaOccupancyAvailableDynamicSMemPerBlock(size_t*, T, int, int) "cudaOccupancyAvailableDynamicSMemPerBlock (C++ API)", * ::cuOccupancyMaxActiveBlocksPerMultiprocessorWithFlags */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaOccupancyMaxActiveBlocksPerMultiprocessorWithFlags(int *numBlocks, const void *func, int blockSize, size_t dynamicSMemSize, unsigned int flags); /** * \brief Given the kernel function (\p func) and launch configuration * (\p config), return the maximum cluster size in \p *clusterSize. * * The cluster dimensions in \p config are ignored. If func has a required * cluster size set (see ::cudaFuncGetAttributes),\p *clusterSize will reflect * the required cluster size. * * By default this function will always return a value that's portable on * future hardware. A higher value may be returned if the kernel function * allows non-portable cluster sizes. * * This function will respect the compile time launch bounds. * * \param clusterSize - Returned maximum cluster size that can be launched * for the given kernel function and launch configuration * \param func - Kernel function for which maximum cluster * size is calculated * \param config - Launch configuration for the given kernel function * * \return * ::cudaSuccess, * ::cudaErrorInvalidDeviceFunction, * ::cudaErrorInvalidValue, * ::cudaErrorUnknown, * \notefnerr * \note_init_rt * \note_callback * \note_cudaKernel_t * * \sa ::cudaFuncGetAttributes * \ref ::cudaOccupancyMaxPotentialClusterSize(int*, T, const cudaLaunchConfig_t*) "cudaOccupancyMaxPotentialClusterSize (C++ API)", * ::cuOccupancyMaxPotentialClusterSize */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaOccupancyMaxPotentialClusterSize(int *clusterSize, const void *func, const cudaLaunchConfig_t *launchConfig); /** * \brief Given the kernel function (\p func) and launch configuration * (\p config), return the maximum number of clusters that could co-exist * on the target device in \p *numClusters. * * If the function has required cluster size already set (see * ::cudaFuncGetAttributes), the cluster size from config must either be * unspecified or match the required size. * Without required sizes, the cluster size must be specified in config, * else the function will return an error. * * Note that various attributes of the kernel function may affect occupancy * calculation. Runtime environment may affect how the hardware schedules * the clusters, so the calculated occupancy is not guaranteed to be achievable. * * \param numClusters - Returned maximum number of clusters that * could co-exist on the target device * \param func - Kernel function for which maximum number * of clusters are calculated * \param config - Launch configuration for the given kernel function * * \return * ::cudaSuccess, * ::cudaErrorInvalidDeviceFunction, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidClusterSize, * ::cudaErrorUnknown, * \notefnerr * \note_init_rt * \note_callback * \note_cudaKernel_t * * \sa * ::cudaFuncGetAttributes * \ref ::cudaOccupancyMaxActiveClusters(int*, T, const cudaLaunchConfig_t*) "cudaOccupancyMaxActiveClusters (C++ API)", * ::cuOccupancyMaxActiveClusters */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaOccupancyMaxActiveClusters(int *numClusters, const void *func, const cudaLaunchConfig_t *launchConfig); /** @} */ /* END CUDA_OCCUPANCY */ /** * \defgroup CUDART_MEMORY Memory Management * * ___MANBRIEF___ memory management functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the memory management functions of the CUDA runtime * application programming interface. * * Some functions have overloaded C++ API template versions documented separately in the * \ref CUDART_HIGHLEVEL "C++ API Routines" module. * * @{ */ /** * \brief Allocates memory that will be automatically managed by the Unified Memory system * * Allocates \p size bytes of managed memory on the device and returns in * \p *devPtr a pointer to the allocated memory. If the device doesn't support * allocating managed memory, ::cudaErrorNotSupported is returned. Support * for managed memory can be queried using the device attribute * ::cudaDevAttrManagedMemory. The allocated memory is suitably * aligned for any kind of variable. The memory is not cleared. If \p size * is 0, ::cudaMallocManaged returns ::cudaErrorInvalidValue. The pointer * is valid on the CPU and on all GPUs in the system that support managed memory. * All accesses to this pointer must obey the Unified Memory programming model. * * \p flags specifies the default stream association for this allocation. * \p flags must be one of ::cudaMemAttachGlobal or ::cudaMemAttachHost. The * default value for \p flags is ::cudaMemAttachGlobal. * If ::cudaMemAttachGlobal is specified, then this memory is accessible from * any stream on any device. If ::cudaMemAttachHost is specified, then the * allocation should not be accessed from devices that have a zero value for the * device attribute ::cudaDevAttrConcurrentManagedAccess; an explicit call to * ::cudaStreamAttachMemAsync will be required to enable access on such devices. * * If the association is later changed via ::cudaStreamAttachMemAsync to * a single stream, the default association, as specifed during ::cudaMallocManaged, * is restored when that stream is destroyed. For __managed__ variables, the * default association is always ::cudaMemAttachGlobal. Note that destroying a * stream is an asynchronous operation, and as a result, the change to default * association won't happen until all work in the stream has completed. * * Memory allocated with ::cudaMallocManaged should be released with ::cudaFree. * * Device memory oversubscription is possible for GPUs that have a non-zero value for the * device attribute ::cudaDevAttrConcurrentManagedAccess. Managed memory on * such GPUs may be evicted from device memory to host memory at any time by the Unified * Memory driver in order to make room for other allocations. * * In a system where all GPUs have a non-zero value for the device attribute * ::cudaDevAttrConcurrentManagedAccess, managed memory may not be populated when this * API returns and instead may be populated on access. In such systems, managed memory can * migrate to any processor's memory at any time. The Unified Memory driver will employ heuristics to * maintain data locality and prevent excessive page faults to the extent possible. The application * can also guide the driver about memory usage patterns via ::cudaMemAdvise. The application * can also explicitly migrate memory to a desired processor's memory via * ::cudaMemPrefetchAsync. * * In a multi-GPU system where all of the GPUs have a zero value for the device attribute * ::cudaDevAttrConcurrentManagedAccess and all the GPUs have peer-to-peer support * with each other, the physical storage for managed memory is created on the GPU which is active * at the time ::cudaMallocManaged is called. All other GPUs will reference the data at reduced * bandwidth via peer mappings over the PCIe bus. The Unified Memory driver does not migrate * memory among such GPUs. * * In a multi-GPU system where not all GPUs have peer-to-peer support with each other and * where the value of the device attribute ::cudaDevAttrConcurrentManagedAccess * is zero for at least one of those GPUs, the location chosen for physical storage of managed * memory is system-dependent. * - On Linux, the location chosen will be device memory as long as the current set of active * contexts are on devices that either have peer-to-peer support with each other or have a * non-zero value for the device attribute ::cudaDevAttrConcurrentManagedAccess. * If there is an active context on a GPU that does not have a non-zero value for that device * attribute and it does not have peer-to-peer support with the other devices that have active * contexts on them, then the location for physical storage will be 'zero-copy' or host memory. * Note that this means that managed memory that is located in device memory is migrated to * host memory if a new context is created on a GPU that doesn't have a non-zero value for * the device attribute and does not support peer-to-peer with at least one of the other devices * that has an active context. This in turn implies that context creation may fail if there is * insufficient host memory to migrate all managed allocations. * - On Windows, the physical storage is always created in 'zero-copy' or host memory. * All GPUs will reference the data at reduced bandwidth over the PCIe bus. In these * circumstances, use of the environment variable CUDA_VISIBLE_DEVICES is recommended to * restrict CUDA to only use those GPUs that have peer-to-peer support. * Alternatively, users can also set CUDA_MANAGED_FORCE_DEVICE_ALLOC to a non-zero * value to force the driver to always use device memory for physical storage. * When this environment variable is set to a non-zero value, all devices used in * that process that support managed memory have to be peer-to-peer compatible * with each other. The error ::cudaErrorInvalidDevice will be returned if a device * that supports managed memory is used and it is not peer-to-peer compatible with * any of the other managed memory supporting devices that were previously used in * that process, even if ::cudaDeviceReset has been called on those devices. These * environment variables are described in the CUDA programming guide under the * "CUDA environment variables" section. * * \param devPtr - Pointer to allocated device memory * \param size - Requested allocation size in bytes * \param flags - Must be either ::cudaMemAttachGlobal or ::cudaMemAttachHost (defaults to ::cudaMemAttachGlobal) * * \return * ::cudaSuccess, * ::cudaErrorMemoryAllocation, * ::cudaErrorNotSupported, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaMallocPitch, ::cudaFree, ::cudaMallocArray, ::cudaFreeArray, * ::cudaMalloc3D, ::cudaMalloc3DArray, * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)", * ::cudaFreeHost, ::cudaHostAlloc, ::cudaDeviceGetAttribute, ::cudaStreamAttachMemAsync, * ::cuMemAllocManaged */ #if defined(__cplusplus) extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMallocManaged(void **devPtr, size_t size, unsigned int flags = cudaMemAttachGlobal); #else extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMallocManaged(void **devPtr, size_t size, unsigned int flags); #endif /** * \brief Allocate memory on the device * * Allocates \p size bytes of linear memory on the device and returns in * \p *devPtr a pointer to the allocated memory. The allocated memory is * suitably aligned for any kind of variable. The memory is not cleared. * ::cudaMalloc() returns ::cudaErrorMemoryAllocation in case of failure. * * The device version of ::cudaFree cannot be used with a \p *devPtr * allocated using the host API, and vice versa. * * \param devPtr - Pointer to allocated device memory * \param size - Requested allocation size in bytes * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorMemoryAllocation * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaMallocPitch, ::cudaFree, ::cudaMallocArray, ::cudaFreeArray, * ::cudaMalloc3D, ::cudaMalloc3DArray, * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)", * ::cudaFreeHost, ::cudaHostAlloc, * ::cuMemAlloc */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMalloc(void **devPtr, size_t size); /** * \brief Allocates page-locked memory on the host * * Allocates \p size bytes of host memory that is page-locked and accessible * to the device. The driver tracks the virtual memory ranges allocated with * this function and automatically accelerates calls to functions such as * ::cudaMemcpy*(). Since the memory can be accessed directly by the device, * it can be read or written with much higher bandwidth than pageable memory * obtained with functions such as ::malloc(). * On systems where ::pageableMemoryAccessUsesHostPageTables * is true, ::cudaMallocHost may not page-lock the allocated memory. * Page-locking excessive amounts of memory with ::cudaMallocHost() may degrade * system performance, since it reduces the amount of memory available to the * system for paging. As a result, this function is best used sparingly to allocate * staging areas for data exchange between host and device. * * \param ptr - Pointer to allocated host memory * \param size - Requested allocation size in bytes * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorMemoryAllocation * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaMalloc, ::cudaMallocPitch, ::cudaMallocArray, ::cudaMalloc3D, * ::cudaMalloc3DArray, ::cudaHostAlloc, ::cudaFree, ::cudaFreeArray, * \ref ::cudaMallocHost(void**, size_t, unsigned int) "cudaMallocHost (C++ API)", * ::cudaFreeHost, ::cudaHostAlloc, * ::cuMemAllocHost */ extern __host__ cudaError_t CUDARTAPI cudaMallocHost(void **ptr, size_t size); /** * \brief Allocates pitched memory on the device * * Allocates at least \p width (in bytes) * \p height bytes of linear memory * on the device and returns in \p *devPtr a pointer to the allocated memory. * The function may pad the allocation to ensure that corresponding pointers * in any given row will continue to meet the alignment requirements for * coalescing as the address is updated from row to row. The pitch returned in * \p *pitch by ::cudaMallocPitch() is the width in bytes of the allocation. * The intended usage of \p pitch is as a separate parameter of the allocation, * used to compute addresses within the 2D array. Given the row and column of * an array element of type \p T, the address is computed as: * \code T* pElement = (T*)((char*)BaseAddress + Row * pitch) + Column; \endcode * * For allocations of 2D arrays, it is recommended that programmers consider * performing pitch allocations using ::cudaMallocPitch(). Due to pitch * alignment restrictions in the hardware, this is especially true if the * application will be performing 2D memory copies between different regions * of device memory (whether linear memory or CUDA arrays). * * \param devPtr - Pointer to allocated pitched device memory * \param pitch - Pitch for allocation * \param width - Requested pitched allocation width (in bytes) * \param height - Requested pitched allocation height * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorMemoryAllocation * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaMalloc, ::cudaFree, ::cudaMallocArray, ::cudaFreeArray, * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)", * ::cudaFreeHost, ::cudaMalloc3D, ::cudaMalloc3DArray, * ::cudaHostAlloc, * ::cuMemAllocPitch */ extern __host__ cudaError_t CUDARTAPI cudaMallocPitch(void **devPtr, size_t *pitch, size_t width, size_t height); /** * \brief Allocate an array on the device * * Allocates a CUDA array according to the ::cudaChannelFormatDesc structure * \p desc and returns a handle to the new CUDA array in \p *array. * * The ::cudaChannelFormatDesc is defined as: * \code struct cudaChannelFormatDesc { int x, y, z, w; enum cudaChannelFormatKind f; }; \endcode * where ::cudaChannelFormatKind is one of ::cudaChannelFormatKindSigned, * ::cudaChannelFormatKindUnsigned, or ::cudaChannelFormatKindFloat. * * The \p flags parameter enables different options to be specified that affect * the allocation, as follows. * - ::cudaArrayDefault: This flag's value is defined to be 0 and provides default array allocation * - ::cudaArraySurfaceLoadStore: Allocates an array that can be read from or written to using a surface reference * - ::cudaArrayTextureGather: This flag indicates that texture gather operations will be performed on the array. * - ::cudaArraySparse: Allocates a CUDA array without physical backing memory. The subregions within this sparse array * can later be mapped onto a physical memory allocation by calling ::cuMemMapArrayAsync. * The physical backing memory must be allocated via ::cuMemCreate. * - ::cudaArrayDeferredMapping: Allocates a CUDA array without physical backing memory. The entire array can * later be mapped onto a physical memory allocation by calling ::cuMemMapArrayAsync. * The physical backing memory must be allocated via ::cuMemCreate. * * \p width and \p height must meet certain size requirements. See ::cudaMalloc3DArray() for more details. * * \param array - Pointer to allocated array in device memory * \param desc - Requested channel format * \param width - Requested array allocation width * \param height - Requested array allocation height * \param flags - Requested properties of allocated array * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorMemoryAllocation * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaMalloc, ::cudaMallocPitch, ::cudaFree, ::cudaFreeArray, * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)", * ::cudaFreeHost, ::cudaMalloc3D, ::cudaMalloc3DArray, * ::cudaHostAlloc, * ::cuArrayCreate */ extern __host__ cudaError_t CUDARTAPI cudaMallocArray(cudaArray_t *array, const struct cudaChannelFormatDesc *desc, size_t width, size_t height __dv(0), unsigned int flags __dv(0)); /** * \brief Frees memory on the device * * Frees the memory space pointed to by \p devPtr, which must have been * returned by a previous call to one of the following memory allocation APIs - * ::cudaMalloc(), ::cudaMallocPitch(), ::cudaMallocManaged(), ::cudaMallocAsync(), * ::cudaMallocFromPoolAsync(). * * Note - This API will not perform any implicit synchronization when the pointer was * allocated with ::cudaMallocAsync or ::cudaMallocFromPoolAsync. Callers must ensure * that all accesses to these pointer have completed before invoking ::cudaFree. For * best performance and memory reuse, users should use ::cudaFreeAsync to free memory * allocated via the stream ordered memory allocator. * For all other pointers, this API may perform implicit synchronization. * * If ::cudaFree(\p devPtr) has already been called before, * an error is returned. If \p devPtr is 0, no operation is performed. * ::cudaFree() returns ::cudaErrorValue in case of failure. * * The device version of ::cudaFree cannot be used with a \p *devPtr * allocated using the host API, and vice versa. * * \param devPtr - Device pointer to memory to free * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaMalloc, ::cudaMallocPitch, ::cudaMallocManaged, ::cudaMallocArray, ::cudaFreeArray, ::cudaMallocAsync, ::cudaMallocFromPoolAsync * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)", * ::cudaFreeHost, ::cudaMalloc3D, ::cudaMalloc3DArray, ::cudaFreeAsync * ::cudaHostAlloc, * ::cuMemFree */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaFree(void *devPtr); /** * \brief Frees page-locked memory * * Frees the memory space pointed to by \p hostPtr, which must have been * returned by a previous call to ::cudaMallocHost() or ::cudaHostAlloc(). * * \param ptr - Pointer to memory to free * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaMalloc, ::cudaMallocPitch, ::cudaFree, ::cudaMallocArray, * ::cudaFreeArray, * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)", * ::cudaMalloc3D, ::cudaMalloc3DArray, ::cudaHostAlloc, * ::cuMemFreeHost */ extern __host__ cudaError_t CUDARTAPI cudaFreeHost(void *ptr); /** * \brief Frees an array on the device * * Frees the CUDA array \p array, which must have been returned by a * previous call to ::cudaMallocArray(). If \p devPtr is 0, * no operation is performed. * * \param array - Pointer to array to free * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaMalloc, ::cudaMallocPitch, ::cudaFree, ::cudaMallocArray, * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)", * ::cudaFreeHost, ::cudaHostAlloc, * ::cuArrayDestroy */ extern __host__ cudaError_t CUDARTAPI cudaFreeArray(cudaArray_t array); /** * \brief Frees a mipmapped array on the device * * Frees the CUDA mipmapped array \p mipmappedArray, which must have been * returned by a previous call to ::cudaMallocMipmappedArray(). If \p devPtr * is 0, no operation is performed. * * \param mipmappedArray - Pointer to mipmapped array to free * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaMalloc, ::cudaMallocPitch, ::cudaFree, ::cudaMallocArray, * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)", * ::cudaFreeHost, ::cudaHostAlloc, * ::cuMipmappedArrayDestroy */ extern __host__ cudaError_t CUDARTAPI cudaFreeMipmappedArray(cudaMipmappedArray_t mipmappedArray); /** * \brief Allocates page-locked memory on the host * * Allocates \p size bytes of host memory that is page-locked and accessible * to the device. The driver tracks the virtual memory ranges allocated with * this function and automatically accelerates calls to functions such as * ::cudaMemcpy(). Since the memory can be accessed directly by the device, it * can be read or written with much higher bandwidth than pageable memory * obtained with functions such as ::malloc(). Allocating excessive amounts of * pinned memory may degrade system performance, since it reduces the amount * of memory available to the system for paging. As a result, this function is * best used sparingly to allocate staging areas for data exchange between host * and device. * * The \p flags parameter enables different options to be specified that affect * the allocation, as follows. * - ::cudaHostAllocDefault: This flag's value is defined to be 0 and causes * ::cudaHostAlloc() to emulate ::cudaMallocHost(). * - ::cudaHostAllocPortable: The memory returned by this call will be * considered as pinned memory by all CUDA contexts, not just the one that * performed the allocation. * - ::cudaHostAllocMapped: Maps the allocation into the CUDA address space. * The device pointer to the memory may be obtained by calling * ::cudaHostGetDevicePointer(). * - ::cudaHostAllocWriteCombined: Allocates the memory as write-combined (WC). * WC memory can be transferred across the PCI Express bus more quickly on some * system configurations, but cannot be read efficiently by most CPUs. WC * memory is a good option for buffers that will be written by the CPU and read * by the device via mapped pinned memory or host->device transfers. * * All of these flags are orthogonal to one another: a developer may allocate * memory that is portable, mapped and/or write-combined with no restrictions. * * In order for the ::cudaHostAllocMapped flag to have any effect, the CUDA context * must support the ::cudaDeviceMapHost flag, which can be checked via * ::cudaGetDeviceFlags(). The ::cudaDeviceMapHost flag is implicitly set for * contexts created via the runtime API. * * The ::cudaHostAllocMapped flag may be specified on CUDA contexts for devices * that do not support mapped pinned memory. The failure is deferred to * ::cudaHostGetDevicePointer() because the memory may be mapped into other * CUDA contexts via the ::cudaHostAllocPortable flag. * * Memory allocated by this function must be freed with ::cudaFreeHost(). * * \param pHost - Device pointer to allocated memory * \param size - Requested allocation size in bytes * \param flags - Requested properties of allocated memory * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorMemoryAllocation * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaSetDeviceFlags, * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)", * ::cudaFreeHost, * ::cudaGetDeviceFlags, * ::cuMemHostAlloc */ extern __host__ cudaError_t CUDARTAPI cudaHostAlloc(void **pHost, size_t size, unsigned int flags); /** * \brief Registers an existing host memory range for use by CUDA * * Page-locks the memory range specified by \p ptr and \p size and maps it * for the device(s) as specified by \p flags. This memory range also is added * to the same tracking mechanism as ::cudaHostAlloc() to automatically accelerate * calls to functions such as ::cudaMemcpy(). Since the memory can be accessed * directly by the device, it can be read or written with much higher bandwidth * than pageable memory that has not been registered. Page-locking excessive * amounts of memory may degrade system performance, since it reduces the amount * of memory available to the system for paging. As a result, this function is * best used sparingly to register staging areas for data exchange between * host and device. * * On systems where ::pageableMemoryAccessUsesHostPageTables is true, ::cudaHostRegister * will not page-lock the memory range specified by \p ptr but only populate * unpopulated pages. * * ::cudaHostRegister is supported only on I/O coherent devices that have a non-zero * value for the device attribute ::cudaDevAttrHostRegisterSupported. * * The \p flags parameter enables different options to be specified that * affect the allocation, as follows. * * - ::cudaHostRegisterDefault: On a system with unified virtual addressing, * the memory will be both mapped and portable. On a system with no unified * virtual addressing, the memory will be neither mapped nor portable. * * - ::cudaHostRegisterPortable: The memory returned by this call will be * considered as pinned memory by all CUDA contexts, not just the one that * performed the allocation. * * - ::cudaHostRegisterMapped: Maps the allocation into the CUDA address * space. The device pointer to the memory may be obtained by calling * ::cudaHostGetDevicePointer(). * * - ::cudaHostRegisterIoMemory: The passed memory pointer is treated as * pointing to some memory-mapped I/O space, e.g. belonging to a * third-party PCIe device, and it will marked as non cache-coherent and * contiguous. * * - ::cudaHostRegisterReadOnly: The passed memory pointer is treated as * pointing to memory that is considered read-only by the device. On * platforms without ::cudaDevAttrPageableMemoryAccessUsesHostPageTables, this * flag is required in order to register memory mapped to the CPU as * read-only. Support for the use of this flag can be queried from the device * attribute ::cudaDevAttrHostRegisterReadOnlySupported. Using this flag with * a current context associated with a device that does not have this attribute * set will cause ::cudaHostRegister to error with cudaErrorNotSupported. * * All of these flags are orthogonal to one another: a developer may page-lock * memory that is portable or mapped with no restrictions. * * The CUDA context must have been created with the ::cudaMapHost flag in * order for the ::cudaHostRegisterMapped flag to have any effect. * * The ::cudaHostRegisterMapped flag may be specified on CUDA contexts for * devices that do not support mapped pinned memory. The failure is deferred * to ::cudaHostGetDevicePointer() because the memory may be mapped into * other CUDA contexts via the ::cudaHostRegisterPortable flag. * * For devices that have a non-zero value for the device attribute * ::cudaDevAttrCanUseHostPointerForRegisteredMem, the memory * can also be accessed from the device using the host pointer \p ptr. * The device pointer returned by ::cudaHostGetDevicePointer() may or may not * match the original host pointer \p ptr and depends on the devices visible to the * application. If all devices visible to the application have a non-zero value for the * device attribute, the device pointer returned by ::cudaHostGetDevicePointer() * will match the original pointer \p ptr. If any device visible to the application * has a zero value for the device attribute, the device pointer returned by * ::cudaHostGetDevicePointer() will not match the original host pointer \p ptr, * but it will be suitable for use on all devices provided Unified Virtual Addressing * is enabled. In such systems, it is valid to access the memory using either pointer * on devices that have a non-zero value for the device attribute. Note however that * such devices should access the memory using only of the two pointers and not both. * * The memory page-locked by this function must be unregistered with ::cudaHostUnregister(). * * \param ptr - Host pointer to memory to page-lock * \param size - Size in bytes of the address range to page-lock in bytes * \param flags - Flags for allocation request * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorMemoryAllocation, * ::cudaErrorHostMemoryAlreadyRegistered, * ::cudaErrorNotSupported * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaHostUnregister, ::cudaHostGetFlags, ::cudaHostGetDevicePointer, * ::cuMemHostRegister */ extern __host__ cudaError_t CUDARTAPI cudaHostRegister(void *ptr, size_t size, unsigned int flags); /** * \brief Unregisters a memory range that was registered with cudaHostRegister * * Unmaps the memory range whose base address is specified by \p ptr, and makes * it pageable again. * * The base address must be the same one specified to ::cudaHostRegister(). * * \param ptr - Host pointer to memory to unregister * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorHostMemoryNotRegistered * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaHostUnregister, * ::cuMemHostUnregister */ extern __host__ cudaError_t CUDARTAPI cudaHostUnregister(void *ptr); /** * \brief Passes back device pointer of mapped host memory allocated by * cudaHostAlloc or registered by cudaHostRegister * * Passes back the device pointer corresponding to the mapped, pinned host * buffer allocated by ::cudaHostAlloc() or registered by ::cudaHostRegister(). * * ::cudaHostGetDevicePointer() will fail if the ::cudaDeviceMapHost flag was * not specified before deferred context creation occurred, or if called on a * device that does not support mapped, pinned memory. * * For devices that have a non-zero value for the device attribute * ::cudaDevAttrCanUseHostPointerForRegisteredMem, the memory * can also be accessed from the device using the host pointer \p pHost. * The device pointer returned by ::cudaHostGetDevicePointer() may or may not * match the original host pointer \p pHost and depends on the devices visible to the * application. If all devices visible to the application have a non-zero value for the * device attribute, the device pointer returned by ::cudaHostGetDevicePointer() * will match the original pointer \p pHost. If any device visible to the application * has a zero value for the device attribute, the device pointer returned by * ::cudaHostGetDevicePointer() will not match the original host pointer \p pHost, * but it will be suitable for use on all devices provided Unified Virtual Addressing * is enabled. In such systems, it is valid to access the memory using either pointer * on devices that have a non-zero value for the device attribute. Note however that * such devices should access the memory using only of the two pointers and not both. * * \p flags provides for future releases. For now, it must be set to 0. * * \param pDevice - Returned device pointer for mapped memory * \param pHost - Requested host pointer mapping * \param flags - Flags for extensions (must be 0 for now) * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorMemoryAllocation * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaSetDeviceFlags, ::cudaHostAlloc, * ::cuMemHostGetDevicePointer */ extern __host__ cudaError_t CUDARTAPI cudaHostGetDevicePointer(void **pDevice, void *pHost, unsigned int flags); /** * \brief Passes back flags used to allocate pinned host memory allocated by * cudaHostAlloc * * ::cudaHostGetFlags() will fail if the input pointer does not * reside in an address range allocated by ::cudaHostAlloc(). * * \param pFlags - Returned flags word * \param pHost - Host pointer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaHostAlloc, * ::cuMemHostGetFlags */ extern __host__ cudaError_t CUDARTAPI cudaHostGetFlags(unsigned int *pFlags, void *pHost); /** * \brief Allocates logical 1D, 2D, or 3D memory objects on the device * * Allocates at least \p width * \p height * \p depth bytes of linear memory * on the device and returns a ::cudaPitchedPtr in which \p ptr is a pointer * to the allocated memory. The function may pad the allocation to ensure * hardware alignment requirements are met. The pitch returned in the \p pitch * field of \p pitchedDevPtr is the width in bytes of the allocation. * * The returned ::cudaPitchedPtr contains additional fields \p xsize and * \p ysize, the logical width and height of the allocation, which are * equivalent to the \p width and \p height \p extent parameters provided by * the programmer during allocation. * * For allocations of 2D and 3D objects, it is highly recommended that * programmers perform allocations using ::cudaMalloc3D() or * ::cudaMallocPitch(). Due to alignment restrictions in the hardware, this is * especially true if the application will be performing memory copies * involving 2D or 3D objects (whether linear memory or CUDA arrays). * * \param pitchedDevPtr - Pointer to allocated pitched device memory * \param extent - Requested allocation size (\p width field in bytes) * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorMemoryAllocation * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaMallocPitch, ::cudaFree, ::cudaMemcpy3D, ::cudaMemset3D, * ::cudaMalloc3DArray, ::cudaMallocArray, ::cudaFreeArray, * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)", * ::cudaFreeHost, ::cudaHostAlloc, ::make_cudaPitchedPtr, ::make_cudaExtent, * ::cuMemAllocPitch */ extern __host__ cudaError_t CUDARTAPI cudaMalloc3D(struct cudaPitchedPtr* pitchedDevPtr, struct cudaExtent extent); /** * \brief Allocate an array on the device * * Allocates a CUDA array according to the ::cudaChannelFormatDesc structure * \p desc and returns a handle to the new CUDA array in \p *array. * * The ::cudaChannelFormatDesc is defined as: * \code struct cudaChannelFormatDesc { int x, y, z, w; enum cudaChannelFormatKind f; }; \endcode * where ::cudaChannelFormatKind is one of ::cudaChannelFormatKindSigned, * ::cudaChannelFormatKindUnsigned, or ::cudaChannelFormatKindFloat. * * ::cudaMalloc3DArray() can allocate the following: * * - A 1D array is allocated if the height and depth extents are both zero. * - A 2D array is allocated if only the depth extent is zero. * - A 3D array is allocated if all three extents are non-zero. * - A 1D layered CUDA array is allocated if only the height extent is zero and * the cudaArrayLayered flag is set. Each layer is a 1D array. The number of layers is * determined by the depth extent. * - A 2D layered CUDA array is allocated if all three extents are non-zero and * the cudaArrayLayered flag is set. Each layer is a 2D array. The number of layers is * determined by the depth extent. * - A cubemap CUDA array is allocated if all three extents are non-zero and the * cudaArrayCubemap flag is set. Width must be equal to height, and depth must be six. A cubemap is * a special type of 2D layered CUDA array, where the six layers represent the six faces of a cube. * The order of the six layers in memory is the same as that listed in ::cudaGraphicsCubeFace. * - A cubemap layered CUDA array is allocated if all three extents are non-zero, and both, * cudaArrayCubemap and cudaArrayLayered flags are set. Width must be equal to height, and depth must be * a multiple of six. A cubemap layered CUDA array is a special type of 2D layered CUDA array that consists * of a collection of cubemaps. The first six layers represent the first cubemap, the next six layers form * the second cubemap, and so on. * * * The \p flags parameter enables different options to be specified that affect * the allocation, as follows. * - ::cudaArrayDefault: This flag's value is defined to be 0 and provides default array allocation * - ::cudaArrayLayered: Allocates a layered CUDA array, with the depth extent indicating the number of layers * - ::cudaArrayCubemap: Allocates a cubemap CUDA array. Width must be equal to height, and depth must be six. * If the cudaArrayLayered flag is also set, depth must be a multiple of six. * - ::cudaArraySurfaceLoadStore: Allocates a CUDA array that could be read from or written to using a surface * reference. * - ::cudaArrayTextureGather: This flag indicates that texture gather operations will be performed on the CUDA * array. Texture gather can only be performed on 2D CUDA arrays. * - ::cudaArraySparse: Allocates a CUDA array without physical backing memory. The subregions within this sparse array * can later be mapped onto a physical memory allocation by calling ::cuMemMapArrayAsync. This flag can only be used for * creating 2D, 3D or 2D layered sparse CUDA arrays. The physical backing memory must be allocated via ::cuMemCreate. * - ::cudaArrayDeferredMapping: Allocates a CUDA array without physical backing memory. The entire array can * later be mapped onto a physical memory allocation by calling ::cuMemMapArrayAsync. The physical backing memory must be allocated * via ::cuMemCreate. * * The width, height and depth extents must meet certain size requirements as listed in the following table. * All values are specified in elements. * * Note that 2D CUDA arrays have different size requirements if the ::cudaArrayTextureGather flag is set. In that * case, the valid range for (width, height, depth) is ((1,maxTexture2DGather[0]), (1,maxTexture2DGather[1]), 0). * * \xmlonly * * * * * * * * CUDA array type * Valid extents that must always be met {(width range in elements), * (height range), (depth range)} * Valid extents with cudaArraySurfaceLoadStore set {(width range in * elements), (height range), (depth range)} * * * * * 1D * { (1,maxTexture1D), 0, 0 } * { (1,maxSurface1D), 0, 0 } * * * 2D * { (1,maxTexture2D[0]), (1,maxTexture2D[1]), 0 } * { (1,maxSurface2D[0]), (1,maxSurface2D[1]), 0 } * * * 3D * { (1,maxTexture3D[0]), (1,maxTexture3D[1]), (1,maxTexture3D[2]) } * OR { (1,maxTexture3DAlt[0]), (1,maxTexture3DAlt[1]), * (1,maxTexture3DAlt[2]) } * { (1,maxSurface3D[0]), (1,maxSurface3D[1]), (1,maxSurface3D[2]) } * * * 1D Layered * { (1,maxTexture1DLayered[0]), 0, (1,maxTexture1DLayered[1]) } * { (1,maxSurface1DLayered[0]), 0, (1,maxSurface1DLayered[1]) } * * * 2D Layered * { (1,maxTexture2DLayered[0]), (1,maxTexture2DLayered[1]), * (1,maxTexture2DLayered[2]) } * { (1,maxSurface2DLayered[0]), (1,maxSurface2DLayered[1]), * (1,maxSurface2DLayered[2]) } * * * Cubemap * { (1,maxTextureCubemap), (1,maxTextureCubemap), 6 } * { (1,maxSurfaceCubemap), (1,maxSurfaceCubemap), 6 } * * * Cubemap Layered * { (1,maxTextureCubemapLayered[0]), (1,maxTextureCubemapLayered[0]), * (1,maxTextureCubemapLayered[1]) } * { (1,maxSurfaceCubemapLayered[0]), (1,maxSurfaceCubemapLayered[0]), * (1,maxSurfaceCubemapLayered[1]) } * * * *
* \endxmlonly * * \param array - Pointer to allocated array in device memory * \param desc - Requested channel format * \param extent - Requested allocation size (\p width field in elements) * \param flags - Flags for extensions * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorMemoryAllocation * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaMalloc3D, ::cudaMalloc, ::cudaMallocPitch, ::cudaFree, * ::cudaFreeArray, * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)", * ::cudaFreeHost, ::cudaHostAlloc, * ::make_cudaExtent, * ::cuArray3DCreate */ extern __host__ cudaError_t CUDARTAPI cudaMalloc3DArray(cudaArray_t *array, const struct cudaChannelFormatDesc* desc, struct cudaExtent extent, unsigned int flags __dv(0)); /** * \brief Allocate a mipmapped array on the device * * Allocates a CUDA mipmapped array according to the ::cudaChannelFormatDesc structure * \p desc and returns a handle to the new CUDA mipmapped array in \p *mipmappedArray. * \p numLevels specifies the number of mipmap levels to be allocated. This value is * clamped to the range [1, 1 + floor(log2(max(width, height, depth)))]. * * The ::cudaChannelFormatDesc is defined as: * \code struct cudaChannelFormatDesc { int x, y, z, w; enum cudaChannelFormatKind f; }; \endcode * where ::cudaChannelFormatKind is one of ::cudaChannelFormatKindSigned, * ::cudaChannelFormatKindUnsigned, or ::cudaChannelFormatKindFloat. * * ::cudaMallocMipmappedArray() can allocate the following: * * - A 1D mipmapped array is allocated if the height and depth extents are both zero. * - A 2D mipmapped array is allocated if only the depth extent is zero. * - A 3D mipmapped array is allocated if all three extents are non-zero. * - A 1D layered CUDA mipmapped array is allocated if only the height extent is zero and * the cudaArrayLayered flag is set. Each layer is a 1D mipmapped array. The number of layers is * determined by the depth extent. * - A 2D layered CUDA mipmapped array is allocated if all three extents are non-zero and * the cudaArrayLayered flag is set. Each layer is a 2D mipmapped array. The number of layers is * determined by the depth extent. * - A cubemap CUDA mipmapped array is allocated if all three extents are non-zero and the * cudaArrayCubemap flag is set. Width must be equal to height, and depth must be six. * The order of the six layers in memory is the same as that listed in ::cudaGraphicsCubeFace. * - A cubemap layered CUDA mipmapped array is allocated if all three extents are non-zero, and both, * cudaArrayCubemap and cudaArrayLayered flags are set. Width must be equal to height, and depth must be * a multiple of six. A cubemap layered CUDA mipmapped array is a special type of 2D layered CUDA mipmapped * array that consists of a collection of cubemap mipmapped arrays. The first six layers represent the * first cubemap mipmapped array, the next six layers form the second cubemap mipmapped array, and so on. * * * The \p flags parameter enables different options to be specified that affect * the allocation, as follows. * - ::cudaArrayDefault: This flag's value is defined to be 0 and provides default mipmapped array allocation * - ::cudaArrayLayered: Allocates a layered CUDA mipmapped array, with the depth extent indicating the number of layers * - ::cudaArrayCubemap: Allocates a cubemap CUDA mipmapped array. Width must be equal to height, and depth must be six. * If the cudaArrayLayered flag is also set, depth must be a multiple of six. * - ::cudaArraySurfaceLoadStore: This flag indicates that individual mipmap levels of the CUDA mipmapped array * will be read from or written to using a surface reference. * - ::cudaArrayTextureGather: This flag indicates that texture gather operations will be performed on the CUDA * array. Texture gather can only be performed on 2D CUDA mipmapped arrays, and the gather operations are * performed only on the most detailed mipmap level. * - ::cudaArraySparse: Allocates a CUDA mipmapped array without physical backing memory. The subregions within this sparse array * can later be mapped onto a physical memory allocation by calling ::cuMemMapArrayAsync. This flag can only be used for creating * 2D, 3D or 2D layered sparse CUDA mipmapped arrays. The physical backing memory must be allocated via ::cuMemCreate. * - ::cudaArrayDeferredMapping: Allocates a CUDA mipmapped array without physical backing memory. The entire array can * later be mapped onto a physical memory allocation by calling ::cuMemMapArrayAsync. The physical backing memory must be allocated * via ::cuMemCreate. * * The width, height and depth extents must meet certain size requirements as listed in the following table. * All values are specified in elements. * * \xmlonly * * * * * * * * CUDA array type * Valid extents that must always be met {(width range in elements), * (height range), (depth range)} * Valid extents with cudaArraySurfaceLoadStore set {(width range in * elements), (height range), (depth range)} * * * * * 1D * { (1,maxTexture1DMipmap), 0, 0 } * { (1,maxSurface1D), 0, 0 } * * * 2D * { (1,maxTexture2DMipmap[0]), (1,maxTexture2DMipmap[1]), 0 } * { (1,maxSurface2D[0]), (1,maxSurface2D[1]), 0 } * * * 3D * { (1,maxTexture3D[0]), (1,maxTexture3D[1]), (1,maxTexture3D[2]) } * OR { (1,maxTexture3DAlt[0]), (1,maxTexture3DAlt[1]), * (1,maxTexture3DAlt[2]) } * { (1,maxSurface3D[0]), (1,maxSurface3D[1]), (1,maxSurface3D[2]) } * * * 1D Layered * { (1,maxTexture1DLayered[0]), 0, (1,maxTexture1DLayered[1]) } * { (1,maxSurface1DLayered[0]), 0, (1,maxSurface1DLayered[1]) } * * * 2D Layered * { (1,maxTexture2DLayered[0]), (1,maxTexture2DLayered[1]), * (1,maxTexture2DLayered[2]) } * { (1,maxSurface2DLayered[0]), (1,maxSurface2DLayered[1]), * (1,maxSurface2DLayered[2]) } * * * Cubemap * { (1,maxTextureCubemap), (1,maxTextureCubemap), 6 } * { (1,maxSurfaceCubemap), (1,maxSurfaceCubemap), 6 } * * * Cubemap Layered * { (1,maxTextureCubemapLayered[0]), (1,maxTextureCubemapLayered[0]), * (1,maxTextureCubemapLayered[1]) } * { (1,maxSurfaceCubemapLayered[0]), (1,maxSurfaceCubemapLayered[0]), * (1,maxSurfaceCubemapLayered[1]) } * * * *
* \endxmlonly * * \param mipmappedArray - Pointer to allocated mipmapped array in device memory * \param desc - Requested channel format * \param extent - Requested allocation size (\p width field in elements) * \param numLevels - Number of mipmap levels to allocate * \param flags - Flags for extensions * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorMemoryAllocation * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaMalloc3D, ::cudaMalloc, ::cudaMallocPitch, ::cudaFree, * ::cudaFreeArray, * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)", * ::cudaFreeHost, ::cudaHostAlloc, * ::make_cudaExtent, * ::cuMipmappedArrayCreate */ extern __host__ cudaError_t CUDARTAPI cudaMallocMipmappedArray(cudaMipmappedArray_t *mipmappedArray, const struct cudaChannelFormatDesc* desc, struct cudaExtent extent, unsigned int numLevels, unsigned int flags __dv(0)); /** * \brief Gets a mipmap level of a CUDA mipmapped array * * Returns in \p *levelArray a CUDA array that represents a single mipmap level * of the CUDA mipmapped array \p mipmappedArray. * * If \p level is greater than the maximum number of levels in this mipmapped array, * ::cudaErrorInvalidValue is returned. * * If \p mipmappedArray is NULL, * ::cudaErrorInvalidResourceHandle is returned. * * \param levelArray - Returned mipmap level CUDA array * \param mipmappedArray - CUDA mipmapped array * \param level - Mipmap level * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * ::cudaErrorInvalidResourceHandle * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaMalloc3D, ::cudaMalloc, ::cudaMallocPitch, ::cudaFree, * ::cudaFreeArray, * \ref ::cudaMallocHost(void**, size_t) "cudaMallocHost (C API)", * ::cudaFreeHost, ::cudaHostAlloc, * ::make_cudaExtent, * ::cuMipmappedArrayGetLevel */ extern __host__ cudaError_t CUDARTAPI cudaGetMipmappedArrayLevel(cudaArray_t *levelArray, cudaMipmappedArray_const_t mipmappedArray, unsigned int level); /** * \brief Copies data between 3D objects * \code struct cudaExtent { size_t width; size_t height; size_t depth; }; struct cudaExtent make_cudaExtent(size_t w, size_t h, size_t d); struct cudaPos { size_t x; size_t y; size_t z; }; struct cudaPos make_cudaPos(size_t x, size_t y, size_t z); struct cudaMemcpy3DParms { cudaArray_t srcArray; struct cudaPos srcPos; struct cudaPitchedPtr srcPtr; cudaArray_t dstArray; struct cudaPos dstPos; struct cudaPitchedPtr dstPtr; struct cudaExtent extent; enum cudaMemcpyKind kind; }; \endcode * * ::cudaMemcpy3D() copies data betwen two 3D objects. The source and * destination objects may be in either host memory, device memory, or a CUDA * array. The source, destination, extent, and kind of copy performed is * specified by the ::cudaMemcpy3DParms struct which should be initialized to * zero before use: \code cudaMemcpy3DParms myParms = {0}; \endcode * * The struct passed to ::cudaMemcpy3D() must specify one of \p srcArray or * \p srcPtr and one of \p dstArray or \p dstPtr. Passing more than one * non-zero source or destination will cause ::cudaMemcpy3D() to return an * error. * * The \p srcPos and \p dstPos fields are optional offsets into the source and * destination objects and are defined in units of each object's elements. The * element for a host or device pointer is assumed to be unsigned char. * * The \p extent field defines the dimensions of the transferred area in * elements. If a CUDA array is participating in the copy, the extent is * defined in terms of that array's elements. If no CUDA array is * participating in the copy then the extents are defined in elements of * unsigned char. * * The \p kind field defines the direction of the copy. It must be one of * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost, * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing * ::cudaMemcpyDefault is recommended, in which case the type of transfer is * inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. * For ::cudaMemcpyHostToHost or ::cudaMemcpyHostToDevice or ::cudaMemcpyDeviceToHost * passed as kind and cudaArray type passed as source or destination, if the kind * implies cudaArray type to be present on the host, ::cudaMemcpy3D() will * disregard that implication and silently correct the kind based on the fact that * cudaArray type can only be present on the device. * * If the source and destination are both arrays, ::cudaMemcpy3D() will return * an error if they do not have the same element size. * * The source and destination object may not overlap. If overlapping source * and destination objects are specified, undefined behavior will result. * * The source object must entirely contain the region defined by \p srcPos * and \p extent. The destination object must entirely contain the region * defined by \p dstPos and \p extent. * * ::cudaMemcpy3D() returns an error if the pitch of \p srcPtr or \p dstPtr * exceeds the maximum allowed. The pitch of a ::cudaPitchedPtr allocated * with ::cudaMalloc3D() will always be valid. * * \param p - 3D memory copy parameters * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidPitchValue, * ::cudaErrorInvalidMemcpyDirection * \notefnerr * \note_sync * \note_init_rt * \note_callback * * \sa ::cudaMalloc3D, ::cudaMalloc3DArray, ::cudaMemset3D, ::cudaMemcpy3DAsync, * ::cudaMemcpy, ::cudaMemcpy2D, * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray, * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol, * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync, * ::cudaMemcpy2DToArrayAsync, * ::cudaMemcpy2DFromArrayAsync, * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync, * ::make_cudaExtent, ::make_cudaPos, * ::cuMemcpy3D */ extern __host__ cudaError_t CUDARTAPI cudaMemcpy3D(const struct cudaMemcpy3DParms *p); /** * \brief Copies memory between devices * * Perform a 3D memory copy according to the parameters specified in * \p p. See the definition of the ::cudaMemcpy3DPeerParms structure * for documentation of its parameters. * * Note that this function is synchronous with respect to the host only if * the source or destination of the transfer is host memory. Note also * that this copy is serialized with respect to all pending and future * asynchronous work in to the current device, the copy's source device, * and the copy's destination device (use ::cudaMemcpy3DPeerAsync to avoid * this synchronization). * * \param p - Parameters for the memory copy * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidDevice, * ::cudaErrorInvalidPitchValue * \notefnerr * \note_sync * \note_init_rt * \note_callback * * \sa ::cudaMemcpy, ::cudaMemcpyPeer, ::cudaMemcpyAsync, ::cudaMemcpyPeerAsync, * ::cudaMemcpy3DPeerAsync, * ::cuMemcpy3DPeer */ extern __host__ cudaError_t CUDARTAPI cudaMemcpy3DPeer(const struct cudaMemcpy3DPeerParms *p); /** * \brief Copies data between 3D objects * \code struct cudaExtent { size_t width; size_t height; size_t depth; }; struct cudaExtent make_cudaExtent(size_t w, size_t h, size_t d); struct cudaPos { size_t x; size_t y; size_t z; }; struct cudaPos make_cudaPos(size_t x, size_t y, size_t z); struct cudaMemcpy3DParms { cudaArray_t srcArray; struct cudaPos srcPos; struct cudaPitchedPtr srcPtr; cudaArray_t dstArray; struct cudaPos dstPos; struct cudaPitchedPtr dstPtr; struct cudaExtent extent; enum cudaMemcpyKind kind; }; \endcode * * ::cudaMemcpy3DAsync() copies data betwen two 3D objects. The source and * destination objects may be in either host memory, device memory, or a CUDA * array. The source, destination, extent, and kind of copy performed is * specified by the ::cudaMemcpy3DParms struct which should be initialized to * zero before use: \code cudaMemcpy3DParms myParms = {0}; \endcode * * The struct passed to ::cudaMemcpy3DAsync() must specify one of \p srcArray * or \p srcPtr and one of \p dstArray or \p dstPtr. Passing more than one * non-zero source or destination will cause ::cudaMemcpy3DAsync() to return an * error. * * The \p srcPos and \p dstPos fields are optional offsets into the source and * destination objects and are defined in units of each object's elements. The * element for a host or device pointer is assumed to be unsigned char. * For CUDA arrays, positions must be in the range [0, 2048) for any * dimension. * * The \p extent field defines the dimensions of the transferred area in * elements. If a CUDA array is participating in the copy, the extent is * defined in terms of that array's elements. If no CUDA array is * participating in the copy then the extents are defined in elements of * unsigned char. * * The \p kind field defines the direction of the copy. It must be one of * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost, * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing * ::cudaMemcpyDefault is recommended, in which case the type of transfer is * inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. * For ::cudaMemcpyHostToHost or ::cudaMemcpyHostToDevice or ::cudaMemcpyDeviceToHost * passed as kind and cudaArray type passed as source or destination, if the kind * implies cudaArray type to be present on the host, ::cudaMemcpy3DAsync() will * disregard that implication and silently correct the kind based on the fact that * cudaArray type can only be present on the device. * * If the source and destination are both arrays, ::cudaMemcpy3DAsync() will * return an error if they do not have the same element size. * * The source and destination object may not overlap. If overlapping source * and destination objects are specified, undefined behavior will result. * * The source object must lie entirely within the region defined by \p srcPos * and \p extent. The destination object must lie entirely within the region * defined by \p dstPos and \p extent. * * ::cudaMemcpy3DAsync() returns an error if the pitch of \p srcPtr or * \p dstPtr exceeds the maximum allowed. The pitch of a * ::cudaPitchedPtr allocated with ::cudaMalloc3D() will always be valid. * * ::cudaMemcpy3DAsync() is asynchronous with respect to the host, so * the call may return before the copy is complete. The copy can optionally * be associated to a stream by passing a non-zero \p stream argument. If * \p kind is ::cudaMemcpyHostToDevice or ::cudaMemcpyDeviceToHost and \p stream * is non-zero, the copy may overlap with operations in other streams. * * The device version of this function only handles device to device copies and * cannot be given local or shared pointers. * * \param p - 3D memory copy parameters * \param stream - Stream identifier * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidPitchValue, * ::cudaErrorInvalidMemcpyDirection * \notefnerr * \note_async * \note_null_stream * \note_init_rt * \note_callback * * \sa ::cudaMalloc3D, ::cudaMalloc3DArray, ::cudaMemset3D, ::cudaMemcpy3D, * ::cudaMemcpy, ::cudaMemcpy2D, * ::cudaMemcpy2DToArray, :::cudaMemcpy2DFromArray, * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol, * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync, * ::cudaMemcpy2DToArrayAsync, * ::cudaMemcpy2DFromArrayAsync, * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync, * ::make_cudaExtent, ::make_cudaPos, * ::cuMemcpy3DAsync */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemcpy3DAsync(const struct cudaMemcpy3DParms *p, cudaStream_t stream __dv(0)); /** * \brief Copies memory between devices asynchronously. * * Perform a 3D memory copy according to the parameters specified in * \p p. See the definition of the ::cudaMemcpy3DPeerParms structure * for documentation of its parameters. * * \param p - Parameters for the memory copy * \param stream - Stream identifier * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidDevice, * ::cudaErrorInvalidPitchValue * \notefnerr * \note_async * \note_null_stream * \note_init_rt * \note_callback * * \sa ::cudaMemcpy, ::cudaMemcpyPeer, ::cudaMemcpyAsync, ::cudaMemcpyPeerAsync, * ::cudaMemcpy3DPeerAsync, * ::cuMemcpy3DPeerAsync */ extern __host__ cudaError_t CUDARTAPI cudaMemcpy3DPeerAsync(const struct cudaMemcpy3DPeerParms *p, cudaStream_t stream __dv(0)); /** * \brief Gets free and total device memory * * Returns in \p *total the total amount of memory available to the the current context. * Returns in \p *free the amount of memory on the device that is free according to the OS. * CUDA is not guaranteed to be able to allocate all of the memory that the OS reports as free. * In a multi-tenet situation, free estimate returned is prone to race condition where * a new allocation/free done by a different process or a different thread in the same * process between the time when free memory was estimated and reported, will result in * deviation in free value reported and actual free memory. * * The integrated GPU on Tegra shares memory with CPU and other component * of the SoC. The free and total values returned by the API excludes * the SWAP memory space maintained by the OS on some platforms. * The OS may move some of the memory pages into swap area as the GPU or * CPU allocate or access memory. See Tegra app note on how to calculate * total and free memory on Tegra. * * \param free - Returned free memory in bytes * \param total - Returned total memory in bytes * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorLaunchFailure * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cuMemGetInfo */ extern __host__ cudaError_t CUDARTAPI cudaMemGetInfo(size_t *free, size_t *total); /** * \brief Gets info about the specified cudaArray * * Returns in \p *desc, \p *extent and \p *flags respectively, the type, shape * and flags of \p array. * * Any of \p *desc, \p *extent and \p *flags may be specified as NULL. * * \param desc - Returned array type * \param extent - Returned array shape. 2D arrays will have depth of zero * \param flags - Returned array flags * \param array - The ::cudaArray to get info for * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cuArrayGetDescriptor, * ::cuArray3DGetDescriptor */ extern __host__ cudaError_t CUDARTAPI cudaArrayGetInfo(struct cudaChannelFormatDesc *desc, struct cudaExtent *extent, unsigned int *flags, cudaArray_t array); /** * \brief Gets a CUDA array plane from a CUDA array * * Returns in \p pPlaneArray a CUDA array that represents a single format plane * of the CUDA array \p hArray. * * If \p planeIdx is greater than the maximum number of planes in this array or if the array does * not have a multi-planar format e.g: ::cudaChannelFormatKindNV12, then ::cudaErrorInvalidValue is returned. * * Note that if the \p hArray has format ::cudaChannelFormatKindNV12, then passing in 0 for \p planeIdx returns * a CUDA array of the same size as \p hArray but with one 8-bit channel and ::cudaChannelFormatKindUnsigned as its format kind. * If 1 is passed for \p planeIdx, then the returned CUDA array has half the height and width * of \p hArray with two 8-bit channels and ::cudaChannelFormatKindUnsigned as its format kind. * * \param pPlaneArray - Returned CUDA array referenced by the \p planeIdx * \param hArray - CUDA array * \param planeIdx - Plane index * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * ::cudaErrorInvalidResourceHandle * \notefnerr * * \sa * ::cuArrayGetPlane */ extern __host__ cudaError_t CUDARTAPI cudaArrayGetPlane(cudaArray_t *pPlaneArray, cudaArray_t hArray, unsigned int planeIdx); /** * \brief Returns the memory requirements of a CUDA array * * Returns the memory requirements of a CUDA array in \p memoryRequirements * If the CUDA array is not allocated with flag ::cudaArrayDeferredMapping * ::cudaErrorInvalidValue will be returned. * * The returned value in ::cudaArrayMemoryRequirements::size * represents the total size of the CUDA array. * The returned value in ::cudaArrayMemoryRequirements::alignment * represents the alignment necessary for mapping the CUDA array. * * \return * ::cudaSuccess * ::cudaErrorInvalidValue * * \param[out] memoryRequirements - Pointer to ::cudaArrayMemoryRequirements * \param[in] array - CUDA array to get the memory requirements of * \param[in] device - Device to get the memory requirements for * \sa ::cudaMipmappedArrayGetMemoryRequirements */ extern __host__ cudaError_t CUDARTAPI cudaArrayGetMemoryRequirements(struct cudaArrayMemoryRequirements *memoryRequirements, cudaArray_t array, int device); /** * \brief Returns the memory requirements of a CUDA mipmapped array * * Returns the memory requirements of a CUDA mipmapped array in \p memoryRequirements * If the CUDA mipmapped array is not allocated with flag ::cudaArrayDeferredMapping * ::cudaErrorInvalidValue will be returned. * * The returned value in ::cudaArrayMemoryRequirements::size * represents the total size of the CUDA mipmapped array. * The returned value in ::cudaArrayMemoryRequirements::alignment * represents the alignment necessary for mapping the CUDA mipmapped * array. * * \return * ::cudaSuccess * ::cudaErrorInvalidValue * * \param[out] memoryRequirements - Pointer to ::cudaArrayMemoryRequirements * \param[in] mipmap - CUDA mipmapped array to get the memory requirements of * \param[in] device - Device to get the memory requirements for * \sa ::cudaArrayGetMemoryRequirements */ extern __host__ cudaError_t CUDARTAPI cudaMipmappedArrayGetMemoryRequirements(struct cudaArrayMemoryRequirements *memoryRequirements, cudaMipmappedArray_t mipmap, int device); /** * \brief Returns the layout properties of a sparse CUDA array * * Returns the layout properties of a sparse CUDA array in \p sparseProperties. * If the CUDA array is not allocated with flag ::cudaArraySparse * ::cudaErrorInvalidValue will be returned. * * If the returned value in ::cudaArraySparseProperties::flags contains ::cudaArraySparsePropertiesSingleMipTail, * then ::cudaArraySparseProperties::miptailSize represents the total size of the array. Otherwise, it will be zero. * Also, the returned value in ::cudaArraySparseProperties::miptailFirstLevel is always zero. * Note that the \p array must have been allocated using ::cudaMallocArray or ::cudaMalloc3DArray. For CUDA arrays obtained * using ::cudaMipmappedArrayGetLevel, ::cudaErrorInvalidValue will be returned. Instead, ::cudaMipmappedArrayGetSparseProperties * must be used to obtain the sparse properties of the entire CUDA mipmapped array to which \p array belongs to. * * \return * ::cudaSuccess * ::cudaErrorInvalidValue * * \param[out] sparseProperties - Pointer to return the ::cudaArraySparseProperties * \param[in] array - The CUDA array to get the sparse properties of * * \sa * ::cudaMipmappedArrayGetSparseProperties, * ::cuMemMapArrayAsync */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaArrayGetSparseProperties(struct cudaArraySparseProperties *sparseProperties, cudaArray_t array); #endif /** * \brief Returns the layout properties of a sparse CUDA mipmapped array * * Returns the sparse array layout properties in \p sparseProperties. * If the CUDA mipmapped array is not allocated with flag ::cudaArraySparse * ::cudaErrorInvalidValue will be returned. * * For non-layered CUDA mipmapped arrays, ::cudaArraySparseProperties::miptailSize returns the * size of the mip tail region. The mip tail region includes all mip levels whose width, height or depth * is less than that of the tile. * For layered CUDA mipmapped arrays, if ::cudaArraySparseProperties::flags contains ::cudaArraySparsePropertiesSingleMipTail, * then ::cudaArraySparseProperties::miptailSize specifies the size of the mip tail of all layers combined. * Otherwise, ::cudaArraySparseProperties::miptailSize specifies mip tail size per layer. * The returned value of ::cudaArraySparseProperties::miptailFirstLevel is valid only if ::cudaArraySparseProperties::miptailSize is non-zero. * * \return * ::cudaSuccess * ::cudaErrorInvalidValue * * \param[out] sparseProperties - Pointer to return ::cudaArraySparseProperties * \param[in] mipmap - The CUDA mipmapped array to get the sparse properties of * * \sa * ::cudaArrayGetSparseProperties, * ::cuMemMapArrayAsync */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaMipmappedArrayGetSparseProperties(struct cudaArraySparseProperties *sparseProperties, cudaMipmappedArray_t mipmap); #endif /** * \brief Copies data between host and device * * Copies \p count bytes from the memory area pointed to by \p src to the * memory area pointed to by \p dst, where \p kind specifies the direction * of the copy, and must be one of ::cudaMemcpyHostToHost, * ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost, * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing * ::cudaMemcpyDefault is recommended, in which case the type of transfer is * inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. Calling * ::cudaMemcpy() with dst and src pointers that do not match the direction of * the copy results in an undefined behavior. * * \param dst - Destination memory address * \param src - Source memory address * \param count - Size in bytes to copy * \param kind - Type of transfer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidMemcpyDirection * \notefnerr * \note_init_rt * \note_callback * * \note_sync * \note_memcpy * * \sa ::cudaMemcpy2D, * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray, * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol, * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync, * ::cudaMemcpy2DToArrayAsync, * ::cudaMemcpy2DFromArrayAsync, * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync, * ::cuMemcpyDtoH, * ::cuMemcpyHtoD, * ::cuMemcpyDtoD, * ::cuMemcpy */ extern __host__ cudaError_t CUDARTAPI cudaMemcpy(void *dst, const void *src, size_t count, enum cudaMemcpyKind kind); /** * \brief Copies memory between two devices * * Copies memory from one device to memory on another device. \p dst is the * base device pointer of the destination memory and \p dstDevice is the * destination device. \p src is the base device pointer of the source memory * and \p srcDevice is the source device. \p count specifies the number of bytes * to copy. * * Note that this function is asynchronous with respect to the host, but * serialized with respect all pending and future asynchronous work in to the * current device, \p srcDevice, and \p dstDevice (use ::cudaMemcpyPeerAsync * to avoid this synchronization). * * \param dst - Destination device pointer * \param dstDevice - Destination device * \param src - Source device pointer * \param srcDevice - Source device * \param count - Size of memory copy in bytes * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidDevice * \notefnerr * \note_sync * \note_init_rt * \note_callback * * \sa ::cudaMemcpy, ::cudaMemcpyAsync, ::cudaMemcpyPeerAsync, * ::cudaMemcpy3DPeerAsync, * ::cuMemcpyPeer */ extern __host__ cudaError_t CUDARTAPI cudaMemcpyPeer(void *dst, int dstDevice, const void *src, int srcDevice, size_t count); /** * \brief Copies data between host and device * * Copies a matrix (\p height rows of \p width bytes each) from the memory * area pointed to by \p src to the memory area pointed to by \p dst, where * \p kind specifies the direction of the copy, and must be one of * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost, * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing * ::cudaMemcpyDefault is recommended, in which case the type of transfer is * inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. \p dpitch and * \p spitch are the widths in memory in bytes of the 2D arrays pointed to by * \p dst and \p src, including any padding added to the end of each row. The * memory areas may not overlap. \p width must not exceed either \p dpitch or * \p spitch. Calling ::cudaMemcpy2D() with \p dst and \p src pointers that do * not match the direction of the copy results in an undefined behavior. * ::cudaMemcpy2D() returns an error if \p dpitch or \p spitch exceeds * the maximum allowed. * * \param dst - Destination memory address * \param dpitch - Pitch of destination memory * \param src - Source memory address * \param spitch - Pitch of source memory * \param width - Width of matrix transfer (columns in bytes) * \param height - Height of matrix transfer (rows) * \param kind - Type of transfer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidPitchValue, * ::cudaErrorInvalidMemcpyDirection * \notefnerr * \note_init_rt * \note_callback * \note_memcpy * * \sa ::cudaMemcpy, * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray, * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol, * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync, * ::cudaMemcpy2DToArrayAsync, * ::cudaMemcpy2DFromArrayAsync, * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync, * ::cuMemcpy2D, * ::cuMemcpy2DUnaligned */ extern __host__ cudaError_t CUDARTAPI cudaMemcpy2D(void *dst, size_t dpitch, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind); /** * \brief Copies data between host and device * * Copies a matrix (\p height rows of \p width bytes each) from the memory * area pointed to by \p src to the CUDA array \p dst starting at * \p hOffset rows and \p wOffset bytes from the upper left corner, * where \p kind specifies the direction of the copy, and must be one * of ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost, * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing * ::cudaMemcpyDefault is recommended, in which case the type of transfer is * inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. * \p spitch is the width in memory in bytes of the 2D array pointed to by * \p src, including any padding added to the end of each row. \p wOffset + * \p width must not exceed the width of the CUDA array \p dst. \p width must * not exceed \p spitch. ::cudaMemcpy2DToArray() returns an error if \p spitch * exceeds the maximum allowed. * * \param dst - Destination memory address * \param wOffset - Destination starting X offset (columns in bytes) * \param hOffset - Destination starting Y offset (rows) * \param src - Source memory address * \param spitch - Pitch of source memory * \param width - Width of matrix transfer (columns in bytes) * \param height - Height of matrix transfer (rows) * \param kind - Type of transfer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidPitchValue, * ::cudaErrorInvalidMemcpyDirection * \notefnerr * \note_sync * \note_init_rt * \note_callback * \note_memcpy * * \sa ::cudaMemcpy, ::cudaMemcpy2D, * ::cudaMemcpy2DFromArray, * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol, * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync, * ::cudaMemcpy2DToArrayAsync, * ::cudaMemcpy2DFromArrayAsync, * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync, * ::cuMemcpy2D, * ::cuMemcpy2DUnaligned */ extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DToArray(cudaArray_t dst, size_t wOffset, size_t hOffset, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind); /** * \brief Copies data between host and device * * Copies a matrix (\p height rows of \p width bytes each) from the CUDA * array \p src starting at \p hOffset rows and \p wOffset bytes from the * upper left corner to the memory area pointed to by \p dst, where * \p kind specifies the direction of the copy, and must be one of * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost, * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing * ::cudaMemcpyDefault is recommended, in which case the type of transfer is * inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. \p dpitch is the * width in memory in bytes of the 2D array pointed to by \p dst, including any * padding added to the end of each row. \p wOffset + \p width must not exceed * the width of the CUDA array \p src. \p width must not exceed \p dpitch. * ::cudaMemcpy2DFromArray() returns an error if \p dpitch exceeds the maximum * allowed. * * \param dst - Destination memory address * \param dpitch - Pitch of destination memory * \param src - Source memory address * \param wOffset - Source starting X offset (columns in bytes) * \param hOffset - Source starting Y offset (rows) * \param width - Width of matrix transfer (columns in bytes) * \param height - Height of matrix transfer (rows) * \param kind - Type of transfer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidPitchValue, * ::cudaErrorInvalidMemcpyDirection * \notefnerr * \note_sync * \note_init_rt * \note_callback * \note_memcpy * * \sa ::cudaMemcpy, ::cudaMemcpy2D, * ::cudaMemcpy2DToArray, * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol, * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync, * ::cudaMemcpy2DToArrayAsync, * ::cudaMemcpy2DFromArrayAsync, * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync, * ::cuMemcpy2D, * ::cuMemcpy2DUnaligned */ extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DFromArray(void *dst, size_t dpitch, cudaArray_const_t src, size_t wOffset, size_t hOffset, size_t width, size_t height, enum cudaMemcpyKind kind); /** * \brief Copies data between host and device * * Copies a matrix (\p height rows of \p width bytes each) from the CUDA * array \p src starting at \p hOffsetSrc rows and \p wOffsetSrc bytes from the * upper left corner to the CUDA array \p dst starting at \p hOffsetDst rows * and \p wOffsetDst bytes from the upper left corner, where \p kind * specifies the direction of the copy, and must be one of * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost, * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing * ::cudaMemcpyDefault is recommended, in which case the type of transfer is * inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. * \p wOffsetDst + \p width must not exceed the width of the CUDA array \p dst. * \p wOffsetSrc + \p width must not exceed the width of the CUDA array \p src. * * \param dst - Destination memory address * \param wOffsetDst - Destination starting X offset (columns in bytes) * \param hOffsetDst - Destination starting Y offset (rows) * \param src - Source memory address * \param wOffsetSrc - Source starting X offset (columns in bytes) * \param hOffsetSrc - Source starting Y offset (rows) * \param width - Width of matrix transfer (columns in bytes) * \param height - Height of matrix transfer (rows) * \param kind - Type of transfer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidMemcpyDirection * \notefnerr * \note_sync * \note_init_rt * \note_callback * * \sa ::cudaMemcpy, ::cudaMemcpy2D, * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray, * ::cudaMemcpyToSymbol, * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync, * ::cudaMemcpy2DToArrayAsync, * ::cudaMemcpy2DFromArrayAsync, * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync, * ::cuMemcpy2D, * ::cuMemcpy2DUnaligned */ extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DArrayToArray(cudaArray_t dst, size_t wOffsetDst, size_t hOffsetDst, cudaArray_const_t src, size_t wOffsetSrc, size_t hOffsetSrc, size_t width, size_t height, enum cudaMemcpyKind kind __dv(cudaMemcpyDeviceToDevice)); /** * \brief Copies data to the given symbol on the device * * Copies \p count bytes from the memory area pointed to by \p src * to the memory area pointed to by \p offset bytes from the start of symbol * \p symbol. The memory areas may not overlap. \p symbol is a variable that * resides in global or constant memory space. \p kind can be either * ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. * Passing ::cudaMemcpyDefault is recommended, in which case the type of * transfer is inferred from the pointer values. However, ::cudaMemcpyDefault * is only allowed on systems that support unified virtual addressing. * * \param symbol - Device symbol address * \param src - Source memory address * \param count - Size in bytes to copy * \param offset - Offset from start of symbol in bytes * \param kind - Type of transfer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidSymbol, * ::cudaErrorInvalidMemcpyDirection, * ::cudaErrorNoKernelImageForDevice * \notefnerr * \note_sync * \note_string_api_deprecation * \note_init_rt * \note_callback * * \sa ::cudaMemcpy, ::cudaMemcpy2D, * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray, * ::cudaMemcpy2DArrayToArray, * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync, * ::cudaMemcpy2DToArrayAsync, * ::cudaMemcpy2DFromArrayAsync, * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync, * ::cuMemcpy, * ::cuMemcpyHtoD, * ::cuMemcpyDtoD */ extern __host__ cudaError_t CUDARTAPI cudaMemcpyToSymbol(const void *symbol, const void *src, size_t count, size_t offset __dv(0), enum cudaMemcpyKind kind __dv(cudaMemcpyHostToDevice)); /** * \brief Copies data from the given symbol on the device * * Copies \p count bytes from the memory area pointed to by \p offset bytes * from the start of symbol \p symbol to the memory area pointed to by \p dst. * The memory areas may not overlap. \p symbol is a variable that * resides in global or constant memory space. \p kind can be either * ::cudaMemcpyDeviceToHost, ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. * Passing ::cudaMemcpyDefault is recommended, in which case the type of * transfer is inferred from the pointer values. However, ::cudaMemcpyDefault * is only allowed on systems that support unified virtual addressing. * * \param dst - Destination memory address * \param symbol - Device symbol address * \param count - Size in bytes to copy * \param offset - Offset from start of symbol in bytes * \param kind - Type of transfer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidSymbol, * ::cudaErrorInvalidMemcpyDirection, * ::cudaErrorNoKernelImageForDevice * \notefnerr * \note_sync * \note_string_api_deprecation * \note_init_rt * \note_callback * * \sa ::cudaMemcpy, ::cudaMemcpy2D, * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray, * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol, * ::cudaMemcpyAsync, ::cudaMemcpy2DAsync, * ::cudaMemcpy2DToArrayAsync, * ::cudaMemcpy2DFromArrayAsync, * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync, * ::cuMemcpy, * ::cuMemcpyDtoH, * ::cuMemcpyDtoD */ extern __host__ cudaError_t CUDARTAPI cudaMemcpyFromSymbol(void *dst, const void *symbol, size_t count, size_t offset __dv(0), enum cudaMemcpyKind kind __dv(cudaMemcpyDeviceToHost)); /** * \brief Copies data between host and device * * Copies \p count bytes from the memory area pointed to by \p src to the * memory area pointed to by \p dst, where \p kind specifies the * direction of the copy, and must be one of ::cudaMemcpyHostToHost, * ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost, * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing * ::cudaMemcpyDefault is recommended, in which case the type of transfer is * inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. * * The memory areas may not overlap. Calling ::cudaMemcpyAsync() with \p dst and * \p src pointers that do not match the direction of the copy results in an * undefined behavior. * * ::cudaMemcpyAsync() is asynchronous with respect to the host, so the call * may return before the copy is complete. The copy can optionally be * associated to a stream by passing a non-zero \p stream argument. If \p kind * is ::cudaMemcpyHostToDevice or ::cudaMemcpyDeviceToHost and the \p stream is * non-zero, the copy may overlap with operations in other streams. * * The device version of this function only handles device to device copies and * cannot be given local or shared pointers. * * \param dst - Destination memory address * \param src - Source memory address * \param count - Size in bytes to copy * \param kind - Type of transfer * \param stream - Stream identifier * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidMemcpyDirection * \notefnerr * \note_async * \note_null_stream * \note_init_rt * \note_callback * \note_memcpy * * \sa ::cudaMemcpy, ::cudaMemcpy2D, * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray, * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol, * ::cudaMemcpyFromSymbol, ::cudaMemcpy2DAsync, * ::cudaMemcpy2DToArrayAsync, * ::cudaMemcpy2DFromArrayAsync, * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync, * ::cuMemcpyAsync, * ::cuMemcpyDtoHAsync, * ::cuMemcpyHtoDAsync, * ::cuMemcpyDtoDAsync */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemcpyAsync(void *dst, const void *src, size_t count, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0)); /** * \brief Copies memory between two devices asynchronously. * * Copies memory from one device to memory on another device. \p dst is the * base device pointer of the destination memory and \p dstDevice is the * destination device. \p src is the base device pointer of the source memory * and \p srcDevice is the source device. \p count specifies the number of bytes * to copy. * * Note that this function is asynchronous with respect to the host and all work * on other devices. * * \param dst - Destination device pointer * \param dstDevice - Destination device * \param src - Source device pointer * \param srcDevice - Source device * \param count - Size of memory copy in bytes * \param stream - Stream identifier * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidDevice * \notefnerr * \note_async * \note_null_stream * \note_init_rt * \note_callback * * \sa ::cudaMemcpy, ::cudaMemcpyPeer, ::cudaMemcpyAsync, * ::cudaMemcpy3DPeerAsync, * ::cuMemcpyPeerAsync */ extern __host__ cudaError_t CUDARTAPI cudaMemcpyPeerAsync(void *dst, int dstDevice, const void *src, int srcDevice, size_t count, cudaStream_t stream __dv(0)); /** * \brief Performs a batch of memory copies asynchronously. * * Performs a batch of memory copies. The batch as a whole executes in stream order but copies within a * batch are not guaranteed to execute in any specific order. This API only supports pointer-to-pointer copies. * For copies involving CUDA arrays, please see ::cudaMemcpy3DBatchAsync. * * Performs memory copies from source buffers specified in \p srcs to destination buffers specified in \p dsts. * The size of each copy is specified in \p sizes. All three arrays must be of the same length as specified * by \p count. Since there are no ordering guarantees for copies within a batch, specifying any dependent copies * within a batch will result in undefined behavior. * * Every copy in the batch has to be associated with a set of attributes specified in the \p attrs array. * Each entry in this array can apply to more than one copy. This can be done by specifying in the \p attrsIdxs array, * the index of the first copy that the corresponding entry in the \p attrs array applies to. Both \p attrs and * \p attrsIdxs must be of the same length as specified by \p numAttrs. For example, if a batch has 10 copies listed * in dst/src/sizes, the first 6 of which have one set of attributes and the remaining 4 another, then \p numAttrs * will be 2, \p attrsIdxs will be {0, 6} and \p attrs will contains the two sets of attributes. Note that the first entry * in \p attrsIdxs must always be 0. Also, each entry must be greater than the previous entry and the last entry should be * less than \p count. Furthermore, \p numAttrs must be lesser than or equal to \p count. * * The ::cudaMemcpyAttributes::srcAccessOrder indicates the source access ordering to be observed for copies associated * with the attribute. If the source access order is set to ::cudaMemcpySrcAccessOrderStream, then the source will * be accessed in stream order. If the source access order is set to ::cudaMemcpySrcAccessOrderDuringApiCall then * it indicates that access to the source pointer can be out of stream order and all accesses must be complete before the * API call returns. This flag is suited for ephemeral sources (ex., stack variables) when it's known that no prior * operations in the stream can be accessing the memory and also that the lifetime of the memory is limited to the scope * that the source variable was declared in. Specifying this flag allows the driver to optimize the copy and removes the * need for the user to synchronize the stream after the API call. If the source access order is set to * ::cudaMemcpySrcAccessOrderAny then it indicates that access to the source pointer can be out of stream order and the * accesses can happen even after the API call returns. This flag is suited for host pointers allocated * outside CUDA (ex., via malloc) when it's known that no prior operations in the stream can be accessing the memory. * Specifying this flag allows the driver to optimize the copy on certain platforms. Each memcpy operation in the batch * must have a valid ::cudaMemcpyAttributes corresponding to it including the appropriate srcAccessOrder setting, * otherwise the API will return ::cudaErrorInvalidValue. * * The ::cudaMemcpyAttributes::srcLocHint and ::cudaMemcpyAttributes::dstLocHint allows applications to specify hint locations * for operands of a copy when the operand doesn't have a fixed location. That is, these hints are * only applicable for managed memory pointers on devices where ::cudaDevAttrConcurrentManagedAccess is true or * system-allocated pageable memory on devices where ::cudaDevAttrPageableMemoryAccess is true. * For other cases, these hints are ignored. * * The ::cudaMemcpyAttributes::flags field can be used to specify certain flags for copies. Setting the * ::cudaMemcpyFlagPreferOverlapWithCompute flag indicates that the associated copies should preferably overlap with * any compute work. Note that this flag is a hint and can be ignored depending on the platform and other parameters of the copy. * * If any error is encountered while parsing the batch, the index within the batch where the error was encountered * will be returned in \p failIdx. * * \param dsts - Array of destination pointers. * \param srcs - Array of memcpy source pointers. * \param sizes - Array of sizes for memcpy operations. * \param count - Size of \p dsts, \p srcs and \p sizes arrays * \param attrs - Array of memcpy attributes. * \param attrsIdxs - Array of indices to specify which copies each entry in the \p attrs array applies to. * The attributes specified in attrs[k] will be applied to copies starting from attrsIdxs[k] * through attrsIdxs[k+1] - 1. Also attrs[numAttrs-1] will apply to copies starting from * attrsIdxs[numAttrs-1] through count - 1. * \param numAttrs - Size of \p attrs and \p attrsIdxs arrays. * \param failIdx - Pointer to a location to return the index of the copy where a failure was encountered. * The value will be SIZE_MAX if the error doesn't pertain to any specific copy. * \param hStream - The stream to enqueue the operations in. Must not be legacy NULL stream. * * \return * ::cudaSuccess * ::cudaErrorInvalidValue * \notefnerr * \note_async * \note_memcpy */ extern __host__ cudaError_t CUDARTAPI cudaMemcpyBatchAsync(void **dsts, void **srcs, size_t *sizes, size_t count, struct cudaMemcpyAttributes *attrs, size_t *attrsIdxs, size_t numAttrs, size_t *failIdx, cudaStream_t stream); /** * \brief Performs a batch of 3D memory copies asynchronously. * * Performs a batch of memory copies. The batch as a whole executes in stream order but copies within a * batch are not guaranteed to execute in any specific order. Note that this means specifying any dependent * copies within a batch will result in undefined behavior. * * Performs memory copies as specified in the \p opList array. The length of this array is specified in \p numOps. * Each entry in this array describes a copy operation. This includes among other things, the source and destination * operands for the copy as specified in ::cudaMemcpy3DBatchOp::src and ::cudaMemcpy3DBatchOp::dst respectively. * The source and destination operands of a copy can either be a pointer or a CUDA array. The width, height and depth * of a copy is specified in ::cudaMemcpy3DBatchOp::extent. The width, height and depth of a copy are specified in * elements and must not be zero. For pointer-to-pointer copies, the element size is considered to be 1. For pointer * to CUDA array or vice versa copies, the element size is determined by the CUDA array. For CUDA array to CUDA array copies, * the element size of the two CUDA arrays must match. * * For a given operand, if ::cudaMemcpy3DOperand::type is specified as ::cudaMemcpyOperandTypePointer, then * ::cudaMemcpy3DOperand::op::ptr will be used. The ::cudaMemcpy3DOperand::op::ptr::ptr field must contain the pointer where * the copy should begin. The ::cudaMemcpy3DOperand::op::ptr::rowLength field specifies the length of each row in elements and * must either be zero or be greater than or equal to the width of the copy specified in ::cudaMemcpy3DBatchOp::extent::width. * The ::cudaMemcpy3DOperand::op::ptr::layerHeight field specifies the height of each layer and must either be * zero or be greater than or equal to the height of the copy specified in ::cudaMemcpy3DBatchOp::extent::height. * When either of these values is zero, that aspect of the operand is considered to be tightly packed according to the copy extent. * For managed memory pointers on devices where ::cudaDevAttrConcurrentManagedAccess is true or system-allocated pageable memory * on devices where ::cudaDevAttrPageableMemoryAccess is true, the ::cudaMemcpy3DOperand::op::ptr::locHint field can be used to hint * the location of the operand. * * If an operand's type is specified as ::cudaMemcpyOperandTypeArray, then ::cudaMemcpy3DOperand::op::array will be used. * The ::cudaMemcpy3DOperand::op::array::array field specifies the CUDA array and ::cudaMemcpy3DOperand::op::array::offset specifies * the 3D offset into that array where the copy begins. * * The ::cudaMemcpyAttributes::srcAccessOrder indicates the source access ordering to be observed for copies associated * with the attribute. If the source access order is set to ::cudaMemcpySrcAccessOrderStream, then the source will * be accessed in stream order. If the source access order is set to ::cudaMemcpySrcAccessOrderDuringApiCall then * it indicates that access to the source pointer can be out of stream order and all accesses must be complete before the * API call returns. This flag is suited for ephemeral sources (ex., stack variables) when it's known that no prior * operations in the stream can be accessing the memory and also that the lifetime of the memory is limited to the scope * that the source variable was declared in. Specifying this flag allows the driver to optimize the copy and removes the * need for the user to synchronize the stream after the API call. If the source access order is set to * ::cudaMemcpySrcAccessOrderAny then it indicates that access to the source pointer can be out of stream order and the * accesses can happen even after the API call returns. This flag is suited for host pointers allocated * outside CUDA (ex., via malloc) when it's known that no prior operations in the stream can be accessing the memory. * Specifying this flag allows the driver to optimize the copy on certain platforms. Each memcopy operation in \p opList * must have a valid srcAccessOrder setting, otherwise this API will return ::cudaErrorInvalidValue. * * The ::cudaMemcpyAttributes::flags field can be used to specify certain flags for copies. Setting the * ::cudaMemcpyFlagPreferOverlapWithCompute flag indicates that the associated copies should preferably overlap with * any compute work. Note that this flag is a hint and can be ignored depending on the platform and other parameters of the copy. * * If any error is encountered while parsing the batch, the index within the batch where the error was encountered * will be returned in \p failIdx. * * \param numOps - Total number of memcpy operations. * \param opList - Array of size \p numOps containing the actual memcpy operations. * \param failIdx - Pointer to a location to return the index of the copy where a failure was encountered. * The value will be SIZE_MAX if the error doesn't pertain to any specific copy. * \param flags - Flags for future use, must be zero now. * \param hStream - The stream to enqueue the operations in. Must not be default NULL stream. * * \return * ::cudaSuccess * ::cudaErrorInvalidValue * \notefnerr * \note_async * \note_memcpy */ extern __host__ cudaError_t CUDARTAPI cudaMemcpy3DBatchAsync(size_t numOps, struct cudaMemcpy3DBatchOp *opList, size_t *failIdx, unsigned long long flags, cudaStream_t stream); /** * \brief Copies data between host and device * * Copies a matrix (\p height rows of \p width bytes each) from the memory * area pointed to by \p src to the memory area pointed to by \p dst, where * \p kind specifies the direction of the copy, and must be one of * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost, * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing * ::cudaMemcpyDefault is recommended, in which case the type of transfer is * inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. * \p dpitch and \p spitch are the widths in memory in bytes of the 2D arrays * pointed to by \p dst and \p src, including any padding added to the end of * each row. The memory areas may not overlap. \p width must not exceed either * \p dpitch or \p spitch. * * Calling ::cudaMemcpy2DAsync() with \p dst and \p src pointers that do not * match the direction of the copy results in an undefined behavior. * ::cudaMemcpy2DAsync() returns an error if \p dpitch or \p spitch is greater * than the maximum allowed. * * ::cudaMemcpy2DAsync() is asynchronous with respect to the host, so * the call may return before the copy is complete. The copy can optionally * be associated to a stream by passing a non-zero \p stream argument. If * \p kind is ::cudaMemcpyHostToDevice or ::cudaMemcpyDeviceToHost and * \p stream is non-zero, the copy may overlap with operations in other * streams. * * The device version of this function only handles device to device copies and * cannot be given local or shared pointers. * * \param dst - Destination memory address * \param dpitch - Pitch of destination memory * \param src - Source memory address * \param spitch - Pitch of source memory * \param width - Width of matrix transfer (columns in bytes) * \param height - Height of matrix transfer (rows) * \param kind - Type of transfer * \param stream - Stream identifier * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidPitchValue, * ::cudaErrorInvalidMemcpyDirection * \notefnerr * \note_async * \note_null_stream * \note_init_rt * \note_callback * \note_memcpy * * \sa ::cudaMemcpy, ::cudaMemcpy2D, * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray, * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol, * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, * ::cudaMemcpy2DToArrayAsync, * ::cudaMemcpy2DFromArrayAsync, * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync, * ::cuMemcpy2DAsync */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemcpy2DAsync(void *dst, size_t dpitch, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0)); /** * \brief Copies data between host and device * * Copies a matrix (\p height rows of \p width bytes each) from the memory * area pointed to by \p src to the CUDA array \p dst starting at \p hOffset * rows and \p wOffset bytes from the upper left corner, where \p kind specifies * the direction of the copy, and must be one of ::cudaMemcpyHostToHost, * ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost, * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing * ::cudaMemcpyDefault is recommended, in which case the type of transfer is * inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. * \p spitch is the width in memory in bytes of the 2D array pointed to by * \p src, including any padding added to the end of each row. \p wOffset + * \p width must not exceed the width of the CUDA array \p dst. \p width must * not exceed \p spitch. ::cudaMemcpy2DToArrayAsync() returns an error if * \p spitch exceeds the maximum allowed. * * ::cudaMemcpy2DToArrayAsync() is asynchronous with respect to the host, so * the call may return before the copy is complete. The copy can optionally * be associated to a stream by passing a non-zero \p stream argument. If * \p kind is ::cudaMemcpyHostToDevice or ::cudaMemcpyDeviceToHost and * \p stream is non-zero, the copy may overlap with operations in other * streams. * * \param dst - Destination memory address * \param wOffset - Destination starting X offset (columns in bytes) * \param hOffset - Destination starting Y offset (rows) * \param src - Source memory address * \param spitch - Pitch of source memory * \param width - Width of matrix transfer (columns in bytes) * \param height - Height of matrix transfer (rows) * \param kind - Type of transfer * \param stream - Stream identifier * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidPitchValue, * ::cudaErrorInvalidMemcpyDirection * \notefnerr * \note_async * \note_null_stream * \note_init_rt * \note_callback * \note_memcpy * * \sa ::cudaMemcpy, ::cudaMemcpy2D, * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray, * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol, * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync, * * ::cudaMemcpy2DFromArrayAsync, * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync, * ::cuMemcpy2DAsync */ extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DToArrayAsync(cudaArray_t dst, size_t wOffset, size_t hOffset, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0)); /** * \brief Copies data between host and device * * Copies a matrix (\p height rows of \p width bytes each) from the CUDA * array \p src starting at \p hOffset rows and \p wOffset bytes from the * upper left corner to the memory area pointed to by \p dst, * where \p kind specifies the direction of the copy, and must be one of * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost, * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing * ::cudaMemcpyDefault is recommended, in which case the type of transfer is * inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. * \p dpitch is the width in memory in bytes of the 2D * array pointed to by \p dst, including any padding added to the end of each * row. \p wOffset + \p width must not exceed the width of the CUDA array * \p src. \p width must not exceed \p dpitch. ::cudaMemcpy2DFromArrayAsync() * returns an error if \p dpitch exceeds the maximum allowed. * * ::cudaMemcpy2DFromArrayAsync() is asynchronous with respect to the host, so * the call may return before the copy is complete. The copy can optionally be * associated to a stream by passing a non-zero \p stream argument. If \p kind * is ::cudaMemcpyHostToDevice or ::cudaMemcpyDeviceToHost and \p stream is * non-zero, the copy may overlap with operations in other streams. * * \param dst - Destination memory address * \param dpitch - Pitch of destination memory * \param src - Source memory address * \param wOffset - Source starting X offset (columns in bytes) * \param hOffset - Source starting Y offset (rows) * \param width - Width of matrix transfer (columns in bytes) * \param height - Height of matrix transfer (rows) * \param kind - Type of transfer * \param stream - Stream identifier * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidPitchValue, * ::cudaErrorInvalidMemcpyDirection * \notefnerr * \note_async * \note_null_stream * \note_init_rt * \note_callback * \note_memcpy * * \sa ::cudaMemcpy, ::cudaMemcpy2D, * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray, * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol, * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync, * ::cudaMemcpy2DToArrayAsync, * * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync, * ::cuMemcpy2DAsync */ extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DFromArrayAsync(void *dst, size_t dpitch, cudaArray_const_t src, size_t wOffset, size_t hOffset, size_t width, size_t height, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0)); /** * \brief Copies data to the given symbol on the device * * Copies \p count bytes from the memory area pointed to by \p src * to the memory area pointed to by \p offset bytes from the start of symbol * \p symbol. The memory areas may not overlap. \p symbol is a variable that * resides in global or constant memory space. \p kind can be either * ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. * Passing ::cudaMemcpyDefault is recommended, in which case the type of transfer * is inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. * * ::cudaMemcpyToSymbolAsync() is asynchronous with respect to the host, so * the call may return before the copy is complete. The copy can optionally * be associated to a stream by passing a non-zero \p stream argument. If * \p kind is ::cudaMemcpyHostToDevice and \p stream is non-zero, the copy * may overlap with operations in other streams. * * \param symbol - Device symbol address * \param src - Source memory address * \param count - Size in bytes to copy * \param offset - Offset from start of symbol in bytes * \param kind - Type of transfer * \param stream - Stream identifier * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidSymbol, * ::cudaErrorInvalidMemcpyDirection, * ::cudaErrorNoKernelImageForDevice * \notefnerr * \note_async * \note_null_stream * \note_string_api_deprecation * \note_init_rt * \note_callback * * \sa ::cudaMemcpy, ::cudaMemcpy2D, * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray, * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol, * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync, * ::cudaMemcpy2DToArrayAsync, * ::cudaMemcpy2DFromArrayAsync, * ::cudaMemcpyFromSymbolAsync, * ::cuMemcpyAsync, * ::cuMemcpyHtoDAsync, * ::cuMemcpyDtoDAsync */ extern __host__ cudaError_t CUDARTAPI cudaMemcpyToSymbolAsync(const void *symbol, const void *src, size_t count, size_t offset, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0)); /** * \brief Copies data from the given symbol on the device * * Copies \p count bytes from the memory area pointed to by \p offset bytes * from the start of symbol \p symbol to the memory area pointed to by \p dst. * The memory areas may not overlap. \p symbol is a variable that resides in * global or constant memory space. \p kind can be either * ::cudaMemcpyDeviceToHost, ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. * Passing ::cudaMemcpyDefault is recommended, in which case the type of transfer * is inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. * * ::cudaMemcpyFromSymbolAsync() is asynchronous with respect to the host, so * the call may return before the copy is complete. The copy can optionally be * associated to a stream by passing a non-zero \p stream argument. If \p kind * is ::cudaMemcpyDeviceToHost and \p stream is non-zero, the copy may overlap * with operations in other streams. * * \param dst - Destination memory address * \param symbol - Device symbol address * \param count - Size in bytes to copy * \param offset - Offset from start of symbol in bytes * \param kind - Type of transfer * \param stream - Stream identifier * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidSymbol, * ::cudaErrorInvalidMemcpyDirection, * ::cudaErrorNoKernelImageForDevice * \notefnerr * \note_async * \note_null_stream * \note_string_api_deprecation * \note_init_rt * \note_callback * * \sa ::cudaMemcpy, ::cudaMemcpy2D, * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray, * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol, * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync, * ::cudaMemcpy2DToArrayAsync, * ::cudaMemcpy2DFromArrayAsync, * ::cudaMemcpyToSymbolAsync, * ::cuMemcpyAsync, * ::cuMemcpyDtoHAsync, * ::cuMemcpyDtoDAsync */ extern __host__ cudaError_t CUDARTAPI cudaMemcpyFromSymbolAsync(void *dst, const void *symbol, size_t count, size_t offset, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0)); /** * \brief Initializes or sets device memory to a value * * Fills the first \p count bytes of the memory area pointed to by \p devPtr * with the constant byte value \p value. * * Note that this function is asynchronous with respect to the host unless * \p devPtr refers to pinned host memory. * * \param devPtr - Pointer to device memory * \param value - Value to set for each byte of specified memory * \param count - Size in bytes to set * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * \notefnerr * \note_memset * \note_init_rt * \note_callback * * \sa * ::cuMemsetD8, * ::cuMemsetD16, * ::cuMemsetD32 */ extern __host__ cudaError_t CUDARTAPI cudaMemset(void *devPtr, int value, size_t count); /** * \brief Initializes or sets device memory to a value * * Sets to the specified value \p value a matrix (\p height rows of \p width * bytes each) pointed to by \p dstPtr. \p pitch is the width in bytes of the * 2D array pointed to by \p dstPtr, including any padding added to the end * of each row. This function performs fastest when the pitch is one that has * been passed back by ::cudaMallocPitch(). * * Note that this function is asynchronous with respect to the host unless * \p devPtr refers to pinned host memory. * * \param devPtr - Pointer to 2D device memory * \param pitch - Pitch in bytes of 2D device memory(Unused if \p height is 1) * \param value - Value to set for each byte of specified memory * \param width - Width of matrix set (columns in bytes) * \param height - Height of matrix set (rows) * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * \notefnerr * \note_memset * \note_init_rt * \note_callback * * \sa ::cudaMemset, ::cudaMemset3D, ::cudaMemsetAsync, * ::cudaMemset2DAsync, ::cudaMemset3DAsync, * ::cuMemsetD2D8, * ::cuMemsetD2D16, * ::cuMemsetD2D32 */ extern __host__ cudaError_t CUDARTAPI cudaMemset2D(void *devPtr, size_t pitch, int value, size_t width, size_t height); /** * \brief Initializes or sets device memory to a value * * Initializes each element of a 3D array to the specified value \p value. * The object to initialize is defined by \p pitchedDevPtr. The \p pitch field * of \p pitchedDevPtr is the width in memory in bytes of the 3D array pointed * to by \p pitchedDevPtr, including any padding added to the end of each row. * The \p xsize field specifies the logical width of each row in bytes, while * the \p ysize field specifies the height of each 2D slice in rows. * The \p pitch field of \p pitchedDevPtr is ignored when \p height and \p depth * are both equal to 1. * * The extents of the initialized region are specified as a \p width in bytes, * a \p height in rows, and a \p depth in slices. * * Extents with \p width greater than or equal to the \p xsize of * \p pitchedDevPtr may perform significantly faster than extents narrower * than the \p xsize. Secondarily, extents with \p height equal to the * \p ysize of \p pitchedDevPtr will perform faster than when the \p height is * shorter than the \p ysize. * * This function performs fastest when the \p pitchedDevPtr has been allocated * by ::cudaMalloc3D(). * * Note that this function is asynchronous with respect to the host unless * \p pitchedDevPtr refers to pinned host memory. * * \param pitchedDevPtr - Pointer to pitched device memory * \param value - Value to set for each byte of specified memory * \param extent - Size parameters for where to set device memory (\p width field in bytes) * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * \notefnerr * \note_memset * \note_init_rt * \note_callback * * \sa ::cudaMemset, ::cudaMemset2D, * ::cudaMemsetAsync, ::cudaMemset2DAsync, ::cudaMemset3DAsync, * ::cudaMalloc3D, ::make_cudaPitchedPtr, * ::make_cudaExtent */ extern __host__ cudaError_t CUDARTAPI cudaMemset3D(struct cudaPitchedPtr pitchedDevPtr, int value, struct cudaExtent extent); /** * \brief Initializes or sets device memory to a value * * Fills the first \p count bytes of the memory area pointed to by \p devPtr * with the constant byte value \p value. * * ::cudaMemsetAsync() is asynchronous with respect to the host, so * the call may return before the memset is complete. The operation can optionally * be associated to a stream by passing a non-zero \p stream argument. * If \p stream is non-zero, the operation may overlap with operations in other streams. * * The device version of this function only handles device to device copies and * cannot be given local or shared pointers. * * \param devPtr - Pointer to device memory * \param value - Value to set for each byte of specified memory * \param count - Size in bytes to set * \param stream - Stream identifier * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * \notefnerr * \note_memset * \note_null_stream * \note_init_rt * \note_callback * * \sa ::cudaMemset, ::cudaMemset2D, ::cudaMemset3D, * ::cudaMemset2DAsync, ::cudaMemset3DAsync, * ::cuMemsetD8Async, * ::cuMemsetD16Async, * ::cuMemsetD32Async */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemsetAsync(void *devPtr, int value, size_t count, cudaStream_t stream __dv(0)); /** * \brief Initializes or sets device memory to a value * * Sets to the specified value \p value a matrix (\p height rows of \p width * bytes each) pointed to by \p dstPtr. \p pitch is the width in bytes of the * 2D array pointed to by \p dstPtr, including any padding added to the end * of each row. This function performs fastest when the pitch is one that has * been passed back by ::cudaMallocPitch(). * * ::cudaMemset2DAsync() is asynchronous with respect to the host, so * the call may return before the memset is complete. The operation can optionally * be associated to a stream by passing a non-zero \p stream argument. * If \p stream is non-zero, the operation may overlap with operations in other streams. * * The device version of this function only handles device to device copies and * cannot be given local or shared pointers. * * \param devPtr - Pointer to 2D device memory * \param pitch - Pitch in bytes of 2D device memory(Unused if \p height is 1) * \param value - Value to set for each byte of specified memory * \param width - Width of matrix set (columns in bytes) * \param height - Height of matrix set (rows) * \param stream - Stream identifier * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * \notefnerr * \note_memset * \note_null_stream * \note_init_rt * \note_callback * * \sa ::cudaMemset, ::cudaMemset2D, ::cudaMemset3D, * ::cudaMemsetAsync, ::cudaMemset3DAsync, * ::cuMemsetD2D8Async, * ::cuMemsetD2D16Async, * ::cuMemsetD2D32Async */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemset2DAsync(void *devPtr, size_t pitch, int value, size_t width, size_t height, cudaStream_t stream __dv(0)); /** * \brief Initializes or sets device memory to a value * * Initializes each element of a 3D array to the specified value \p value. * The object to initialize is defined by \p pitchedDevPtr. The \p pitch field * of \p pitchedDevPtr is the width in memory in bytes of the 3D array pointed * to by \p pitchedDevPtr, including any padding added to the end of each row. * The \p xsize field specifies the logical width of each row in bytes, while * the \p ysize field specifies the height of each 2D slice in rows. * The \p pitch field of \p pitchedDevPtr is ignored when \p height and \p depth * are both equal to 1. * * The extents of the initialized region are specified as a \p width in bytes, * a \p height in rows, and a \p depth in slices. * * Extents with \p width greater than or equal to the \p xsize of * \p pitchedDevPtr may perform significantly faster than extents narrower * than the \p xsize. Secondarily, extents with \p height equal to the * \p ysize of \p pitchedDevPtr will perform faster than when the \p height is * shorter than the \p ysize. * * This function performs fastest when the \p pitchedDevPtr has been allocated * by ::cudaMalloc3D(). * * ::cudaMemset3DAsync() is asynchronous with respect to the host, so * the call may return before the memset is complete. The operation can optionally * be associated to a stream by passing a non-zero \p stream argument. * If \p stream is non-zero, the operation may overlap with operations in other streams. * * The device version of this function only handles device to device copies and * cannot be given local or shared pointers. * * \param pitchedDevPtr - Pointer to pitched device memory * \param value - Value to set for each byte of specified memory * \param extent - Size parameters for where to set device memory (\p width field in bytes) * \param stream - Stream identifier * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * \notefnerr * \note_memset * \note_null_stream * \note_init_rt * \note_callback * * \sa ::cudaMemset, ::cudaMemset2D, ::cudaMemset3D, * ::cudaMemsetAsync, ::cudaMemset2DAsync, * ::cudaMalloc3D, ::make_cudaPitchedPtr, * ::make_cudaExtent */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemset3DAsync(struct cudaPitchedPtr pitchedDevPtr, int value, struct cudaExtent extent, cudaStream_t stream __dv(0)); /** * \brief Finds the address associated with a CUDA symbol * * Returns in \p *devPtr the address of symbol \p symbol on the device. * \p symbol is a variable that resides in global or constant memory space. * If \p symbol cannot be found, or if \p symbol is not declared in the * global or constant memory space, \p *devPtr is unchanged and the error * ::cudaErrorInvalidSymbol is returned. * * \param devPtr - Return device pointer associated with symbol * \param symbol - Device symbol address * * \return * ::cudaSuccess, * ::cudaErrorInvalidSymbol, * ::cudaErrorNoKernelImageForDevice * \notefnerr * \note_string_api_deprecation * \note_init_rt * \note_callback * * \sa * \ref ::cudaGetSymbolAddress(void**, const T&) "cudaGetSymbolAddress (C++ API)", * \ref ::cudaGetSymbolSize(size_t*, const void*) "cudaGetSymbolSize (C API)", * ::cuModuleGetGlobal */ extern __host__ cudaError_t CUDARTAPI cudaGetSymbolAddress(void **devPtr, const void *symbol); /** * \brief Finds the size of the object associated with a CUDA symbol * * Returns in \p *size the size of symbol \p symbol. \p symbol is a variable that * resides in global or constant memory space. If \p symbol cannot be found, or * if \p symbol is not declared in global or constant memory space, \p *size is * unchanged and the error ::cudaErrorInvalidSymbol is returned. * * \param size - Size of object associated with symbol * \param symbol - Device symbol address * * \return * ::cudaSuccess, * ::cudaErrorInvalidSymbol, * ::cudaErrorNoKernelImageForDevice * \notefnerr * \note_string_api_deprecation * \note_init_rt * \note_callback * * \sa * \ref ::cudaGetSymbolAddress(void**, const void*) "cudaGetSymbolAddress (C API)", * \ref ::cudaGetSymbolSize(size_t*, const T&) "cudaGetSymbolSize (C++ API)", * ::cuModuleGetGlobal */ extern __host__ cudaError_t CUDARTAPI cudaGetSymbolSize(size_t *size, const void *symbol); /** * \brief Prefetches memory to the specified destination device * * Prefetches memory to the specified destination device. \p devPtr is the * base device pointer of the memory to be prefetched and \p dstDevice is the * destination device. \p count specifies the number of bytes to copy. \p stream * is the stream in which the operation is enqueued. The memory range must refer * to managed memory allocated via ::cudaMallocManaged or declared via __managed__ variables, * or it may also refer to system-allocated memory on systems with non-zero * cudaDevAttrPageableMemoryAccess. * * Passing in cudaCpuDeviceId for \p dstDevice will prefetch the data to host memory. If * \p dstDevice is a GPU, then the device attribute ::cudaDevAttrConcurrentManagedAccess * must be non-zero. Additionally, \p stream must be associated with a device that has a * non-zero value for the device attribute ::cudaDevAttrConcurrentManagedAccess. * * The start address and end address of the memory range will be rounded down and rounded up * respectively to be aligned to CPU page size before the prefetch operation is enqueued * in the stream. * * If no physical memory has been allocated for this region, then this memory region * will be populated and mapped on the destination device. If there's insufficient * memory to prefetch the desired region, the Unified Memory driver may evict pages from other * ::cudaMallocManaged allocations to host memory in order to make room. Device memory * allocated using ::cudaMalloc or ::cudaMallocArray will not be evicted. * * By default, any mappings to the previous location of the migrated pages are removed and * mappings for the new location are only setup on \p dstDevice. The exact behavior however * also depends on the settings applied to this memory range via ::cudaMemAdvise as described * below: * * If ::cudaMemAdviseSetReadMostly was set on any subset of this memory range, * then that subset will create a read-only copy of the pages on \p dstDevice. * * If ::cudaMemAdviseSetPreferredLocation was called on any subset of this memory * range, then the pages will be migrated to \p dstDevice even if \p dstDevice is not the * preferred location of any pages in the memory range. * * If ::cudaMemAdviseSetAccessedBy was called on any subset of this memory range, * then mappings to those pages from all the appropriate processors are updated to * refer to the new location if establishing such a mapping is possible. Otherwise, * those mappings are cleared. * * Note that this API is not required for functionality and only serves to improve performance * by allowing the application to migrate data to a suitable location before it is accessed. * Memory accesses to this range are always coherent and are allowed even when the data is * actively being migrated. * * Note that this function is asynchronous with respect to the host and all work * on other devices. * * \param devPtr - Pointer to be prefetched * \param count - Size in bytes * \param dstDevice - Destination device to prefetch to * \param stream - Stream to enqueue prefetch operation * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidDevice * \notefnerr * \note_async * \note_null_stream * \note_init_rt * \note_callback * * \sa ::cudaMemcpy, ::cudaMemcpyPeer, ::cudaMemcpyAsync, * ::cudaMemcpy3DPeerAsync, ::cudaMemAdvise, ::cudaMemAdvise_v2 * ::cuMemPrefetchAsync */ extern __host__ cudaError_t CUDARTAPI cudaMemPrefetchAsync(const void *devPtr, size_t count, int dstDevice, cudaStream_t stream __dv(0)); /** * \brief Prefetches memory to the specified destination location * * Prefetches memory to the specified destination location. \p devPtr is the * base device pointer of the memory to be prefetched and \p location specifies the * destination location. \p count specifies the number of bytes to copy. \p stream * is the stream in which the operation is enqueued. The memory range must refer * to managed memory allocated via ::cudaMallocManaged or declared via __managed__ variables, * or it may also refer to system-allocated memory on systems with non-zero * cudaDevAttrPageableMemoryAccess. * * Specifying ::cudaMemLocationTypeDevice for ::cudaMemLocation::type will prefetch memory to GPU * specified by device ordinal ::cudaMemLocation::id which must have non-zero value for the device attribute * ::concurrentManagedAccess. Additionally, \p stream must be associated with a device * that has a non-zero value for the device attribute ::concurrentManagedAccess. * Specifying ::cudaMemLocationTypeHost as ::cudaMemLocation::type will prefetch data to host memory. * Applications can request prefetching memory to a specific host NUMA node by specifying * ::cudaMemLocationTypeHostNuma for ::cudaMemLocation::type and a valid host NUMA node id in ::cudaMemLocation::id * Users can also request prefetching memory to the host NUMA node closest to the current thread's CPU by specifying * ::cudaMemLocationTypeHostNumaCurrent for ::cudaMemLocation::type. Note when ::cudaMemLocation::type is etiher * ::cudaMemLocationTypeHost OR ::cudaMemLocationTypeHostNumaCurrent, ::cudaMemLocation::id will be ignored. * * The start address and end address of the memory range will be rounded down and rounded up * respectively to be aligned to CPU page size before the prefetch operation is enqueued * in the stream. * * If no physical memory has been allocated for this region, then this memory region * will be populated and mapped on the destination device. If there's insufficient * memory to prefetch the desired region, the Unified Memory driver may evict pages from other * ::cudaMallocManaged allocations to host memory in order to make room. Device memory * allocated using ::cudaMalloc or ::cudaMallocArray will not be evicted. * * By default, any mappings to the previous location of the migrated pages are removed and * mappings for the new location are only setup on the destination location. The exact behavior however * also depends on the settings applied to this memory range via ::cuMemAdvise as described * below: * * If ::cudaMemAdviseSetReadMostly was set on any subset of this memory range, * then that subset will create a read-only copy of the pages on destination location. * If however the destination location is a host NUMA node, then any pages of that subset * that are already in another host NUMA node will be transferred to the destination. * * If ::cudaMemAdviseSetPreferredLocation was called on any subset of this memory * range, then the pages will be migrated to \p location even if \p location is not the * preferred location of any pages in the memory range. * * If ::cudaMemAdviseSetAccessedBy was called on any subset of this memory range, * then mappings to those pages from all the appropriate processors are updated to * refer to the new location if establishing such a mapping is possible. Otherwise, * those mappings are cleared. * * Note that this API is not required for functionality and only serves to improve performance * by allowing the application to migrate data to a suitable location before it is accessed. * Memory accesses to this range are always coherent and are allowed even when the data is * actively being migrated. * * Note that this function is asynchronous with respect to the host and all work * on other devices. * * \param devPtr - Pointer to be prefetched * \param count - Size in bytes * \param location - location to prefetch to * \param flags - flags for future use, must be zero now. * \param stream - Stream to enqueue prefetch operation * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidDevice * \notefnerr * \note_async * \note_null_stream * \note_init_rt * \note_callback * * \sa ::cudaMemcpy, ::cudaMemcpyPeer, ::cudaMemcpyAsync, * ::cudaMemcpy3DPeerAsync, ::cudaMemAdvise, ::cudaMemAdvise_v2 * ::cuMemPrefetchAsync */ extern __host__ cudaError_t CUDARTAPI cudaMemPrefetchAsync_v2(const void *devPtr, size_t count, struct cudaMemLocation location, unsigned int flags, cudaStream_t stream __dv(0)); /** * \brief Advise about the usage of a given memory range * * Advise the Unified Memory subsystem about the usage pattern for the memory range * starting at \p devPtr with a size of \p count bytes. The start address and end address of the memory * range will be rounded down and rounded up respectively to be aligned to CPU page size before the * advice is applied. The memory range must refer to managed memory allocated via ::cudaMallocManaged * or declared via __managed__ variables. The memory range could also refer to system-allocated pageable * memory provided it represents a valid, host-accessible region of memory and all additional constraints * imposed by \p advice as outlined below are also satisfied. Specifying an invalid system-allocated pageable * memory range results in an error being returned. * * The \p advice parameter can take the following values: * - ::cudaMemAdviseSetReadMostly: This implies that the data is mostly going to be read * from and only occasionally written to. Any read accesses from any processor to this region will create a * read-only copy of at least the accessed pages in that processor's memory. Additionally, if ::cudaMemPrefetchAsync * is called on this region, it will create a read-only copy of the data on the destination processor. * If any processor writes to this region, all copies of the corresponding page will be invalidated * except for the one where the write occurred. The \p device argument is ignored for this advice. * Note that for a page to be read-duplicated, the accessing processor must either be the CPU or a GPU * that has a non-zero value for the device attribute ::cudaDevAttrConcurrentManagedAccess. * Also, if a context is created on a device that does not have the device attribute * ::cudaDevAttrConcurrentManagedAccess set, then read-duplication will not occur until * all such contexts are destroyed. * If the memory region refers to valid system-allocated pageable memory, then the accessing device must * have a non-zero value for the device attribute ::cudaDevAttrPageableMemoryAccess for a read-only * copy to be created on that device. Note however that if the accessing device also has a non-zero value for the * device attribute ::cudaDevAttrPageableMemoryAccessUsesHostPageTables, then setting this advice * will not create a read-only copy when that device accesses this memory region. * * - ::cudaMemAdviceUnsetReadMostly: Undoes the effect of ::cudaMemAdviceReadMostly and also prevents the * Unified Memory driver from attempting heuristic read-duplication on the memory range. Any read-duplicated * copies of the data will be collapsed into a single copy. The location for the collapsed * copy will be the preferred location if the page has a preferred location and one of the read-duplicated * copies was resident at that location. Otherwise, the location chosen is arbitrary. * * - ::cudaMemAdviseSetPreferredLocation: This advice sets the preferred location for the * data to be the memory belonging to \p device. Passing in cudaCpuDeviceId for \p device sets the * preferred location as host memory. If \p device is a GPU, then it must have a non-zero value for the * device attribute ::cudaDevAttrConcurrentManagedAccess. Setting the preferred location * does not cause data to migrate to that location immediately. Instead, it guides the migration policy * when a fault occurs on that memory region. If the data is already in its preferred location and the * faulting processor can establish a mapping without requiring the data to be migrated, then * data migration will be avoided. On the other hand, if the data is not in its preferred location * or if a direct mapping cannot be established, then it will be migrated to the processor accessing * it. It is important to note that setting the preferred location does not prevent data prefetching * done using ::cudaMemPrefetchAsync. * Having a preferred location can override the page thrash detection and resolution logic in the Unified * Memory driver. Normally, if a page is detected to be constantly thrashing between for example host and device * memory, the page may eventually be pinned to host memory by the Unified Memory driver. But * if the preferred location is set as device memory, then the page will continue to thrash indefinitely. * If ::cudaMemAdviseSetReadMostly is also set on this memory region or any subset of it, then the * policies associated with that advice will override the policies of this advice, unless read accesses from * \p device will not result in a read-only copy being created on that device as outlined in description for * the advice ::cudaMemAdviseSetReadMostly. * If the memory region refers to valid system-allocated pageable memory, then \p device must have a non-zero * value for the device attribute ::cudaDevAttrPageableMemoryAccess. * * - ::cudaMemAdviseUnsetPreferredLocation: Undoes the effect of ::cudaMemAdviseSetPreferredLocation * and changes the preferred location to none. * * - ::cudaMemAdviseSetAccessedBy: This advice implies that the data will be accessed by \p device. * Passing in ::cudaCpuDeviceId for \p device will set the advice for the CPU. If \p device is a GPU, then * the device attribute ::cudaDevAttrConcurrentManagedAccess must be non-zero. * This advice does not cause data migration and has no impact on the location of the data per se. Instead, * it causes the data to always be mapped in the specified processor's page tables, as long as the * location of the data permits a mapping to be established. If the data gets migrated for any reason, * the mappings are updated accordingly. * This advice is recommended in scenarios where data locality is not important, but avoiding faults is. * Consider for example a system containing multiple GPUs with peer-to-peer access enabled, where the * data located on one GPU is occasionally accessed by peer GPUs. In such scenarios, migrating data * over to the other GPUs is not as important because the accesses are infrequent and the overhead of * migration may be too high. But preventing faults can still help improve performance, and so having * a mapping set up in advance is useful. Note that on CPU access of this data, the data may be migrated * to host memory because the CPU typically cannot access device memory directly. Any GPU that had the * ::cudaMemAdviceSetAccessedBy flag set for this data will now have its mapping updated to point to the * page in host memory. * If ::cudaMemAdviseSetReadMostly is also set on this memory region or any subset of it, then the * policies associated with that advice will override the policies of this advice. Additionally, if the * preferred location of this memory region or any subset of it is also \p device, then the policies * associated with ::cudaMemAdviseSetPreferredLocation will override the policies of this advice. * If the memory region refers to valid system-allocated pageable memory, then \p device must have a non-zero * value for the device attribute ::cudaDevAttrPageableMemoryAccess. Additionally, if \p device has * a non-zero value for the device attribute ::cudaDevAttrPageableMemoryAccessUsesHostPageTables, * then this call has no effect. * * - ::cudaMemAdviseUnsetAccessedBy: Undoes the effect of ::cudaMemAdviseSetAccessedBy. Any mappings to * the data from \p device may be removed at any time causing accesses to result in non-fatal page faults. * If the memory region refers to valid system-allocated pageable memory, then \p device must have a non-zero * value for the device attribute ::cudaDevAttrPageableMemoryAccess. Additionally, if \p device has * a non-zero value for the device attribute ::cudaDevAttrPageableMemoryAccessUsesHostPageTables, * then this call has no effect. * * \param devPtr - Pointer to memory to set the advice for * \param count - Size in bytes of the memory range * \param advice - Advice to be applied for the specified memory range * \param device - Device to apply the advice for * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidDevice * \notefnerr * \note_async * \note_null_stream * \note_init_rt * \note_callback * * \sa ::cudaMemcpy, ::cudaMemcpyPeer, ::cudaMemcpyAsync, * ::cudaMemcpy3DPeerAsync, ::cudaMemPrefetchAsync, * ::cuMemAdvise */ extern __host__ cudaError_t CUDARTAPI cudaMemAdvise(const void *devPtr, size_t count, enum cudaMemoryAdvise advice, int device); /** * \brief Advise about the usage of a given memory range * * Advise the Unified Memory subsystem about the usage pattern for the memory range * starting at \p devPtr with a size of \p count bytes. The start address and end address of the memory * range will be rounded down and rounded up respectively to be aligned to CPU page size before the * advice is applied. The memory range must refer to managed memory allocated via ::cudaMallocManaged * or declared via __managed__ variables. The memory range could also refer to system-allocated pageable * memory provided it represents a valid, host-accessible region of memory and all additional constraints * imposed by \p advice as outlined below are also satisfied. Specifying an invalid system-allocated pageable * memory range results in an error being returned. * * The \p advice parameter can take the following values: * - ::cudaMemAdviseSetReadMostly: This implies that the data is mostly going to be read * from and only occasionally written to. Any read accesses from any processor to this region will create a * read-only copy of at least the accessed pages in that processor's memory. Additionally, if ::cudaMemPrefetchAsync * or ::cudaMemPrefetchAsync_v2 is called on this region, it will create a read-only copy of the data on the destination processor. * If the target location for ::cudaMemPrefetchAsync_v2 is a host NUMA node and a read-only copy already exists on * another host NUMA node, that copy will be migrated to the targeted host NUMA node. * If any processor writes to this region, all copies of the corresponding page will be invalidated * except for the one where the write occurred. If the writing processor is the CPU and the preferred location of * the page is a host NUMA node, then the page will also be migrated to that host NUMA node. The \p location argument is ignored for this advice. * Note that for a page to be read-duplicated, the accessing processor must either be the CPU or a GPU * that has a non-zero value for the device attribute ::cudaDevAttrConcurrentManagedAccess. * Also, if a context is created on a device that does not have the device attribute * ::cudaDevAttrConcurrentManagedAccess set, then read-duplication will not occur until * all such contexts are destroyed. * If the memory region refers to valid system-allocated pageable memory, then the accessing device must * have a non-zero value for the device attribute ::cudaDevAttrPageableMemoryAccess for a read-only * copy to be created on that device. Note however that if the accessing device also has a non-zero value for the * device attribute ::cudaDevAttrPageableMemoryAccessUsesHostPageTables, then setting this advice * will not create a read-only copy when that device accesses this memory region. * * - ::cudaMemAdviceUnsetReadMostly: Undoes the effect of ::cudaMemAdviseSetReadMostly and also prevents the * Unified Memory driver from attempting heuristic read-duplication on the memory range. Any read-duplicated * copies of the data will be collapsed into a single copy. The location for the collapsed * copy will be the preferred location if the page has a preferred location and one of the read-duplicated * copies was resident at that location. Otherwise, the location chosen is arbitrary. * Note: The \p location argument is ignored for this advice. * * - ::cudaMemAdviseSetPreferredLocation: This advice sets the preferred location for the * data to be the memory belonging to \p location. When ::cudaMemLocation::type is ::cudaMemLocationTypeHost, * ::cudaMemLocation::id is ignored and the preferred location is set to be host memory. To set the preferred location * to a specific host NUMA node, applications must set ::cudaMemLocation::type to ::cudaMemLocationTypeHostNuma and * ::cudaMemLocation::id must specify the NUMA ID of the host NUMA node. If ::cudaMemLocation::type is set to ::cudaMemLocationTypeHostNumaCurrent, * ::cudaMemLocation::id will be ignored and the host NUMA node closest to the calling thread's CPU will be used as the preferred location. * If ::cudaMemLocation::type is a ::cudaMemLocationTypeDevice, then ::cudaMemLocation::id must be a valid device ordinal * and the device must have a non-zero value for the device attribute ::cudaDevAttrConcurrentManagedAccess. * Setting the preferred location does not cause data to migrate to that location immediately. Instead, it guides the migration policy * when a fault occurs on that memory region. If the data is already in its preferred location and the * faulting processor can establish a mapping without requiring the data to be migrated, then * data migration will be avoided. On the other hand, if the data is not in its preferred location * or if a direct mapping cannot be established, then it will be migrated to the processor accessing * it. It is important to note that setting the preferred location does not prevent data prefetching * done using ::cudaMemPrefetchAsync. * Having a preferred location can override the page thrash detection and resolution logic in the Unified * Memory driver. Normally, if a page is detected to be constantly thrashing between for example host and device * memory, the page may eventually be pinned to host memory by the Unified Memory driver. But * if the preferred location is set as device memory, then the page will continue to thrash indefinitely. * If ::cudaMemAdviseSetReadMostly is also set on this memory region or any subset of it, then the * policies associated with that advice will override the policies of this advice, unless read accesses from * \p location will not result in a read-only copy being created on that procesor as outlined in description for * the advice ::cudaMemAdviseSetReadMostly. * If the memory region refers to valid system-allocated pageable memory, and ::cudaMemLocation::type is ::cudaMemLocationTypeDevice * then ::cudaMemLocation::id must be a valid device that has a non-zero alue for the device attribute ::cudaDevAttrPageableMemoryAccess. * * - ::cudaMemAdviseUnsetPreferredLocation: Undoes the effect of ::cudaMemAdviseSetPreferredLocation * and changes the preferred location to none. The \p location argument is ignored for this advice. * * - ::cudaMemAdviseSetAccessedBy: This advice implies that the data will be accessed by processor \p location. * The ::cudaMemLocation::type must be either ::cudaMemLocationTypeDevice with ::cudaMemLocation::id representing a valid device * ordinal or ::cudaMemLocationTypeHost and ::cudaMemLocation::id will be ignored. All other location types are invalid. * If ::cudaMemLocation::id is a GPU, then the device attribute ::cudaDevAttrConcurrentManagedAccess must be non-zero. * This advice does not cause data migration and has no impact on the location of the data per se. Instead, * it causes the data to always be mapped in the specified processor's page tables, as long as the * location of the data permits a mapping to be established. If the data gets migrated for any reason, * the mappings are updated accordingly. * This advice is recommended in scenarios where data locality is not important, but avoiding faults is. * Consider for example a system containing multiple GPUs with peer-to-peer access enabled, where the * data located on one GPU is occasionally accessed by peer GPUs. In such scenarios, migrating data * over to the other GPUs is not as important because the accesses are infrequent and the overhead of * migration may be too high. But preventing faults can still help improve performance, and so having * a mapping set up in advance is useful. Note that on CPU access of this data, the data may be migrated * to host memory because the CPU typically cannot access device memory directly. Any GPU that had the * ::cudaMemAdviseSetAccessedBy flag set for this data will now have its mapping updated to point to the * page in host memory. * If ::cudaMemAdviseSetReadMostly is also set on this memory region or any subset of it, then the * policies associated with that advice will override the policies of this advice. Additionally, if the * preferred location of this memory region or any subset of it is also \p location, then the policies * associated with ::CU_MEM_ADVISE_SET_PREFERRED_LOCATION will override the policies of this advice. * If the memory region refers to valid system-allocated pageable memory, and ::cudaMemLocation::type is ::cudaMemLocationTypeDevice * then device in ::cudaMemLocation::id must have a non-zero value for the device attribute ::cudaDevAttrPageableMemoryAccess. * Additionally, if ::cudaMemLocation::id has a non-zero value for the device attribute ::cudaDevAttrPageableMemoryAccessUsesHostPageTables, * then this call has no effect. * * - ::CU_MEM_ADVISE_UNSET_ACCESSED_BY: Undoes the effect of ::cudaMemAdviseSetAccessedBy. Any mappings to * the data from \p location may be removed at any time causing accesses to result in non-fatal page faults. * If the memory region refers to valid system-allocated pageable memory, and ::cudaMemLocation::type is ::cudaMemLocationTypeDevice * then device in ::cudaMemLocation::id must have a non-zero value for the device attribute ::cudaDevAttrPageableMemoryAccess. * Additionally, if ::cudaMemLocation::id has a non-zero value for the device attribute ::cudaDevAttrPageableMemoryAccessUsesHostPageTables, * then this call has no effect. * * \param devPtr - Pointer to memory to set the advice for * \param count - Size in bytes of the memory range * \param advice - Advice to be applied for the specified memory range * \param location - location to apply the advice for * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidDevice * \notefnerr * \note_async * \note_null_stream * \note_init_rt * \note_callback * * \sa ::cudaMemcpy, ::cudaMemcpyPeer, ::cudaMemcpyAsync, * ::cudaMemcpy3DPeerAsync, ::cudaMemPrefetchAsync, * ::cuMemAdvise, ::cuMemAdvise_v2 */ extern __host__ cudaError_t CUDARTAPI cudaMemAdvise_v2(const void *devPtr, size_t count, enum cudaMemoryAdvise advice, struct cudaMemLocation location); /** * \brief Query an attribute of a given memory range * * Query an attribute about the memory range starting at \p devPtr with a size of \p count bytes. The * memory range must refer to managed memory allocated via ::cudaMallocManaged or declared via * __managed__ variables. * * The \p attribute parameter can take the following values: * - ::cudaMemRangeAttributeReadMostly: If this attribute is specified, \p data will be interpreted * as a 32-bit integer, and \p dataSize must be 4. The result returned will be 1 if all pages in the given * memory range have read-duplication enabled, or 0 otherwise. * - ::cudaMemRangeAttributePreferredLocation: If this attribute is specified, \p data will be * interpreted as a 32-bit integer, and \p dataSize must be 4. The result returned will be a GPU device * id if all pages in the memory range have that GPU as their preferred location, or it will be cudaCpuDeviceId * if all pages in the memory range have the CPU as their preferred location, or it will be cudaInvalidDeviceId * if either all the pages don't have the same preferred location or some of the pages don't have a * preferred location at all. Note that the actual location of the pages in the memory range at the time of * the query may be different from the preferred location. * - ::cudaMemRangeAttributeAccessedBy: If this attribute is specified, \p data will be interpreted * as an array of 32-bit integers, and \p dataSize must be a non-zero multiple of 4. The result returned * will be a list of device ids that had ::cudaMemAdviceSetAccessedBy set for that entire memory range. * If any device does not have that advice set for the entire memory range, that device will not be included. * If \p data is larger than the number of devices that have that advice set for that memory range, * cudaInvalidDeviceId will be returned in all the extra space provided. For ex., if \p dataSize is 12 * (i.e. \p data has 3 elements) and only device 0 has the advice set, then the result returned will be * { 0, cudaInvalidDeviceId, cudaInvalidDeviceId }. If \p data is smaller than the number of devices that have * that advice set, then only as many devices will be returned as can fit in the array. There is no * guarantee on which specific devices will be returned, however. * - ::cudaMemRangeAttributeLastPrefetchLocation: If this attribute is specified, \p data will be * interpreted as a 32-bit integer, and \p dataSize must be 4. The result returned will be the last location * to which all pages in the memory range were prefetched explicitly via ::cudaMemPrefetchAsync. This will either be * a GPU id or cudaCpuDeviceId depending on whether the last location for prefetch was a GPU or the CPU * respectively. If any page in the memory range was never explicitly prefetched or if all pages were not * prefetched to the same location, cudaInvalidDeviceId will be returned. Note that this simply returns the * last location that the applicaton requested to prefetch the memory range to. It gives no indication as to * whether the prefetch operation to that location has completed or even begun. * - ::cudaMemRangeAttributePreferredLocationType: If this attribute is specified, \p data will be * interpreted as a ::cudaMemLocationType, and \p dataSize must be sizeof(cudaMemLocationType). The ::cudaMemLocationType returned will be * ::cudaMemLocationTypeDevice if all pages in the memory range have the same GPU as their preferred location, or ::cudaMemLocationType * will be ::cudaMemLocationTypeHost if all pages in the memory range have the CPU as their preferred location, or or it will be ::cudaMemLocationTypeHostNuma * if all the pages in the memory range have the same host NUMA node ID as their preferred location or it will be ::cudaMemLocationTypeInvalid * if either all the pages don't have the same preferred location or some of the pages don't have a preferred location at all. * Note that the actual location type of the pages in the memory range at the time of the query may be different from the preferred location type. * - ::cudaMemRangeAttributePreferredLocationId: If this attribute is specified, \p data will be * interpreted as a 32-bit integer, and \p dataSize must be 4. If the ::cudaMemRangeAttributePreferredLocationType query for the same address range * returns ::cudaMemLocationTypeDevice, it will be a valid device ordinal or if it returns ::cudaMemLocationTypeHostNuma, it will be a valid host NUMA node ID * or if it returns any other location type, the id should be ignored. * - ::cudaMemRangeAttributeLastPrefetchLocationType: If this attribute is specified, \p data will be * interpreted as a ::cudaMemLocationType, and \p dataSize must be sizeof(cudaMemLocationType). The result returned will be the last location type * to which all pages in the memory range were prefetched explicitly via ::cuMemPrefetchAsync. The ::cudaMemLocationType returned * will be ::cudaMemLocationTypeDevice if the last prefetch location was the GPU or ::cudaMemLocationTypeHost if it was the CPU or ::cudaMemLocationTypeHostNuma if * the last prefetch location was a specific host NUMA node. If any page in the memory range was never explicitly prefetched or if all pages were not * prefetched to the same location, ::CUmemLocationType will be ::cudaMemLocationTypeInvalid. * Note that this simply returns the last location type that the application requested to prefetch the memory range to. It gives no indication as to * whether the prefetch operation to that location has completed or even begun. * - ::cudaMemRangeAttributeLastPrefetchLocationId: If this attribute is specified, \p data will be * interpreted as a 32-bit integer, and \p dataSize must be 4. If the ::cudaMemRangeAttributeLastPrefetchLocationType query for the same address range * returns ::cudaMemLocationTypeDevice, it will be a valid device ordinal or if it returns ::cudaMemLocationTypeHostNuma, it will be a valid host NUMA node ID * or if it returns any other location type, the id should be ignored. * * \param data - A pointers to a memory location where the result * of each attribute query will be written to. * \param dataSize - Array containing the size of data * \param attribute - The attribute to query * \param devPtr - Start of the range to query * \param count - Size of the range to query * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * \note_async * \note_null_stream * \note_init_rt * \note_callback * * \sa ::cudaMemRangeGetAttributes, ::cudaMemPrefetchAsync, * ::cudaMemAdvise, * ::cuMemRangeGetAttribute */ extern __host__ cudaError_t CUDARTAPI cudaMemRangeGetAttribute(void *data, size_t dataSize, enum cudaMemRangeAttribute attribute, const void *devPtr, size_t count); /** * \brief Query attributes of a given memory range. * * Query attributes of the memory range starting at \p devPtr with a size of \p count bytes. The * memory range must refer to managed memory allocated via ::cudaMallocManaged or declared via * __managed__ variables. The \p attributes array will be interpreted to have \p numAttributes * entries. The \p dataSizes array will also be interpreted to have \p numAttributes entries. * The results of the query will be stored in \p data. * * The list of supported attributes are given below. Please refer to ::cudaMemRangeGetAttribute for * attribute descriptions and restrictions. * * - ::cudaMemRangeAttributeReadMostly * - ::cudaMemRangeAttributePreferredLocation * - ::cudaMemRangeAttributeAccessedBy * - ::cudaMemRangeAttributeLastPrefetchLocation * - :: cudaMemRangeAttributePreferredLocationType * - :: cudaMemRangeAttributePreferredLocationId * - :: cudaMemRangeAttributeLastPrefetchLocationType * - :: cudaMemRangeAttributeLastPrefetchLocationId * * \param data - A two-dimensional array containing pointers to memory * locations where the result of each attribute query will be written to. * \param dataSizes - Array containing the sizes of each result * \param attributes - An array of attributes to query * (numAttributes and the number of attributes in this array should match) * \param numAttributes - Number of attributes to query * \param devPtr - Start of the range to query * \param count - Size of the range to query * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaMemRangeGetAttribute, ::cudaMemAdvise, * ::cudaMemPrefetchAsync, * ::cuMemRangeGetAttributes */ extern __host__ cudaError_t CUDARTAPI cudaMemRangeGetAttributes(void **data, size_t *dataSizes, enum cudaMemRangeAttribute *attributes, size_t numAttributes, const void *devPtr, size_t count); /** @} */ /* END CUDART_MEMORY */ /** * \defgroup CUDART_MEMORY_DEPRECATED Memory Management [DEPRECATED] * * ___MANBRIEF___ deprecated memory management functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes deprecated memory management functions of the CUDA runtime * application programming interface. * * Some functions have overloaded C++ API template versions documented separately in the * \ref CUDART_HIGHLEVEL "C++ API Routines" module. * * @{ */ /** * \brief Copies data between host and device * * \deprecated * * Copies \p count bytes from the memory area pointed to by \p src to the * CUDA array \p dst starting at \p hOffset rows and \p wOffset bytes from * the upper left corner, where \p kind specifies the direction * of the copy, and must be one of ::cudaMemcpyHostToHost, * ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost, * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing * ::cudaMemcpyDefault is recommended, in which case the type of transfer is * inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. * * \param dst - Destination memory address * \param wOffset - Destination starting X offset (columns in bytes) * \param hOffset - Destination starting Y offset (rows) * \param src - Source memory address * \param count - Size in bytes to copy * \param kind - Type of transfer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidMemcpyDirection * \notefnerr * \note_sync * \note_init_rt * \note_callback * * \sa ::cudaMemcpy, ::cudaMemcpy2D, * ::cudaMemcpy2DToArray, ::cudaMemcpyFromArray, ::cudaMemcpy2DFromArray, * ::cudaMemcpyArrayToArray, ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol, * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync, * ::cudaMemcpyToArrayAsync, ::cudaMemcpy2DToArrayAsync, * ::cudaMemcpyFromArrayAsync, ::cudaMemcpy2DFromArrayAsync, * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync, * ::cuMemcpyHtoA, * ::cuMemcpyDtoA */ extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaMemcpyToArray(cudaArray_t dst, size_t wOffset, size_t hOffset, const void *src, size_t count, enum cudaMemcpyKind kind); /** * \brief Copies data between host and device * * \deprecated * * Copies \p count bytes from the CUDA array \p src starting at \p hOffset rows * and \p wOffset bytes from the upper left corner to the memory area pointed to * by \p dst, where \p kind specifies the direction of the copy, and must be one of * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost, * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing * ::cudaMemcpyDefault is recommended, in which case the type of transfer is * inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. * * \param dst - Destination memory address * \param src - Source memory address * \param wOffset - Source starting X offset (columns in bytes) * \param hOffset - Source starting Y offset (rows) * \param count - Size in bytes to copy * \param kind - Type of transfer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidMemcpyDirection * \notefnerr * \note_sync * \note_init_rt * \note_callback * * \sa ::cudaMemcpy, ::cudaMemcpy2D, ::cudaMemcpyToArray, * ::cudaMemcpy2DToArray, ::cudaMemcpy2DFromArray, * ::cudaMemcpyArrayToArray, ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol, * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync, * ::cudaMemcpyToArrayAsync, ::cudaMemcpy2DToArrayAsync, * ::cudaMemcpyFromArrayAsync, ::cudaMemcpy2DFromArrayAsync, * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync, * ::cuMemcpyAtoH, * ::cuMemcpyAtoD */ extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaMemcpyFromArray(void *dst, cudaArray_const_t src, size_t wOffset, size_t hOffset, size_t count, enum cudaMemcpyKind kind); /** * \brief Copies data between host and device * * \deprecated * * Copies \p count bytes from the CUDA array \p src starting at \p hOffsetSrc * rows and \p wOffsetSrc bytes from the upper left corner to the CUDA array * \p dst starting at \p hOffsetDst rows and \p wOffsetDst bytes from the upper * left corner, where \p kind specifies the direction of the copy, and must be one of * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost, * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing * ::cudaMemcpyDefault is recommended, in which case the type of transfer is * inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. * * \param dst - Destination memory address * \param wOffsetDst - Destination starting X offset (columns in bytes) * \param hOffsetDst - Destination starting Y offset (rows) * \param src - Source memory address * \param wOffsetSrc - Source starting X offset (columns in bytes) * \param hOffsetSrc - Source starting Y offset (rows) * \param count - Size in bytes to copy * \param kind - Type of transfer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidMemcpyDirection * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaMemcpy, ::cudaMemcpy2D, ::cudaMemcpyToArray, * ::cudaMemcpy2DToArray, ::cudaMemcpyFromArray, ::cudaMemcpy2DFromArray, * ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol, * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync, * ::cudaMemcpyToArrayAsync, ::cudaMemcpy2DToArrayAsync, * ::cudaMemcpyFromArrayAsync, ::cudaMemcpy2DFromArrayAsync, * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync, * ::cuMemcpyAtoA */ extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaMemcpyArrayToArray(cudaArray_t dst, size_t wOffsetDst, size_t hOffsetDst, cudaArray_const_t src, size_t wOffsetSrc, size_t hOffsetSrc, size_t count, enum cudaMemcpyKind kind __dv(cudaMemcpyDeviceToDevice)); /** * \brief Copies data between host and device * * \deprecated * * Copies \p count bytes from the memory area pointed to by \p src to the * CUDA array \p dst starting at \p hOffset rows and \p wOffset bytes from * the upper left corner, where \p kind specifies the * direction of the copy, and must be one of ::cudaMemcpyHostToHost, * ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost, * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing * ::cudaMemcpyDefault is recommended, in which case the type of transfer is * inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. * * ::cudaMemcpyToArrayAsync() is asynchronous with respect to the host, so * the call may return before the copy is complete. The copy can optionally * be associated to a stream by passing a non-zero \p stream argument. If \p * kind is ::cudaMemcpyHostToDevice or ::cudaMemcpyDeviceToHost and \p stream * is non-zero, the copy may overlap with operations in other streams. * * \param dst - Destination memory address * \param wOffset - Destination starting X offset (columns in bytes) * \param hOffset - Destination starting Y offset (rows) * \param src - Source memory address * \param count - Size in bytes to copy * \param kind - Type of transfer * \param stream - Stream identifier * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidMemcpyDirection * \notefnerr * \note_async * \note_null_stream * \note_init_rt * \note_callback * * \sa ::cudaMemcpy, ::cudaMemcpy2D, ::cudaMemcpyToArray, * ::cudaMemcpy2DToArray, ::cudaMemcpyFromArray, ::cudaMemcpy2DFromArray, * ::cudaMemcpyArrayToArray, ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol, * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync, * ::cudaMemcpy2DToArrayAsync, * ::cudaMemcpyFromArrayAsync, ::cudaMemcpy2DFromArrayAsync, * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync, * ::cuMemcpyHtoAAsync, * ::cuMemcpy2DAsync */ extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaMemcpyToArrayAsync(cudaArray_t dst, size_t wOffset, size_t hOffset, const void *src, size_t count, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0)); /** * \brief Copies data between host and device * * \deprecated * * Copies \p count bytes from the CUDA array \p src starting at \p hOffset rows * and \p wOffset bytes from the upper left corner to the memory area pointed to * by \p dst, where \p kind specifies the direction of the copy, and must be one of * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost, * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing * ::cudaMemcpyDefault is recommended, in which case the type of transfer is * inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. * * ::cudaMemcpyFromArrayAsync() is asynchronous with respect to the host, so * the call may return before the copy is complete. The copy can optionally * be associated to a stream by passing a non-zero \p stream argument. If \p * kind is ::cudaMemcpyHostToDevice or ::cudaMemcpyDeviceToHost and \p stream * is non-zero, the copy may overlap with operations in other streams. * * \param dst - Destination memory address * \param src - Source memory address * \param wOffset - Source starting X offset (columns in bytes) * \param hOffset - Source starting Y offset (rows) * \param count - Size in bytes to copy * \param kind - Type of transfer * \param stream - Stream identifier * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidMemcpyDirection * \notefnerr * \note_async * \note_null_stream * \note_init_rt * \note_callback * * \sa ::cudaMemcpy, ::cudaMemcpy2D, ::cudaMemcpyToArray, * ::cudaMemcpy2DToArray, ::cudaMemcpyFromArray, ::cudaMemcpy2DFromArray, * ::cudaMemcpyArrayToArray, ::cudaMemcpy2DArrayToArray, ::cudaMemcpyToSymbol, * ::cudaMemcpyFromSymbol, ::cudaMemcpyAsync, ::cudaMemcpy2DAsync, * ::cudaMemcpyToArrayAsync, ::cudaMemcpy2DToArrayAsync, * ::cudaMemcpy2DFromArrayAsync, * ::cudaMemcpyToSymbolAsync, ::cudaMemcpyFromSymbolAsync, * ::cuMemcpyAtoHAsync, * ::cuMemcpy2DAsync */ extern __CUDA_DEPRECATED __host__ cudaError_t CUDARTAPI cudaMemcpyFromArrayAsync(void *dst, cudaArray_const_t src, size_t wOffset, size_t hOffset, size_t count, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0)); /** @} */ /* END CUDART_MEMORY_DEPRECATED */ /** * \defgroup CUDART_MEMORY_POOLS Stream Ordered Memory Allocator * * ___MANBRIEF___ Functions for performing allocation and free operations in stream order. * Functions for controlling the behavior of the underlying allocator. * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * * @{ * * \section CUDART_MEMORY_POOLS_overview overview * * The asynchronous allocator allows the user to allocate and free in stream order. * All asynchronous accesses of the allocation must happen between * the stream executions of the allocation and the free. If the memory is accessed * outside of the promised stream order, a use before allocation / use after free error * will cause undefined behavior. * * The allocator is free to reallocate the memory as long as it can guarantee * that compliant memory accesses will not overlap temporally. * The allocator may refer to internal stream ordering as well as inter-stream dependencies * (such as CUDA events and null stream dependencies) when establishing the temporal guarantee. * The allocator may also insert inter-stream dependencies to establish the temporal guarantee. * * \section CUDART_MEMORY_POOLS_support Supported Platforms * * Whether or not a device supports the integrated stream ordered memory allocator * may be queried by calling ::cudaDeviceGetAttribute() with the device attribute * ::cudaDevAttrMemoryPoolsSupported. */ /** * \brief Allocates memory with stream ordered semantics * * Inserts an allocation operation into \p hStream. * A pointer to the allocated memory is returned immediately in *dptr. * The allocation must not be accessed until the the allocation operation completes. * The allocation comes from the memory pool associated with the stream's device. * * \note The default memory pool of a device contains device memory from that device. * \note Basic stream ordering allows future work submitted into the same stream to use the allocation. * Stream query, stream synchronize, and CUDA events can be used to guarantee that the allocation * operation completes before work submitted in a separate stream runs. * \note During stream capture, this function results in the creation of an allocation node. In this case, * the allocation is owned by the graph instead of the memory pool. The memory pool's properties * are used to set the node's creation parameters. * * \param[out] devPtr - Returned device pointer * \param[in] size - Number of bytes to allocate * \param[in] hStream - The stream establishing the stream ordering contract and the memory pool to allocate from * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorNotSupported, * ::cudaErrorOutOfMemory, * \notefnerr * \note_null_stream * \note_init_rt * \note_callback * * \sa ::cuMemAllocAsync, * \ref ::cudaMallocAsync(void** ptr, size_t size, cudaMemPool_t memPool, cudaStream_t stream) "cudaMallocAsync (C++ API)", * ::cudaMallocFromPoolAsync, ::cudaFreeAsync, ::cudaDeviceSetMemPool, ::cudaDeviceGetDefaultMemPool, ::cudaDeviceGetMemPool, ::cudaMemPoolSetAccess, ::cudaMemPoolSetAttribute, ::cudaMemPoolGetAttribute */ extern __host__ cudaError_t CUDARTAPI cudaMallocAsync(void **devPtr, size_t size, cudaStream_t hStream); /** * \brief Frees memory with stream ordered semantics * * Inserts a free operation into \p hStream. * The allocation must not be accessed after stream execution reaches the free. * After this API returns, accessing the memory from any subsequent work launched on the GPU * or querying its pointer attributes results in undefined behavior. * * \note During stream capture, this function results in the creation of a free node and * must therefore be passed the address of a graph allocation. * * \param dptr - memory to free * \param hStream - The stream establishing the stream ordering promise * \returns * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorNotSupported * \notefnerr * \note_null_stream * \note_init_rt * \note_callback * * \sa ::cuMemFreeAsync, ::cudaMallocAsync */ extern __host__ cudaError_t CUDARTAPI cudaFreeAsync(void *devPtr, cudaStream_t hStream); /** * \brief Tries to release memory back to the OS * * Releases memory back to the OS until the pool contains fewer than minBytesToKeep * reserved bytes, or there is no more memory that the allocator can safely release. * The allocator cannot release OS allocations that back outstanding asynchronous allocations. * The OS allocations may happen at different granularity from the user allocations. * * \note: Allocations that have not been freed count as outstanding. * \note: Allocations that have been asynchronously freed but whose completion has * not been observed on the host (eg. by a synchronize) can count as outstanding. * * \param[in] pool - The memory pool to trim * \param[in] minBytesToKeep - If the pool has less than minBytesToKeep reserved, * the TrimTo operation is a no-op. Otherwise the pool will be guaranteed to have * at least minBytesToKeep bytes reserved after the operation. * \returns * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_callback * * \sa ::cuMemPoolTrimTo, ::cudaMallocAsync, ::cudaFreeAsync, ::cudaDeviceGetDefaultMemPool, ::cudaDeviceGetMemPool, ::cudaMemPoolCreate */ extern __host__ cudaError_t CUDARTAPI cudaMemPoolTrimTo(cudaMemPool_t memPool, size_t minBytesToKeep); /** * \brief Sets attributes of a memory pool * * Supported attributes are: * - ::cudaMemPoolAttrReleaseThreshold: (value type = cuuint64_t) * Amount of reserved memory in bytes to hold onto before trying * to release memory back to the OS. When more than the release * threshold bytes of memory are held by the memory pool, the * allocator will try to release memory back to the OS on the * next call to stream, event or context synchronize. (default 0) * - ::cudaMemPoolReuseFollowEventDependencies: (value type = int) * Allow ::cudaMallocAsync to use memory asynchronously freed * in another stream as long as a stream ordering dependency * of the allocating stream on the free action exists. * Cuda events and null stream interactions can create the required * stream ordered dependencies. (default enabled) * - ::cudaMemPoolReuseAllowOpportunistic: (value type = int) * Allow reuse of already completed frees when there is no dependency * between the free and allocation. (default enabled) * - ::cudaMemPoolReuseAllowInternalDependencies: (value type = int) * Allow ::cudaMallocAsync to insert new stream dependencies * in order to establish the stream ordering required to reuse * a piece of memory released by ::cudaFreeAsync (default enabled). * - ::cudaMemPoolAttrReservedMemHigh: (value type = cuuint64_t) * Reset the high watermark that tracks the amount of backing memory that was * allocated for the memory pool. It is illegal to set this attribute to a non-zero value. * - ::cudaMemPoolAttrUsedMemHigh: (value type = cuuint64_t) * Reset the high watermark that tracks the amount of used memory that was * allocated for the memory pool. It is illegal to set this attribute to a non-zero value. * * \param[in] pool - The memory pool to modify * \param[in] attr - The attribute to modify * \param[in] value - Pointer to the value to assign * * \returns * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_callback * * \sa ::cuMemPoolSetAttribute, ::cudaMallocAsync, ::cudaFreeAsync, ::cudaDeviceGetDefaultMemPool, ::cudaDeviceGetMemPool, ::cudaMemPoolCreate */ extern __host__ cudaError_t CUDARTAPI cudaMemPoolSetAttribute(cudaMemPool_t memPool, enum cudaMemPoolAttr attr, void *value ); /** * \brief Gets attributes of a memory pool * * Supported attributes are: * - ::cudaMemPoolAttrReleaseThreshold: (value type = cuuint64_t) * Amount of reserved memory in bytes to hold onto before trying * to release memory back to the OS. When more than the release * threshold bytes of memory are held by the memory pool, the * allocator will try to release memory back to the OS on the * next call to stream, event or context synchronize. (default 0) * - ::cudaMemPoolReuseFollowEventDependencies: (value type = int) * Allow ::cudaMallocAsync to use memory asynchronously freed * in another stream as long as a stream ordering dependency * of the allocating stream on the free action exists. * Cuda events and null stream interactions can create the required * stream ordered dependencies. (default enabled) * - ::cudaMemPoolReuseAllowOpportunistic: (value type = int) * Allow reuse of already completed frees when there is no dependency * between the free and allocation. (default enabled) * - ::cudaMemPoolReuseAllowInternalDependencies: (value type = int) * Allow ::cudaMallocAsync to insert new stream dependencies * in order to establish the stream ordering required to reuse * a piece of memory released by ::cudaFreeAsync (default enabled). * - ::cudaMemPoolAttrReservedMemCurrent: (value type = cuuint64_t) * Amount of backing memory currently allocated for the mempool. * - ::cudaMemPoolAttrReservedMemHigh: (value type = cuuint64_t) * High watermark of backing memory allocated for the mempool since * the last time it was reset. * - ::cudaMemPoolAttrUsedMemCurrent: (value type = cuuint64_t) * Amount of memory from the pool that is currently in use by the application. * - ::cudaMemPoolAttrUsedMemHigh: (value type = cuuint64_t) * High watermark of the amount of memory from the pool that was in use by the * application since the last time it was reset. * * \param[in] pool - The memory pool to get attributes of * \param[in] attr - The attribute to get * \param[in] value - Retrieved value * * \returns * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_callback * * \sa ::cuMemPoolGetAttribute, ::cudaMallocAsync, ::cudaFreeAsync, ::cudaDeviceGetDefaultMemPool, ::cudaDeviceGetMemPool, ::cudaMemPoolCreate */ extern __host__ cudaError_t CUDARTAPI cudaMemPoolGetAttribute(cudaMemPool_t memPool, enum cudaMemPoolAttr attr, void *value ); /** * \brief Controls visibility of pools between devices * * \param[in] pool - The pool being modified * \param[in] map - Array of access descriptors. Each descriptor instructs the access to enable for a single gpu * \param[in] count - Number of descriptors in the map array. * * \returns * ::cudaSuccess, * ::cudaErrorInvalidValue * * \sa ::cuMemPoolSetAccess, ::cudaMemPoolGetAccess, ::cudaMallocAsync, cudaFreeAsync */ extern __host__ cudaError_t CUDARTAPI cudaMemPoolSetAccess(cudaMemPool_t memPool, const struct cudaMemAccessDesc *descList, size_t count); /** * \brief Returns the accessibility of a pool from a device * * Returns the accessibility of the pool's memory from the specified location. * * \param[out] flags - the accessibility of the pool from the specified location * \param[in] memPool - the pool being queried * \param[in] location - the location accessing the pool * * \sa ::cuMemPoolGetAccess, ::cudaMemPoolSetAccess */ extern __host__ cudaError_t CUDARTAPI cudaMemPoolGetAccess(enum cudaMemAccessFlags *flags, cudaMemPool_t memPool, struct cudaMemLocation *location); /** * \brief Creates a memory pool * * Creates a CUDA memory pool and returns the handle in \p pool. The \p poolProps determines * the properties of the pool such as the backing device and IPC capabilities. * * To create a memory pool targeting a specific host NUMA node, applications must * set ::cudaMemPoolProps::cudaMemLocation::type to ::cudaMemLocationTypeHostNuma and * ::cudaMemPoolProps::cudaMemLocation::id must specify the NUMA ID of the host memory node. * Specifying ::cudaMemLocationTypeHostNumaCurrent or ::cudaMemLocationTypeHost as the * ::cudaMemPoolProps::cudaMemLocation::type will result in ::cudaErrorInvalidValue. * By default, the pool's memory will be accessible from the device it is allocated on. * In the case of pools created with ::cudaMemLocationTypeHostNuma, their default accessibility * will be from the host CPU. * Applications can control the maximum size of the pool by specifying a non-zero value for ::cudaMemPoolProps::maxSize. * If set to 0, the maximum size of the pool will default to a system dependent value. * * Applications that intend to use ::CU_MEM_HANDLE_TYPE_FABRIC based memory sharing must ensure: * (1) `nvidia-caps-imex-channels` character device is created by the driver and is listed under /proc/devices * (2) have at least one IMEX channel file accessible by the user launching the application. * * When exporter and importer CUDA processes have been granted access to the same IMEX channel, they can securely * share memory. * * The IMEX channel security model works on a per user basis. Which means all processes under a user can share * memory if the user has access to a valid IMEX channel. When multi-user isolation is desired, a separate IMEX * channel is required for each user. * * These channel files exist in /dev/nvidia-caps-imex-channels/channel* and can be created using standard OS * native calls like mknod on Linux. For example: To create channel0 with the major number from /proc/devices * users can execute the following command: `mknod /dev/nvidia-caps-imex-channels/channel0 c 0` * * \note Specifying cudaMemHandleTypeNone creates a memory pool that will not support IPC. * * \returns * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorNotSupported * * \sa ::cuMemPoolCreate, ::cudaDeviceSetMemPool, ::cudaMallocFromPoolAsync, ::cudaMemPoolExportToShareableHandle, ::cudaDeviceGetDefaultMemPool, ::cudaDeviceGetMemPool */ extern __host__ cudaError_t CUDARTAPI cudaMemPoolCreate(cudaMemPool_t *memPool, const struct cudaMemPoolProps *poolProps); /** * \brief Destroys the specified memory pool * * If any pointers obtained from this pool haven't been freed or * the pool has free operations that haven't completed * when ::cudaMemPoolDestroy is invoked, the function will return immediately and the * resources associated with the pool will be released automatically * once there are no more outstanding allocations. * * Destroying the current mempool of a device sets the default mempool of * that device as the current mempool for that device. * * \note A device's default memory pool cannot be destroyed. * * \returns * ::cudaSuccess, * ::cudaErrorInvalidValue * * \sa cuMemPoolDestroy, ::cudaFreeAsync, ::cudaDeviceSetMemPool, ::cudaDeviceGetDefaultMemPool, ::cudaDeviceGetMemPool, ::cudaMemPoolCreate */ extern __host__ cudaError_t CUDARTAPI cudaMemPoolDestroy(cudaMemPool_t memPool); /** * \brief Allocates memory from a specified pool with stream ordered semantics. * * Inserts an allocation operation into \p hStream. * A pointer to the allocated memory is returned immediately in *dptr. * The allocation must not be accessed until the the allocation operation completes. * The allocation comes from the specified memory pool. * * \note * - The specified memory pool may be from a device different than that of the specified \p hStream. * * - Basic stream ordering allows future work submitted into the same stream to use the allocation. * Stream query, stream synchronize, and CUDA events can be used to guarantee that the allocation * operation completes before work submitted in a separate stream runs. * * \note During stream capture, this function results in the creation of an allocation node. In this case, * the allocation is owned by the graph instead of the memory pool. The memory pool's properties * are used to set the node's creation parameters. * * \param[out] ptr - Returned device pointer * \param[in] bytesize - Number of bytes to allocate * \param[in] memPool - The pool to allocate from * \param[in] stream - The stream establishing the stream ordering semantic * * \returns * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorNotSupported, * ::cudaErrorOutOfMemory * * \sa ::cuMemAllocFromPoolAsync, * \ref ::cudaMallocAsync(void** ptr, size_t size, cudaMemPool_t memPool, cudaStream_t stream) "cudaMallocAsync (C++ API)", * ::cudaMallocAsync, ::cudaFreeAsync, ::cudaDeviceGetDefaultMemPool, ::cudaMemPoolCreate, ::cudaMemPoolSetAccess, ::cudaMemPoolSetAttribute */ extern __host__ cudaError_t CUDARTAPI cudaMallocFromPoolAsync(void **ptr, size_t size, cudaMemPool_t memPool, cudaStream_t stream); /** * \brief Exports a memory pool to the requested handle type. * * Given an IPC capable mempool, create an OS handle to share the pool with another process. * A recipient process can convert the shareable handle into a mempool with ::cudaMemPoolImportFromShareableHandle. * Individual pointers can then be shared with the ::cudaMemPoolExportPointer and ::cudaMemPoolImportPointer APIs. * The implementation of what the shareable handle is and how it can be transferred is defined by the requested * handle type. * * \note: To create an IPC capable mempool, create a mempool with a CUmemAllocationHandleType other than cudaMemHandleTypeNone. * * \param[out] handle_out - pointer to the location in which to store the requested handle * \param[in] pool - pool to export * \param[in] handleType - the type of handle to create * \param[in] flags - must be 0 * * \returns * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorOutOfMemory * * \sa ::cuMemPoolExportToShareableHandle, ::cudaMemPoolImportFromShareableHandle, ::cudaMemPoolExportPointer, ::cudaMemPoolImportPointer */ extern __host__ cudaError_t CUDARTAPI cudaMemPoolExportToShareableHandle( void *shareableHandle, cudaMemPool_t memPool, enum cudaMemAllocationHandleType handleType, unsigned int flags); /** * \brief imports a memory pool from a shared handle. * * Specific allocations can be imported from the imported pool with ::cudaMemPoolImportPointer. * * \note Imported memory pools do not support creating new allocations. * As such imported memory pools may not be used in ::cudaDeviceSetMemPool * or ::cudaMallocFromPoolAsync calls. * * \param[out] pool_out - Returned memory pool * \param[in] handle - OS handle of the pool to open * \param[in] handleType - The type of handle being imported * \param[in] flags - must be 0 * * \returns * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorOutOfMemory * * \sa ::cuMemPoolImportFromShareableHandle, ::cudaMemPoolExportToShareableHandle, ::cudaMemPoolExportPointer, ::cudaMemPoolImportPointer */ extern __host__ cudaError_t CUDARTAPI cudaMemPoolImportFromShareableHandle( cudaMemPool_t *memPool, void *shareableHandle, enum cudaMemAllocationHandleType handleType, unsigned int flags); /** * \brief Export data to share a memory pool allocation between processes. * * Constructs \p shareData_out for sharing a specific allocation from an already shared memory pool. * The recipient process can import the allocation with the ::cudaMemPoolImportPointer api. * The data is not a handle and may be shared through any IPC mechanism. * * \param[out] shareData_out - Returned export data * \param[in] ptr - pointer to memory being exported * * \returns * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorOutOfMemory * * \sa ::cuMemPoolExportPointer, ::cudaMemPoolExportToShareableHandle, ::cudaMemPoolImportFromShareableHandle, ::cudaMemPoolImportPointer */ extern __host__ cudaError_t CUDARTAPI cudaMemPoolExportPointer(struct cudaMemPoolPtrExportData *exportData, void *ptr); /** * \brief Import a memory pool allocation from another process. * * Returns in \p ptr_out a pointer to the imported memory. * The imported memory must not be accessed before the allocation operation completes * in the exporting process. The imported memory must be freed from all importing processes before * being freed in the exporting process. The pointer may be freed with cudaFree * or cudaFreeAsync. If ::cudaFreeAsync is used, the free must be completed * on the importing process before the free operation on the exporting process. * * \note The ::cudaFreeAsync api may be used in the exporting process before * the ::cudaFreeAsync operation completes in its stream as long as the * ::cudaFreeAsync in the exporting process specifies a stream with * a stream dependency on the importing process's ::cudaFreeAsync. * * \param[out] ptr_out - pointer to imported memory * \param[in] pool - pool from which to import * \param[in] shareData - data specifying the memory to import * * \returns * ::CUDA_SUCCESS, * ::CUDA_ERROR_INVALID_VALUE, * ::CUDA_ERROR_NOT_INITIALIZED, * ::CUDA_ERROR_OUT_OF_MEMORY * * \sa ::cuMemPoolImportPointer, ::cudaMemPoolExportToShareableHandle, ::cudaMemPoolImportFromShareableHandle, ::cudaMemPoolExportPointer */ extern __host__ cudaError_t CUDARTAPI cudaMemPoolImportPointer(void **ptr, cudaMemPool_t memPool, struct cudaMemPoolPtrExportData *exportData); /** @} */ /* END CUDART_MEMORY_POOLS */ /** * \defgroup CUDART_UNIFIED Unified Addressing * * ___MANBRIEF___ unified addressing functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the unified addressing functions of the CUDA * runtime application programming interface. * * @{ * * \section CUDART_UNIFIED_overview Overview * * CUDA devices can share a unified address space with the host. * For these devices there is no distinction between a device * pointer and a host pointer -- the same pointer value may be * used to access memory from the host program and from a kernel * running on the device (with exceptions enumerated below). * * \section CUDART_UNIFIED_support Supported Platforms * * Whether or not a device supports unified addressing may be * queried by calling ::cudaGetDeviceProperties() with the device * property ::cudaDeviceProp::unifiedAddressing. * * Unified addressing is automatically enabled in 64-bit processes . * * \section CUDART_UNIFIED_lookup Looking Up Information from Pointer Values * * It is possible to look up information about the memory which backs a * pointer value. For instance, one may want to know if a pointer points * to host or device memory. As another example, in the case of device * memory, one may want to know on which CUDA device the memory * resides. These properties may be queried using the function * ::cudaPointerGetAttributes() * * Since pointers are unique, it is not necessary to specify information * about the pointers specified to ::cudaMemcpy() and other copy functions. * The copy direction ::cudaMemcpyDefault may be used to specify that the * CUDA runtime should infer the location of the pointer from its value. * * \section CUDART_UNIFIED_automaphost Automatic Mapping of Host Allocated Host Memory * * All host memory allocated through all devices using ::cudaMallocHost() and * ::cudaHostAlloc() is always directly accessible from all devices that * support unified addressing. This is the case regardless of whether or * not the flags ::cudaHostAllocPortable and ::cudaHostAllocMapped are * specified. * * The pointer value through which allocated host memory may be accessed * in kernels on all devices that support unified addressing is the same * as the pointer value through which that memory is accessed on the host. * It is not necessary to call ::cudaHostGetDevicePointer() to get the device * pointer for these allocations. * * Note that this is not the case for memory allocated using the flag * ::cudaHostAllocWriteCombined, as discussed below. * * \section CUDART_UNIFIED_autopeerregister Direct Access of Peer Memory * Upon enabling direct access from a device that supports unified addressing * to another peer device that supports unified addressing using * ::cudaDeviceEnablePeerAccess() all memory allocated in the peer device using * ::cudaMalloc() and ::cudaMallocPitch() will immediately be accessible * by the current device. The device pointer value through * which any peer's memory may be accessed in the current device * is the same pointer value through which that memory may be * accessed from the peer device. * * \section CUDART_UNIFIED_exceptions Exceptions, Disjoint Addressing * * Not all memory may be accessed on devices through the same pointer * value through which they are accessed on the host. These exceptions * are host memory registered using ::cudaHostRegister() and host memory * allocated using the flag ::cudaHostAllocWriteCombined. For these * exceptions, there exists a distinct host and device address for the * memory. The device address is guaranteed to not overlap any valid host * pointer range and is guaranteed to have the same value across all devices * that support unified addressing. * * This device address may be queried using ::cudaHostGetDevicePointer() * when a device using unified addressing is current. Either the host * or the unified device pointer value may be used to refer to this memory * in ::cudaMemcpy() and similar functions using the ::cudaMemcpyDefault * memory direction. * */ /** * \brief Returns attributes about a specified pointer * * Returns in \p *attributes the attributes of the pointer \p ptr. * If pointer was not allocated in, mapped by or registered with context * supporting unified addressing ::cudaErrorInvalidValue is returned. * * \note In CUDA 11.0 forward passing host pointer will return ::cudaMemoryTypeUnregistered * in ::cudaPointerAttributes::type and call will return ::cudaSuccess. * * The ::cudaPointerAttributes structure is defined as: * \code struct cudaPointerAttributes { enum cudaMemoryType type; int device; void *devicePointer; void *hostPointer; } \endcode * In this structure, the individual fields mean * * - \ref ::cudaPointerAttributes::type identifies type of memory. It can be * ::cudaMemoryTypeUnregistered for unregistered host memory, * ::cudaMemoryTypeHost for registered host memory, ::cudaMemoryTypeDevice for device * memory or ::cudaMemoryTypeManaged for managed memory. * * - \ref ::cudaPointerAttributes::device "device" is the device against which * \p ptr was allocated. If \p ptr has memory type ::cudaMemoryTypeDevice * then this identifies the device on which the memory referred to by \p ptr * physically resides. If \p ptr has memory type ::cudaMemoryTypeHost then this * identifies the device which was current when the allocation was made * (and if that device is deinitialized then this allocation will vanish * with that device's state). * * - \ref ::cudaPointerAttributes::devicePointer "devicePointer" is * the device pointer alias through which the memory referred to by \p ptr * may be accessed on the current device. * If the memory referred to by \p ptr cannot be accessed directly by the * current device then this is NULL. * * - \ref ::cudaPointerAttributes::hostPointer "hostPointer" is * the host pointer alias through which the memory referred to by \p ptr * may be accessed on the host. * If the memory referred to by \p ptr cannot be accessed directly by the * host then this is NULL. * * \param attributes - Attributes for the specified pointer * \param ptr - Pointer to get attributes for * * \return * ::cudaSuccess, * ::cudaErrorInvalidDevice, * ::cudaErrorInvalidValue * \note_init_rt * \note_callback * * \sa ::cudaGetDeviceCount, ::cudaGetDevice, ::cudaSetDevice, * ::cudaChooseDevice, * ::cudaInitDevice, * ::cuPointerGetAttributes */ extern __host__ cudaError_t CUDARTAPI cudaPointerGetAttributes(struct cudaPointerAttributes *attributes, const void *ptr); /** @} */ /* END CUDART_UNIFIED */ /** * \defgroup CUDART_PEER Peer Device Memory Access * * ___MANBRIEF___ peer device memory access functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the peer device memory access functions of the CUDA runtime * application programming interface. * * @{ */ /** * \brief Queries if a device may directly access a peer device's memory. * * Returns in \p *canAccessPeer a value of 1 if device \p device is capable of * directly accessing memory from \p peerDevice and 0 otherwise. If direct * access of \p peerDevice from \p device is possible, then access may be * enabled by calling ::cudaDeviceEnablePeerAccess(). * * \param canAccessPeer - Returned access capability * \param device - Device from which allocations on \p peerDevice are to * be directly accessed. * \param peerDevice - Device on which the allocations to be directly accessed * by \p device reside. * * \return * ::cudaSuccess, * ::cudaErrorInvalidDevice * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaDeviceEnablePeerAccess, * ::cudaDeviceDisablePeerAccess, * ::cuDeviceCanAccessPeer */ extern __host__ cudaError_t CUDARTAPI cudaDeviceCanAccessPeer(int *canAccessPeer, int device, int peerDevice); /** * \brief Enables direct access to memory allocations on a peer device. * * On success, all allocations from \p peerDevice will immediately be accessible by * the current device. They will remain accessible until access is explicitly * disabled using ::cudaDeviceDisablePeerAccess() or either device is reset using * ::cudaDeviceReset(). * * Note that access granted by this call is unidirectional and that in order to access * memory on the current device from \p peerDevice, a separate symmetric call * to ::cudaDeviceEnablePeerAccess() is required. * * Note that there are both device-wide and system-wide limitations per system * configuration, as noted in the CUDA Programming Guide under the section * "Peer-to-Peer Memory Access". * * Returns ::cudaErrorInvalidDevice if ::cudaDeviceCanAccessPeer() indicates * that the current device cannot directly access memory from \p peerDevice. * * Returns ::cudaErrorPeerAccessAlreadyEnabled if direct access of * \p peerDevice from the current device has already been enabled. * * Returns ::cudaErrorInvalidValue if \p flags is not 0. * * \param peerDevice - Peer device to enable direct access to from the current device * \param flags - Reserved for future use and must be set to 0 * * \return * ::cudaSuccess, * ::cudaErrorInvalidDevice, * ::cudaErrorPeerAccessAlreadyEnabled, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaDeviceCanAccessPeer, * ::cudaDeviceDisablePeerAccess, * ::cuCtxEnablePeerAccess */ extern __host__ cudaError_t CUDARTAPI cudaDeviceEnablePeerAccess(int peerDevice, unsigned int flags); /** * \brief Disables direct access to memory allocations on a peer device. * * Returns ::cudaErrorPeerAccessNotEnabled if direct access to memory on * \p peerDevice has not yet been enabled from the current device. * * \param peerDevice - Peer device to disable direct access to * * \return * ::cudaSuccess, * ::cudaErrorPeerAccessNotEnabled, * ::cudaErrorInvalidDevice * \notefnerr * \note_init_rt * \note_callback * * \sa ::cudaDeviceCanAccessPeer, * ::cudaDeviceEnablePeerAccess, * ::cuCtxDisablePeerAccess */ extern __host__ cudaError_t CUDARTAPI cudaDeviceDisablePeerAccess(int peerDevice); /** @} */ /* END CUDART_PEER */ /** \defgroup CUDART_OPENGL OpenGL Interoperability */ /** \defgroup CUDART_OPENGL_DEPRECATED OpenGL Interoperability [DEPRECATED] */ /** \defgroup CUDART_D3D9 Direct3D 9 Interoperability */ /** \defgroup CUDART_D3D9_DEPRECATED Direct3D 9 Interoperability [DEPRECATED] */ /** \defgroup CUDART_D3D10 Direct3D 10 Interoperability */ /** \defgroup CUDART_D3D10_DEPRECATED Direct3D 10 Interoperability [DEPRECATED] */ /** \defgroup CUDART_D3D11 Direct3D 11 Interoperability */ /** \defgroup CUDART_D3D11_DEPRECATED Direct3D 11 Interoperability [DEPRECATED] */ /** \defgroup CUDART_VDPAU VDPAU Interoperability */ /** \defgroup CUDART_EGL EGL Interoperability */ /** * \defgroup CUDART_INTEROP Graphics Interoperability * * ___MANBRIEF___ graphics interoperability functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the graphics interoperability functions of the CUDA * runtime application programming interface. * * @{ */ /** * \brief Unregisters a graphics resource for access by CUDA * * Unregisters the graphics resource \p resource so it is not accessible by * CUDA unless registered again. * * If \p resource is invalid then ::cudaErrorInvalidResourceHandle is * returned. * * \param resource - Resource to unregister * * \return * ::cudaSuccess, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorUnknown * \notefnerr * \note_init_rt * \note_callback * \note_destroy_ub * * \sa * ::cudaGraphicsD3D9RegisterResource, * ::cudaGraphicsD3D10RegisterResource, * ::cudaGraphicsD3D11RegisterResource, * ::cudaGraphicsGLRegisterBuffer, * ::cudaGraphicsGLRegisterImage, * ::cuGraphicsUnregisterResource */ extern __host__ cudaError_t CUDARTAPI cudaGraphicsUnregisterResource(cudaGraphicsResource_t resource); /** * \brief Set usage flags for mapping a graphics resource * * Set \p flags for mapping the graphics resource \p resource. * * Changes to \p flags will take effect the next time \p resource is mapped. * The \p flags argument may be any of the following: * - ::cudaGraphicsMapFlagsNone: Specifies no hints about how \p resource will * be used. It is therefore assumed that CUDA may read from or write to \p resource. * - ::cudaGraphicsMapFlagsReadOnly: Specifies that CUDA will not write to \p resource. * - ::cudaGraphicsMapFlagsWriteDiscard: Specifies CUDA will not read from \p resource and will * write over the entire contents of \p resource, so none of the data * previously stored in \p resource will be preserved. * * If \p resource is presently mapped for access by CUDA then ::cudaErrorUnknown is returned. * If \p flags is not one of the above values then ::cudaErrorInvalidValue is returned. * * \param resource - Registered resource to set flags for * \param flags - Parameters for resource mapping * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorUnknown, * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphicsMapResources, * ::cuGraphicsResourceSetMapFlags */ extern __host__ cudaError_t CUDARTAPI cudaGraphicsResourceSetMapFlags(cudaGraphicsResource_t resource, unsigned int flags); /** * \brief Map graphics resources for access by CUDA * * Maps the \p count graphics resources in \p resources for access by CUDA. * * The resources in \p resources may be accessed by CUDA until they * are unmapped. The graphics API from which \p resources were registered * should not access any resources while they are mapped by CUDA. If an * application does so, the results are undefined. * * This function provides the synchronization guarantee that any graphics calls * issued before ::cudaGraphicsMapResources() will complete before any subsequent CUDA * work issued in \p stream begins. * * If \p resources contains any duplicate entries then ::cudaErrorInvalidResourceHandle * is returned. If any of \p resources are presently mapped for access by * CUDA then ::cudaErrorUnknown is returned. * * \param count - Number of resources to map * \param resources - Resources to map for CUDA * \param stream - Stream for synchronization * * \return * ::cudaSuccess, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorUnknown * \note_null_stream * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphicsResourceGetMappedPointer, * ::cudaGraphicsSubResourceGetMappedArray, * ::cudaGraphicsUnmapResources, * ::cuGraphicsMapResources */ extern __host__ cudaError_t CUDARTAPI cudaGraphicsMapResources(int count, cudaGraphicsResource_t *resources, cudaStream_t stream __dv(0)); /** * \brief Unmap graphics resources. * * Unmaps the \p count graphics resources in \p resources. * * Once unmapped, the resources in \p resources may not be accessed by CUDA * until they are mapped again. * * This function provides the synchronization guarantee that any CUDA work issued * in \p stream before ::cudaGraphicsUnmapResources() will complete before any * subsequently issued graphics work begins. * * If \p resources contains any duplicate entries then ::cudaErrorInvalidResourceHandle * is returned. If any of \p resources are not presently mapped for access by * CUDA then ::cudaErrorUnknown is returned. * * \param count - Number of resources to unmap * \param resources - Resources to unmap * \param stream - Stream for synchronization * * \return * ::cudaSuccess, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorUnknown * \note_null_stream * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphicsMapResources, * ::cuGraphicsUnmapResources */ extern __host__ cudaError_t CUDARTAPI cudaGraphicsUnmapResources(int count, cudaGraphicsResource_t *resources, cudaStream_t stream __dv(0)); /** * \brief Get an device pointer through which to access a mapped graphics resource. * * Returns in \p *devPtr a pointer through which the mapped graphics resource * \p resource may be accessed. * Returns in \p *size the size of the memory in bytes which may be accessed from that pointer. * The value set in \p devPtr may change every time that \p resource is mapped. * * If \p resource is not a buffer then it cannot be accessed via a pointer and * ::cudaErrorUnknown is returned. * If \p resource is not mapped then ::cudaErrorUnknown is returned. * * * \param devPtr - Returned pointer through which \p resource may be accessed * \param size - Returned size of the buffer accessible starting at \p *devPtr * \param resource - Mapped resource to access * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorUnknown * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphicsMapResources, * ::cudaGraphicsSubResourceGetMappedArray, * ::cuGraphicsResourceGetMappedPointer */ extern __host__ cudaError_t CUDARTAPI cudaGraphicsResourceGetMappedPointer(void **devPtr, size_t *size, cudaGraphicsResource_t resource); /** * \brief Get an array through which to access a subresource of a mapped graphics resource. * * Returns in \p *array an array through which the subresource of the mapped * graphics resource \p resource which corresponds to array index \p arrayIndex * and mipmap level \p mipLevel may be accessed. The value set in \p array may * change every time that \p resource is mapped. * * If \p resource is not a texture then it cannot be accessed via an array and * ::cudaErrorUnknown is returned. * If \p arrayIndex is not a valid array index for \p resource then * ::cudaErrorInvalidValue is returned. * If \p mipLevel is not a valid mipmap level for \p resource then * ::cudaErrorInvalidValue is returned. * If \p resource is not mapped then ::cudaErrorUnknown is returned. * * \param array - Returned array through which a subresource of \p resource may be accessed * \param resource - Mapped resource to access * \param arrayIndex - Array index for array textures or cubemap face * index as defined by ::cudaGraphicsCubeFace for * cubemap textures for the subresource to access * \param mipLevel - Mipmap level for the subresource to access * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorUnknown * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphicsResourceGetMappedPointer, * ::cuGraphicsSubResourceGetMappedArray */ extern __host__ cudaError_t CUDARTAPI cudaGraphicsSubResourceGetMappedArray(cudaArray_t *array, cudaGraphicsResource_t resource, unsigned int arrayIndex, unsigned int mipLevel); /** * \brief Get a mipmapped array through which to access a mapped graphics resource. * * Returns in \p *mipmappedArray a mipmapped array through which the mapped * graphics resource \p resource may be accessed. The value set in \p mipmappedArray may * change every time that \p resource is mapped. * * If \p resource is not a texture then it cannot be accessed via an array and * ::cudaErrorUnknown is returned. * If \p resource is not mapped then ::cudaErrorUnknown is returned. * * \param mipmappedArray - Returned mipmapped array through which \p resource may be accessed * \param resource - Mapped resource to access * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorUnknown * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphicsResourceGetMappedPointer, * ::cuGraphicsResourceGetMappedMipmappedArray */ extern __host__ cudaError_t CUDARTAPI cudaGraphicsResourceGetMappedMipmappedArray(cudaMipmappedArray_t *mipmappedArray, cudaGraphicsResource_t resource); /** @} */ /* END CUDART_INTEROP */ /** * \defgroup CUDART_TEXTURE_OBJECT Texture Object Management * * ___MANBRIEF___ texture object management functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the low level texture object management functions * of the CUDA runtime application programming interface. The texture * object API is only supported on devices of compute capability 3.0 or higher. * * @{ */ /** * \brief Get the channel descriptor of an array * * Returns in \p *desc the channel descriptor of the CUDA array \p array. * * \param desc - Channel format * \param array - Memory array on device * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa \ref ::cudaCreateChannelDesc(int, int, int, int, cudaChannelFormatKind) "cudaCreateChannelDesc (C API)", * ::cudaCreateTextureObject, ::cudaCreateSurfaceObject */ extern __host__ cudaError_t CUDARTAPI cudaGetChannelDesc(struct cudaChannelFormatDesc *desc, cudaArray_const_t array); /** * \brief Returns a channel descriptor using the specified format * * Returns a channel descriptor with format \p f and number of bits of each * component \p x, \p y, \p z, and \p w. The ::cudaChannelFormatDesc is * defined as: * \code struct cudaChannelFormatDesc { int x, y, z, w; enum cudaChannelFormatKind f; }; * \endcode * * where ::cudaChannelFormatKind is one of ::cudaChannelFormatKindSigned, * ::cudaChannelFormatKindUnsigned, or ::cudaChannelFormatKindFloat. * * \param x - X component * \param y - Y component * \param z - Z component * \param w - W component * \param f - Channel format * * \return * Channel descriptor with format \p f * * \sa \ref ::cudaCreateChannelDesc(void) "cudaCreateChannelDesc (C++ API)", * ::cudaGetChannelDesc, ::cudaCreateTextureObject, ::cudaCreateSurfaceObject */ extern __host__ struct cudaChannelFormatDesc CUDARTAPI cudaCreateChannelDesc(int x, int y, int z, int w, enum cudaChannelFormatKind f); /** * \brief Creates a texture object * * Creates a texture object and returns it in \p pTexObject. \p pResDesc describes * the data to texture from. \p pTexDesc describes how the data should be sampled. * \p pResViewDesc is an optional argument that specifies an alternate format for * the data described by \p pResDesc, and also describes the subresource region * to restrict access to when texturing. \p pResViewDesc can only be specified if * the type of resource is a CUDA array or a CUDA mipmapped array not in a block * compressed format. * * Texture objects are only supported on devices of compute capability 3.0 or higher. * Additionally, a texture object is an opaque value, and, as such, should only be * accessed through CUDA API calls. * * The ::cudaResourceDesc structure is defined as: * \code struct cudaResourceDesc { enum cudaResourceType resType; union { struct { cudaArray_t array; } array; struct { cudaMipmappedArray_t mipmap; } mipmap; struct { void *devPtr; struct cudaChannelFormatDesc desc; size_t sizeInBytes; } linear; struct { void *devPtr; struct cudaChannelFormatDesc desc; size_t width; size_t height; size_t pitchInBytes; } pitch2D; } res; }; * \endcode * where: * - ::cudaResourceDesc::resType specifies the type of resource to texture from. * CUresourceType is defined as: * \code enum cudaResourceType { cudaResourceTypeArray = 0x00, cudaResourceTypeMipmappedArray = 0x01, cudaResourceTypeLinear = 0x02, cudaResourceTypePitch2D = 0x03 }; * \endcode * * \par * If ::cudaResourceDesc::resType is set to ::cudaResourceTypeArray, ::cudaResourceDesc::res::array::array * must be set to a valid CUDA array handle. * * \par * If ::cudaResourceDesc::resType is set to ::cudaResourceTypeMipmappedArray, ::cudaResourceDesc::res::mipmap::mipmap * must be set to a valid CUDA mipmapped array handle and ::cudaTextureDesc::normalizedCoords must be set to true. * * \par * If ::cudaResourceDesc::resType is set to ::cudaResourceTypeLinear, ::cudaResourceDesc::res::linear::devPtr * must be set to a valid device pointer, that is aligned to ::cudaDeviceProp::textureAlignment. * ::cudaResourceDesc::res::linear::desc describes the format and the number of components per array element. ::cudaResourceDesc::res::linear::sizeInBytes * specifies the size of the array in bytes. The total number of elements in the linear address range cannot exceed * ::cudaDeviceProp::maxTexture1DLinear. The number of elements is computed as (sizeInBytes / sizeof(desc)). * * \par * If ::cudaResourceDesc::resType is set to ::cudaResourceTypePitch2D, ::cudaResourceDesc::res::pitch2D::devPtr * must be set to a valid device pointer, that is aligned to ::cudaDeviceProp::textureAlignment. * ::cudaResourceDesc::res::pitch2D::desc describes the format and the number of components per array element. ::cudaResourceDesc::res::pitch2D::width * and ::cudaResourceDesc::res::pitch2D::height specify the width and height of the array in elements, and cannot exceed * ::cudaDeviceProp::maxTexture2DLinear[0] and ::cudaDeviceProp::maxTexture2DLinear[1] respectively. * ::cudaResourceDesc::res::pitch2D::pitchInBytes specifies the pitch between two rows in bytes and has to be aligned to * ::cudaDeviceProp::texturePitchAlignment. Pitch cannot exceed ::cudaDeviceProp::maxTexture2DLinear[2]. * * * The ::cudaTextureDesc struct is defined as * \code struct cudaTextureDesc { enum cudaTextureAddressMode addressMode[3]; enum cudaTextureFilterMode filterMode; enum cudaTextureReadMode readMode; int sRGB; float borderColor[4]; int normalizedCoords; unsigned int maxAnisotropy; enum cudaTextureFilterMode mipmapFilterMode; float mipmapLevelBias; float minMipmapLevelClamp; float maxMipmapLevelClamp; int disableTrilinearOptimization; int seamlessCubemap; }; * \endcode * where * - ::cudaTextureDesc::addressMode specifies the addressing mode for each dimension of the texture data. ::cudaTextureAddressMode is defined as: * \code enum cudaTextureAddressMode { cudaAddressModeWrap = 0, cudaAddressModeClamp = 1, cudaAddressModeMirror = 2, cudaAddressModeBorder = 3 }; * \endcode * This is ignored if ::cudaResourceDesc::resType is ::cudaResourceTypeLinear. Also, if ::cudaTextureDesc::normalizedCoords * is set to zero, ::cudaAddressModeWrap and ::cudaAddressModeMirror won't be supported and will be switched to ::cudaAddressModeClamp. * * - ::cudaTextureDesc::filterMode specifies the filtering mode to be used when fetching from the texture. ::cudaTextureFilterMode is defined as: * \code enum cudaTextureFilterMode { cudaFilterModePoint = 0, cudaFilterModeLinear = 1 }; * \endcode * This is ignored if ::cudaResourceDesc::resType is ::cudaResourceTypeLinear. * * - ::cudaTextureDesc::readMode specifies whether integer data should be converted to floating point or not. ::cudaTextureReadMode is defined as: * \code enum cudaTextureReadMode { cudaReadModeElementType = 0, cudaReadModeNormalizedFloat = 1 }; * \endcode * Note that this applies only to 8-bit and 16-bit integer formats. 32-bit integer format would not be promoted, regardless of * whether or not this ::cudaTextureDesc::readMode is set ::cudaReadModeNormalizedFloat is specified. * * - ::cudaTextureDesc::sRGB specifies whether sRGB to linear conversion should be performed during texture fetch. * * - ::cudaTextureDesc::borderColor specifies the float values of color. where: * ::cudaTextureDesc::borderColor[0] contains value of 'R', * ::cudaTextureDesc::borderColor[1] contains value of 'G', * ::cudaTextureDesc::borderColor[2] contains value of 'B', * ::cudaTextureDesc::borderColor[3] contains value of 'A' * Note that application using integer border color values will need to these values to float. * The values are set only when the addressing mode specified by ::cudaTextureDesc::addressMode is cudaAddressModeBorder. * * - ::cudaTextureDesc::normalizedCoords specifies whether the texture coordinates will be normalized or not. * * - ::cudaTextureDesc::maxAnisotropy specifies the maximum anistropy ratio to be used when doing anisotropic filtering. This value will be * clamped to the range [1,16]. * * - ::cudaTextureDesc::mipmapFilterMode specifies the filter mode when the calculated mipmap level lies between two defined mipmap levels. * * - ::cudaTextureDesc::mipmapLevelBias specifies the offset to be applied to the calculated mipmap level. * * - ::cudaTextureDesc::minMipmapLevelClamp specifies the lower end of the mipmap level range to clamp access to. * * - ::cudaTextureDesc::maxMipmapLevelClamp specifies the upper end of the mipmap level range to clamp access to. * * - ::cudaTextureDesc::disableTrilinearOptimization specifies whether the trilinear filtering optimizations will be disabled. * * - ::cudaTextureDesc::seamlessCubemap specifies whether seamless cube map filtering is enabled. This flag can only be specified if the * underlying resource is a CUDA array or a CUDA mipmapped array that was created with the flag ::cudaArrayCubemap. * When seamless cube map filtering is enabled, texture address modes specified by ::cudaTextureDesc::addressMode are ignored. * Instead, if the ::cudaTextureDesc::filterMode is set to ::cudaFilterModePoint the address mode ::cudaAddressModeClamp will be applied for all dimensions. * If the ::cudaTextureDesc::filterMode is set to ::cudaFilterModeLinear seamless cube map filtering will be performed when sampling along the cube face borders. * * The ::cudaResourceViewDesc struct is defined as * \code struct cudaResourceViewDesc { enum cudaResourceViewFormat format; size_t width; size_t height; size_t depth; unsigned int firstMipmapLevel; unsigned int lastMipmapLevel; unsigned int firstLayer; unsigned int lastLayer; }; * \endcode * where: * - ::cudaResourceViewDesc::format specifies how the data contained in the CUDA array or CUDA mipmapped array should * be interpreted. Note that this can incur a change in size of the texture data. If the resource view format is a block * compressed format, then the underlying CUDA array or CUDA mipmapped array has to have a 32-bit unsigned integer format * with 2 or 4 channels, depending on the block compressed format. For ex., BC1 and BC4 require the underlying CUDA array to have * a 32-bit unsigned int with 2 channels. The other BC formats require the underlying resource to have the same 32-bit unsigned int * format but with 4 channels. * * - ::cudaResourceViewDesc::width specifies the new width of the texture data. If the resource view format is a block * compressed format, this value has to be 4 times the original width of the resource. For non block compressed formats, * this value has to be equal to that of the original resource. * * - ::cudaResourceViewDesc::height specifies the new height of the texture data. If the resource view format is a block * compressed format, this value has to be 4 times the original height of the resource. For non block compressed formats, * this value has to be equal to that of the original resource. * * - ::cudaResourceViewDesc::depth specifies the new depth of the texture data. This value has to be equal to that of the * original resource. * * - ::cudaResourceViewDesc::firstMipmapLevel specifies the most detailed mipmap level. This will be the new mipmap level zero. * For non-mipmapped resources, this value has to be zero.::cudaTextureDesc::minMipmapLevelClamp and ::cudaTextureDesc::maxMipmapLevelClamp * will be relative to this value. For ex., if the firstMipmapLevel is set to 2, and a minMipmapLevelClamp of 1.2 is specified, * then the actual minimum mipmap level clamp will be 3.2. * * - ::cudaResourceViewDesc::lastMipmapLevel specifies the least detailed mipmap level. For non-mipmapped resources, this value * has to be zero. * * - ::cudaResourceViewDesc::firstLayer specifies the first layer index for layered textures. This will be the new layer zero. * For non-layered resources, this value has to be zero. * * - ::cudaResourceViewDesc::lastLayer specifies the last layer index for layered textures. For non-layered resources, * this value has to be zero. * * * \param pTexObject - Texture object to create * \param pResDesc - Resource descriptor * \param pTexDesc - Texture descriptor * \param pResViewDesc - Resource view descriptor * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_init_rt * \note_callback * * \sa * ::cudaDestroyTextureObject, * ::cuTexObjectCreate */ extern __host__ cudaError_t CUDARTAPI cudaCreateTextureObject(cudaTextureObject_t *pTexObject, const struct cudaResourceDesc *pResDesc, const struct cudaTextureDesc *pTexDesc, const struct cudaResourceViewDesc *pResViewDesc); /** * \brief Destroys a texture object * * Destroys the texture object specified by \p texObject. * * \param texObject - Texture object to destroy * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_init_rt * \note_callback * \note_destroy_ub * * \sa * ::cudaCreateTextureObject, * ::cuTexObjectDestroy */ extern __host__ cudaError_t CUDARTAPI cudaDestroyTextureObject(cudaTextureObject_t texObject); /** * \brief Returns a texture object's resource descriptor * * Returns the resource descriptor for the texture object specified by \p texObject. * * \param pResDesc - Resource descriptor * \param texObject - Texture object * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_init_rt * \note_callback * * \sa * ::cudaCreateTextureObject, * ::cuTexObjectGetResourceDesc */ extern __host__ cudaError_t CUDARTAPI cudaGetTextureObjectResourceDesc(struct cudaResourceDesc *pResDesc, cudaTextureObject_t texObject); /** * \brief Returns a texture object's texture descriptor * * Returns the texture descriptor for the texture object specified by \p texObject. * * \param pTexDesc - Texture descriptor * \param texObject - Texture object * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_init_rt * \note_callback * * \sa * ::cudaCreateTextureObject, * ::cuTexObjectGetTextureDesc */ extern __host__ cudaError_t CUDARTAPI cudaGetTextureObjectTextureDesc(struct cudaTextureDesc *pTexDesc, cudaTextureObject_t texObject); /** * \brief Returns a texture object's resource view descriptor * * Returns the resource view descriptor for the texture object specified by \p texObject. * If no resource view was specified, ::cudaErrorInvalidValue is returned. * * \param pResViewDesc - Resource view descriptor * \param texObject - Texture object * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_init_rt * \note_callback * * \sa * ::cudaCreateTextureObject, * ::cuTexObjectGetResourceViewDesc */ extern __host__ cudaError_t CUDARTAPI cudaGetTextureObjectResourceViewDesc(struct cudaResourceViewDesc *pResViewDesc, cudaTextureObject_t texObject); /** @} */ /* END CUDART_TEXTURE_OBJECT */ /** * \defgroup CUDART_SURFACE_OBJECT Surface Object Management * * ___MANBRIEF___ surface object management functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the low level texture object management functions * of the CUDA runtime application programming interface. The surface object * API is only supported on devices of compute capability 3.0 or higher. * * @{ */ /** * \brief Creates a surface object * * Creates a surface object and returns it in \p pSurfObject. \p pResDesc describes * the data to perform surface load/stores on. ::cudaResourceDesc::resType must be * ::cudaResourceTypeArray and ::cudaResourceDesc::res::array::array * must be set to a valid CUDA array handle. * * Surface objects are only supported on devices of compute capability 3.0 or higher. * Additionally, a surface object is an opaque value, and, as such, should only be * accessed through CUDA API calls. * * \param pSurfObject - Surface object to create * \param pResDesc - Resource descriptor * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidChannelDescriptor, * ::cudaErrorInvalidResourceHandle * \note_init_rt * \note_callback * * \sa * ::cudaDestroySurfaceObject, * ::cuSurfObjectCreate */ extern __host__ cudaError_t CUDARTAPI cudaCreateSurfaceObject(cudaSurfaceObject_t *pSurfObject, const struct cudaResourceDesc *pResDesc); /** * \brief Destroys a surface object * * Destroys the surface object specified by \p surfObject. * * \param surfObject - Surface object to destroy * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_init_rt * \note_callback * \note_destroy_ub * * \sa * ::cudaCreateSurfaceObject, * ::cuSurfObjectDestroy */ extern __host__ cudaError_t CUDARTAPI cudaDestroySurfaceObject(cudaSurfaceObject_t surfObject); /** * \brief Returns a surface object's resource descriptor * Returns the resource descriptor for the surface object specified by \p surfObject. * * \param pResDesc - Resource descriptor * \param surfObject - Surface object * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_init_rt * \note_callback * * \sa * ::cudaCreateSurfaceObject, * ::cuSurfObjectGetResourceDesc */ extern __host__ cudaError_t CUDARTAPI cudaGetSurfaceObjectResourceDesc(struct cudaResourceDesc *pResDesc, cudaSurfaceObject_t surfObject); /** @} */ /* END CUDART_SURFACE_OBJECT */ /** * \defgroup CUDART__VERSION Version Management * * @{ */ /** * \brief Returns the latest version of CUDA supported by the driver * * Returns in \p *driverVersion the latest version of CUDA supported by * the driver. The version is returned as (1000 × major + 10 × minor). * For example, CUDA 9.2 would be represented by 9020. If no driver is installed, * then 0 is returned as the driver version. * * This function automatically returns ::cudaErrorInvalidValue * if \p driverVersion is NULL. * * \param driverVersion - Returns the CUDA driver version. * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaRuntimeGetVersion, * ::cuDriverGetVersion */ extern __host__ cudaError_t CUDARTAPI cudaDriverGetVersion(int *driverVersion); /** * \brief Returns the CUDA Runtime version * * Returns in \p *runtimeVersion the version number of the current CUDA * Runtime instance. The version is returned as * (1000 × major + 10 × minor). For example, * CUDA 9.2 would be represented by 9020. * * As of CUDA 12.0, this function no longer initializes CUDA. The purpose * of this API is solely to return a compile-time constant stating the * CUDA Toolkit version in the above format. * * This function automatically returns ::cudaErrorInvalidValue if * the \p runtimeVersion argument is NULL. * * \param runtimeVersion - Returns the CUDA Runtime version. * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_init_rt * \note_callback * * \sa * ::cudaDriverGetVersion, * ::cuDriverGetVersion */ extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaRuntimeGetVersion(int *runtimeVersion); /** @} */ /* END CUDART__VERSION */ /** * \defgroup CUDART_GRAPH Graph Management * * ___MANBRIEF___ graph management functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the graph management functions of CUDA * runtime application programming interface. * * @{ */ /** * \brief Creates a graph * * Creates an empty graph, which is returned via \p pGraph. * * \param pGraph - Returns newly created graph * \param flags - Graph creation flags, must be 0 * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorMemoryAllocation * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddChildGraphNode, * ::cudaGraphAddEmptyNode, * ::cudaGraphAddKernelNode, * ::cudaGraphAddHostNode, * ::cudaGraphAddMemcpyNode, * ::cudaGraphAddMemsetNode, * ::cudaGraphInstantiate, * ::cudaGraphDestroy, * ::cudaGraphGetNodes, * ::cudaGraphGetRootNodes, * ::cudaGraphGetEdges, * ::cudaGraphClone */ extern __host__ cudaError_t CUDARTAPI cudaGraphCreate(cudaGraph_t *pGraph, unsigned int flags); /** * \brief Creates a kernel execution node and adds it to a graph * * Creates a new kernel execution node and adds it to \p graph with \p numDependencies * dependencies specified via \p pDependencies and arguments specified in \p pNodeParams. * It is possible for \p numDependencies to be 0, in which case the node will be placed * at the root of the graph. \p pDependencies may not have any duplicate entries. * A handle to the new node will be returned in \p pGraphNode. * * The cudaKernelNodeParams structure is defined as: * * \code * struct cudaKernelNodeParams * { * void* func; * dim3 gridDim; * dim3 blockDim; * unsigned int sharedMemBytes; * void **kernelParams; * void **extra; * }; * \endcode * * When the graph is launched, the node will invoke kernel \p func on a (\p gridDim.x x * \p gridDim.y x \p gridDim.z) grid of blocks. Each block contains * (\p blockDim.x x \p blockDim.y x \p blockDim.z) threads. * * \p sharedMem sets the amount of dynamic shared memory that will be * available to each thread block. * * Kernel parameters to \p func can be specified in one of two ways: * * 1) Kernel parameters can be specified via \p kernelParams. If the kernel has N * parameters, then \p kernelParams needs to be an array of N pointers. Each pointer, * from \p kernelParams[0] to \p kernelParams[N-1], points to the region of memory from which the actual * parameter will be copied. The number of kernel parameters and their offsets and sizes do not need * to be specified as that information is retrieved directly from the kernel's image. * * 2) Kernel parameters can also be packaged by the application into a single buffer that is passed in * via \p extra. This places the burden on the application of knowing each kernel * parameter's size and alignment/padding within the buffer. The \p extra parameter exists * to allow this function to take additional less commonly used arguments. \p extra specifies * a list of names of extra settings and their corresponding values. Each extra setting name is * immediately followed by the corresponding value. The list must be terminated with either NULL or * CU_LAUNCH_PARAM_END. * * - ::CU_LAUNCH_PARAM_END, which indicates the end of the \p extra * array; * - ::CU_LAUNCH_PARAM_BUFFER_POINTER, which specifies that the next * value in \p extra will be a pointer to a buffer * containing all the kernel parameters for launching kernel * \p func; * - ::CU_LAUNCH_PARAM_BUFFER_SIZE, which specifies that the next * value in \p extra will be a pointer to a size_t * containing the size of the buffer specified with * ::CU_LAUNCH_PARAM_BUFFER_POINTER; * * The error ::cudaErrorInvalidValue will be returned if kernel parameters are specified with both * \p kernelParams and \p extra (i.e. both \p kernelParams and * \p extra are non-NULL). * * The \p kernelParams or \p extra array, as well as the argument values it points to, * are copied during this call. * * \note Kernels launched using graphs must not use texture and surface references. Reading or * writing through any texture or surface reference is undefined behavior. * This restriction does not apply to texture and surface objects. * * \param pGraphNode - Returns newly created node * \param graph - Graph to which to add the node * \param pDependencies - Dependencies of the node * \param numDependencies - Number of dependencies * \param pNodeParams - Parameters for the GPU execution node * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidDeviceFunction * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * \note_cudaKernel_t * * \sa * ::cudaGraphAddNode, * ::cudaLaunchKernel, * ::cudaGraphKernelNodeGetParams, * ::cudaGraphKernelNodeSetParams, * ::cudaGraphCreate, * ::cudaGraphDestroyNode, * ::cudaGraphAddChildGraphNode, * ::cudaGraphAddEmptyNode, * ::cudaGraphAddHostNode, * ::cudaGraphAddMemcpyNode, * ::cudaGraphAddMemsetNode */ extern __host__ cudaError_t CUDARTAPI cudaGraphAddKernelNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, const struct cudaKernelNodeParams *pNodeParams); /** * \brief Returns a kernel node's parameters * * Returns the parameters of kernel node \p node in \p pNodeParams. * The \p kernelParams or \p extra array returned in \p pNodeParams, * as well as the argument values it points to, are owned by the node. * This memory remains valid until the node is destroyed or its * parameters are modified, and should not be modified * directly. Use ::cudaGraphKernelNodeSetParams to update the * parameters of this node. * * The params will contain either \p kernelParams or \p extra, * according to which of these was most recently set on the node. * * \param node - Node to get the parameters for * \param pNodeParams - Pointer to return the parameters * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidDeviceFunction * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaLaunchKernel, * ::cudaGraphAddKernelNode, * ::cudaGraphKernelNodeSetParams */ extern __host__ cudaError_t CUDARTAPI cudaGraphKernelNodeGetParams(cudaGraphNode_t node, struct cudaKernelNodeParams *pNodeParams); /** * \brief Sets a kernel node's parameters * * Sets the parameters of kernel node \p node to \p pNodeParams. * * \param node - Node to set the parameters for * \param pNodeParams - Parameters to copy * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorMemoryAllocation * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * \note_cudaKernel_t * * \sa * ::cudaGraphNodeSetParams, * ::cudaLaunchKernel, * ::cudaGraphAddKernelNode, * ::cudaGraphKernelNodeGetParams */ extern __host__ cudaError_t CUDARTAPI cudaGraphKernelNodeSetParams(cudaGraphNode_t node, const struct cudaKernelNodeParams *pNodeParams); /** * \brief Copies attributes from source node to destination node. * * Copies attributes from source node \p src to destination node \p dst. * Both node must have the same context. * * \param[out] dst Destination node * \param[in] src Source node * For list of attributes see ::cudaKernelNodeAttrID * * \return * ::cudaSuccess, * ::cudaErrorInvalidContext * \notefnerr * * \sa * ::cudaAccessPolicyWindow */ extern __host__ cudaError_t CUDARTAPI cudaGraphKernelNodeCopyAttributes( cudaGraphNode_t hSrc, cudaGraphNode_t hDst); /** * \brief Queries node attribute. * * Queries attribute \p attr from node \p hNode and stores it in corresponding * member of \p value_out. * * \param[in] hNode * \param[in] attr * \param[out] value_out * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle * \notefnerr * * \sa * ::cudaAccessPolicyWindow */ extern __host__ cudaError_t CUDARTAPI cudaGraphKernelNodeGetAttribute( cudaGraphNode_t hNode, cudaKernelNodeAttrID attr, cudaKernelNodeAttrValue *value_out); /** * \brief Sets node attribute. * * Sets attribute \p attr on node \p hNode from corresponding attribute of * \p value. * * \param[out] hNode * \param[in] attr * \param[out] value * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle * \notefnerr * * \sa * ::cudaAccessPolicyWindow */ extern __host__ cudaError_t CUDARTAPI cudaGraphKernelNodeSetAttribute( cudaGraphNode_t hNode, cudaKernelNodeAttrID attr, const cudaKernelNodeAttrValue *value); /** * \brief Creates a memcpy node and adds it to a graph * * Creates a new memcpy node and adds it to \p graph with \p numDependencies * dependencies specified via \p pDependencies. * It is possible for \p numDependencies to be 0, in which case the node will be placed * at the root of the graph. \p pDependencies may not have any duplicate entries. * A handle to the new node will be returned in \p pGraphNode. * * When the graph is launched, the node will perform the memcpy described by \p pCopyParams. * See ::cudaMemcpy3D() for a description of the structure and its restrictions. * * Memcpy nodes have some additional restrictions with regards to managed memory, if the * system contains at least one device which has a zero value for the device attribute * ::cudaDevAttrConcurrentManagedAccess. * * \param pGraphNode - Returns newly created node * \param graph - Graph to which to add the node * \param pDependencies - Dependencies of the node * \param numDependencies - Number of dependencies * \param pCopyParams - Parameters for the memory copy * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddNode, * ::cudaMemcpy3D, * ::cudaGraphAddMemcpyNodeToSymbol, * ::cudaGraphAddMemcpyNodeFromSymbol, * ::cudaGraphAddMemcpyNode1D, * ::cudaGraphMemcpyNodeGetParams, * ::cudaGraphMemcpyNodeSetParams, * ::cudaGraphCreate, * ::cudaGraphDestroyNode, * ::cudaGraphAddChildGraphNode, * ::cudaGraphAddEmptyNode, * ::cudaGraphAddKernelNode, * ::cudaGraphAddHostNode, * ::cudaGraphAddMemsetNode */ extern __host__ cudaError_t CUDARTAPI cudaGraphAddMemcpyNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, const struct cudaMemcpy3DParms *pCopyParams); /** * \brief Creates a memcpy node to copy to a symbol on the device and adds it to a graph * * Creates a new memcpy node to copy to \p symbol and adds it to \p graph with * \p numDependencies dependencies specified via \p pDependencies. * It is possible for \p numDependencies to be 0, in which case the node will be placed * at the root of the graph. \p pDependencies may not have any duplicate entries. * A handle to the new node will be returned in \p pGraphNode. * * When the graph is launched, the node will copy \p count bytes from the memory area * pointed to by \p src to the memory area pointed to by \p offset bytes from the start * of symbol \p symbol. The memory areas may not overlap. \p symbol is a variable that * resides in global or constant memory space. \p kind can be either * ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. * Passing ::cudaMemcpyDefault is recommended, in which case the type of * transfer is inferred from the pointer values. However, ::cudaMemcpyDefault * is only allowed on systems that support unified virtual addressing. * * Memcpy nodes have some additional restrictions with regards to managed memory, if the * system contains at least one device which has a zero value for the device attribute * ::cudaDevAttrConcurrentManagedAccess. * * \param pGraphNode - Returns newly created node * \param graph - Graph to which to add the node * \param pDependencies - Dependencies of the node * \param numDependencies - Number of dependencies * \param symbol - Device symbol address * \param src - Source memory address * \param count - Size in bytes to copy * \param offset - Offset from start of symbol in bytes * \param kind - Type of transfer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaMemcpyToSymbol, * ::cudaGraphAddMemcpyNode, * ::cudaGraphAddMemcpyNodeFromSymbol, * ::cudaGraphMemcpyNodeGetParams, * ::cudaGraphMemcpyNodeSetParams, * ::cudaGraphMemcpyNodeSetParamsToSymbol, * ::cudaGraphMemcpyNodeSetParamsFromSymbol, * ::cudaGraphCreate, * ::cudaGraphDestroyNode, * ::cudaGraphAddChildGraphNode, * ::cudaGraphAddEmptyNode, * ::cudaGraphAddKernelNode, * ::cudaGraphAddHostNode, * ::cudaGraphAddMemsetNode */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaGraphAddMemcpyNodeToSymbol( cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, const void* symbol, const void* src, size_t count, size_t offset, enum cudaMemcpyKind kind); #endif /** * \brief Creates a memcpy node to copy from a symbol on the device and adds it to a graph * * Creates a new memcpy node to copy from \p symbol and adds it to \p graph with * \p numDependencies dependencies specified via \p pDependencies. * It is possible for \p numDependencies to be 0, in which case the node will be placed * at the root of the graph. \p pDependencies may not have any duplicate entries. * A handle to the new node will be returned in \p pGraphNode. * * When the graph is launched, the node will copy \p count bytes from the memory area * pointed to by \p offset bytes from the start of symbol \p symbol to the memory area * pointed to by \p dst. The memory areas may not overlap. \p symbol is a variable * that resides in global or constant memory space. \p kind can be either * ::cudaMemcpyDeviceToHost, ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. * Passing ::cudaMemcpyDefault is recommended, in which case the type of transfer * is inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. * * Memcpy nodes have some additional restrictions with regards to managed memory, if the * system contains at least one device which has a zero value for the device attribute * ::cudaDevAttrConcurrentManagedAccess. * * \param pGraphNode - Returns newly created node * \param graph - Graph to which to add the node * \param pDependencies - Dependencies of the node * \param numDependencies - Number of dependencies * \param dst - Destination memory address * \param symbol - Device symbol address * \param count - Size in bytes to copy * \param offset - Offset from start of symbol in bytes * \param kind - Type of transfer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaMemcpyFromSymbol, * ::cudaGraphAddMemcpyNode, * ::cudaGraphAddMemcpyNodeToSymbol, * ::cudaGraphMemcpyNodeGetParams, * ::cudaGraphMemcpyNodeSetParams, * ::cudaGraphMemcpyNodeSetParamsFromSymbol, * ::cudaGraphMemcpyNodeSetParamsToSymbol, * ::cudaGraphCreate, * ::cudaGraphDestroyNode, * ::cudaGraphAddChildGraphNode, * ::cudaGraphAddEmptyNode, * ::cudaGraphAddKernelNode, * ::cudaGraphAddHostNode, * ::cudaGraphAddMemsetNode */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaGraphAddMemcpyNodeFromSymbol( cudaGraphNode_t* pGraphNode, cudaGraph_t graph, const cudaGraphNode_t* pDependencies, size_t numDependencies, void* dst, const void* symbol, size_t count, size_t offset, enum cudaMemcpyKind kind); #endif /** * \brief Creates a 1D memcpy node and adds it to a graph * * Creates a new 1D memcpy node and adds it to \p graph with \p numDependencies * dependencies specified via \p pDependencies. * It is possible for \p numDependencies to be 0, in which case the node will be placed * at the root of the graph. \p pDependencies may not have any duplicate entries. * A handle to the new node will be returned in \p pGraphNode. * * When the graph is launched, the node will copy \p count bytes from the memory * area pointed to by \p src to the memory area pointed to by \p dst, where * \p kind specifies the direction of the copy, and must be one of * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost, * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing * ::cudaMemcpyDefault is recommended, in which case the type of transfer is * inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. Launching a * memcpy node with dst and src pointers that do not match the direction of * the copy results in an undefined behavior. * * Memcpy nodes have some additional restrictions with regards to managed memory, if the * system contains at least one device which has a zero value for the device attribute * ::cudaDevAttrConcurrentManagedAccess. * * \param pGraphNode - Returns newly created node * \param graph - Graph to which to add the node * \param pDependencies - Dependencies of the node * \param numDependencies - Number of dependencies * \param dst - Destination memory address * \param src - Source memory address * \param count - Size in bytes to copy * \param kind - Type of transfer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaMemcpy, * ::cudaGraphAddMemcpyNode, * ::cudaGraphMemcpyNodeGetParams, * ::cudaGraphMemcpyNodeSetParams, * ::cudaGraphMemcpyNodeSetParams1D, * ::cudaGraphCreate, * ::cudaGraphDestroyNode, * ::cudaGraphAddChildGraphNode, * ::cudaGraphAddEmptyNode, * ::cudaGraphAddKernelNode, * ::cudaGraphAddHostNode, * ::cudaGraphAddMemsetNode */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaGraphAddMemcpyNode1D( cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, void* dst, const void* src, size_t count, enum cudaMemcpyKind kind); #endif /** * \brief Returns a memcpy node's parameters * * Returns the parameters of memcpy node \p node in \p pNodeParams. * * \param node - Node to get the parameters for * \param pNodeParams - Pointer to return the parameters * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaMemcpy3D, * ::cudaGraphAddMemcpyNode, * ::cudaGraphMemcpyNodeSetParams */ extern __host__ cudaError_t CUDARTAPI cudaGraphMemcpyNodeGetParams(cudaGraphNode_t node, struct cudaMemcpy3DParms *pNodeParams); /** * \brief Sets a memcpy node's parameters * * Sets the parameters of memcpy node \p node to \p pNodeParams. * * \param node - Node to set the parameters for * \param pNodeParams - Parameters to copy * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphNodeSetParams, * ::cudaMemcpy3D, * ::cudaGraphMemcpyNodeSetParamsToSymbol, * ::cudaGraphMemcpyNodeSetParamsFromSymbol, * ::cudaGraphMemcpyNodeSetParams1D, * ::cudaGraphAddMemcpyNode, * ::cudaGraphMemcpyNodeGetParams */ extern __host__ cudaError_t CUDARTAPI cudaGraphMemcpyNodeSetParams(cudaGraphNode_t node, const struct cudaMemcpy3DParms *pNodeParams); /** * \brief Sets a memcpy node's parameters to copy to a symbol on the device * * Sets the parameters of memcpy node \p node to the copy described by the provided parameters. * * When the graph is launched, the node will copy \p count bytes from the memory area * pointed to by \p src to the memory area pointed to by \p offset bytes from the start * of symbol \p symbol. The memory areas may not overlap. \p symbol is a variable that * resides in global or constant memory space. \p kind can be either * ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. * Passing ::cudaMemcpyDefault is recommended, in which case the type of * transfer is inferred from the pointer values. However, ::cudaMemcpyDefault * is only allowed on systems that support unified virtual addressing. * * \param node - Node to set the parameters for * \param symbol - Device symbol address * \param src - Source memory address * \param count - Size in bytes to copy * \param offset - Offset from start of symbol in bytes * \param kind - Type of transfer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaMemcpyToSymbol, * ::cudaGraphMemcpyNodeSetParams, * ::cudaGraphMemcpyNodeSetParamsFromSymbol, * ::cudaGraphAddMemcpyNode, * ::cudaGraphMemcpyNodeGetParams */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaGraphMemcpyNodeSetParamsToSymbol( cudaGraphNode_t node, const void* symbol, const void* src, size_t count, size_t offset, enum cudaMemcpyKind kind); #endif /** * \brief Sets a memcpy node's parameters to copy from a symbol on the device * * Sets the parameters of memcpy node \p node to the copy described by the provided parameters. * * When the graph is launched, the node will copy \p count bytes from the memory area * pointed to by \p offset bytes from the start of symbol \p symbol to the memory area * pointed to by \p dst. The memory areas may not overlap. \p symbol is a variable * that resides in global or constant memory space. \p kind can be either * ::cudaMemcpyDeviceToHost, ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. * Passing ::cudaMemcpyDefault is recommended, in which case the type of transfer * is inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. * * \param node - Node to set the parameters for * \param dst - Destination memory address * \param symbol - Device symbol address * \param count - Size in bytes to copy * \param offset - Offset from start of symbol in bytes * \param kind - Type of transfer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaMemcpyFromSymbol, * ::cudaGraphMemcpyNodeSetParams, * ::cudaGraphMemcpyNodeSetParamsToSymbol, * ::cudaGraphAddMemcpyNode, * ::cudaGraphMemcpyNodeGetParams */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaGraphMemcpyNodeSetParamsFromSymbol( cudaGraphNode_t node, void* dst, const void* symbol, size_t count, size_t offset, enum cudaMemcpyKind kind); #endif /** * \brief Sets a memcpy node's parameters to perform a 1-dimensional copy * * Sets the parameters of memcpy node \p node to the copy described by the provided parameters. * * When the graph is launched, the node will copy \p count bytes from the memory * area pointed to by \p src to the memory area pointed to by \p dst, where * \p kind specifies the direction of the copy, and must be one of * ::cudaMemcpyHostToHost, ::cudaMemcpyHostToDevice, ::cudaMemcpyDeviceToHost, * ::cudaMemcpyDeviceToDevice, or ::cudaMemcpyDefault. Passing * ::cudaMemcpyDefault is recommended, in which case the type of transfer is * inferred from the pointer values. However, ::cudaMemcpyDefault is only * allowed on systems that support unified virtual addressing. Launching a * memcpy node with dst and src pointers that do not match the direction of * the copy results in an undefined behavior. * * \param node - Node to set the parameters for * \param dst - Destination memory address * \param src - Source memory address * \param count - Size in bytes to copy * \param kind - Type of transfer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaMemcpy, * ::cudaGraphMemcpyNodeSetParams, * ::cudaGraphAddMemcpyNode, * ::cudaGraphMemcpyNodeGetParams */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaGraphMemcpyNodeSetParams1D( cudaGraphNode_t node, void* dst, const void* src, size_t count, enum cudaMemcpyKind kind); #endif /** * \brief Creates a memset node and adds it to a graph * * Creates a new memset node and adds it to \p graph with \p numDependencies * dependencies specified via \p pDependencies. * It is possible for \p numDependencies to be 0, in which case the node will be placed * at the root of the graph. \p pDependencies may not have any duplicate entries. * A handle to the new node will be returned in \p pGraphNode. * * The element size must be 1, 2, or 4 bytes. * When the graph is launched, the node will perform the memset described by \p pMemsetParams. * * \param pGraphNode - Returns newly created node * \param graph - Graph to which to add the node * \param pDependencies - Dependencies of the node * \param numDependencies - Number of dependencies * \param pMemsetParams - Parameters for the memory set * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidDevice * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddNode, * ::cudaMemset2D, * ::cudaGraphMemsetNodeGetParams, * ::cudaGraphMemsetNodeSetParams, * ::cudaGraphCreate, * ::cudaGraphDestroyNode, * ::cudaGraphAddChildGraphNode, * ::cudaGraphAddEmptyNode, * ::cudaGraphAddKernelNode, * ::cudaGraphAddHostNode, * ::cudaGraphAddMemcpyNode */ extern __host__ cudaError_t CUDARTAPI cudaGraphAddMemsetNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, const struct cudaMemsetParams *pMemsetParams); /** * \brief Returns a memset node's parameters * * Returns the parameters of memset node \p node in \p pNodeParams. * * \param node - Node to get the parameters for * \param pNodeParams - Pointer to return the parameters * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaMemset2D, * ::cudaGraphAddMemsetNode, * ::cudaGraphMemsetNodeSetParams */ extern __host__ cudaError_t CUDARTAPI cudaGraphMemsetNodeGetParams(cudaGraphNode_t node, struct cudaMemsetParams *pNodeParams); /** * \brief Sets a memset node's parameters * * Sets the parameters of memset node \p node to \p pNodeParams. * * \param node - Node to set the parameters for * \param pNodeParams - Parameters to copy * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphNodeSetParams, * ::cudaMemset2D, * ::cudaGraphAddMemsetNode, * ::cudaGraphMemsetNodeGetParams */ extern __host__ cudaError_t CUDARTAPI cudaGraphMemsetNodeSetParams(cudaGraphNode_t node, const struct cudaMemsetParams *pNodeParams); /** * \brief Creates a host execution node and adds it to a graph * * Creates a new CPU execution node and adds it to \p graph with \p numDependencies * dependencies specified via \p pDependencies and arguments specified in \p pNodeParams. * It is possible for \p numDependencies to be 0, in which case the node will be placed * at the root of the graph. \p pDependencies may not have any duplicate entries. * A handle to the new node will be returned in \p pGraphNode. * * When the graph is launched, the node will invoke the specified CPU function. * Host nodes are not supported under MPS with pre-Volta GPUs. * * \param pGraphNode - Returns newly created node * \param graph - Graph to which to add the node * \param pDependencies - Dependencies of the node * \param numDependencies - Number of dependencies * \param pNodeParams - Parameters for the host node * * \return * ::cudaSuccess, * ::cudaErrorNotSupported, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddNode, * ::cudaLaunchHostFunc, * ::cudaGraphHostNodeGetParams, * ::cudaGraphHostNodeSetParams, * ::cudaGraphCreate, * ::cudaGraphDestroyNode, * ::cudaGraphAddChildGraphNode, * ::cudaGraphAddEmptyNode, * ::cudaGraphAddKernelNode, * ::cudaGraphAddMemcpyNode, * ::cudaGraphAddMemsetNode */ extern __host__ cudaError_t CUDARTAPI cudaGraphAddHostNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, const struct cudaHostNodeParams *pNodeParams); /** * \brief Returns a host node's parameters * * Returns the parameters of host node \p node in \p pNodeParams. * * \param node - Node to get the parameters for * \param pNodeParams - Pointer to return the parameters * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaLaunchHostFunc, * ::cudaGraphAddHostNode, * ::cudaGraphHostNodeSetParams */ extern __host__ cudaError_t CUDARTAPI cudaGraphHostNodeGetParams(cudaGraphNode_t node, struct cudaHostNodeParams *pNodeParams); /** * \brief Sets a host node's parameters * * Sets the parameters of host node \p node to \p nodeParams. * * \param node - Node to set the parameters for * \param pNodeParams - Parameters to copy * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphNodeSetParams, * ::cudaLaunchHostFunc, * ::cudaGraphAddHostNode, * ::cudaGraphHostNodeGetParams */ extern __host__ cudaError_t CUDARTAPI cudaGraphHostNodeSetParams(cudaGraphNode_t node, const struct cudaHostNodeParams *pNodeParams); /** * \brief Creates a child graph node and adds it to a graph * * Creates a new node which executes an embedded graph, and adds it to \p graph with * \p numDependencies dependencies specified via \p pDependencies. * It is possible for \p numDependencies to be 0, in which case the node will be placed * at the root of the graph. \p pDependencies may not have any duplicate entries. * A handle to the new node will be returned in \p pGraphNode. * * If \p hGraph contains allocation or free nodes, this call will return an error. * * The node executes an embedded child graph. The child graph is cloned in this call. * * \param pGraphNode - Returns newly created node * \param graph - Graph to which to add the node * \param pDependencies - Dependencies of the node * \param numDependencies - Number of dependencies * \param childGraph - The graph to clone into this node * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddNode, * ::cudaGraphChildGraphNodeGetGraph, * ::cudaGraphCreate, * ::cudaGraphDestroyNode, * ::cudaGraphAddEmptyNode, * ::cudaGraphAddKernelNode, * ::cudaGraphAddHostNode, * ::cudaGraphAddMemcpyNode, * ::cudaGraphAddMemsetNode, * ::cudaGraphClone */ extern __host__ cudaError_t CUDARTAPI cudaGraphAddChildGraphNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, cudaGraph_t childGraph); /** * \brief Gets a handle to the embedded graph of a child graph node * * Gets a handle to the embedded graph in a child graph node. This call * does not clone the graph. Changes to the graph will be reflected in * the node, and the node retains ownership of the graph. * * Allocation and free nodes cannot be added to the returned graph. * Attempting to do so will return an error. * * \param node - Node to get the embedded graph for * \param pGraph - Location to store a handle to the graph * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddChildGraphNode, * ::cudaGraphNodeFindInClone */ extern __host__ cudaError_t CUDARTAPI cudaGraphChildGraphNodeGetGraph(cudaGraphNode_t node, cudaGraph_t *pGraph); /** * \brief Creates an empty node and adds it to a graph * * Creates a new node which performs no operation, and adds it to \p graph with * \p numDependencies dependencies specified via \p pDependencies. * It is possible for \p numDependencies to be 0, in which case the node will be placed * at the root of the graph. \p pDependencies may not have any duplicate entries. * A handle to the new node will be returned in \p pGraphNode. * * An empty node performs no operation during execution, but can be used for * transitive ordering. For example, a phased execution graph with 2 groups of n * nodes with a barrier between them can be represented using an empty node and * 2*n dependency edges, rather than no empty node and n^2 dependency edges. * * \param pGraphNode - Returns newly created node * \param graph - Graph to which to add the node * \param pDependencies - Dependencies of the node * \param numDependencies - Number of dependencies * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddNode, * ::cudaGraphCreate, * ::cudaGraphDestroyNode, * ::cudaGraphAddChildGraphNode, * ::cudaGraphAddKernelNode, * ::cudaGraphAddHostNode, * ::cudaGraphAddMemcpyNode, * ::cudaGraphAddMemsetNode */ extern __host__ cudaError_t CUDARTAPI cudaGraphAddEmptyNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies); /** * \brief Creates an event record node and adds it to a graph * * Creates a new event record node and adds it to \p hGraph with \p numDependencies * dependencies specified via \p dependencies and event specified in \p event. * It is possible for \p numDependencies to be 0, in which case the node will be placed * at the root of the graph. \p dependencies may not have any duplicate entries. * A handle to the new node will be returned in \p phGraphNode. * * Each launch of the graph will record \p event to capture execution of the * node's dependencies. * * These nodes may not be used in loops or conditionals. * * \param phGraphNode - Returns newly created node * \param hGraph - Graph to which to add the node * \param dependencies - Dependencies of the node * \param numDependencies - Number of dependencies * \param event - Event for the node * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddNode, * ::cudaGraphAddEventWaitNode, * ::cudaEventRecordWithFlags, * ::cudaStreamWaitEvent, * ::cudaGraphCreate, * ::cudaGraphDestroyNode, * ::cudaGraphAddChildGraphNode, * ::cudaGraphAddEmptyNode, * ::cudaGraphAddKernelNode, * ::cudaGraphAddMemcpyNode, * ::cudaGraphAddMemsetNode */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaGraphAddEventRecordNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, cudaEvent_t event); #endif /** * \brief Returns the event associated with an event record node * * Returns the event of event record node \p hNode in \p event_out. * * \param hNode - Node to get the event for * \param event_out - Pointer to return the event * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddEventRecordNode, * ::cudaGraphEventRecordNodeSetEvent, * ::cudaGraphEventWaitNodeGetEvent, * ::cudaEventRecordWithFlags, * ::cudaStreamWaitEvent */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaGraphEventRecordNodeGetEvent(cudaGraphNode_t node, cudaEvent_t *event_out); #endif /** * \brief Sets an event record node's event * * Sets the event of event record node \p hNode to \p event. * * \param hNode - Node to set the event for * \param event - Event to use * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphNodeSetParams, * ::cudaGraphAddEventRecordNode, * ::cudaGraphEventRecordNodeGetEvent, * ::cudaGraphEventWaitNodeSetEvent, * ::cudaEventRecordWithFlags, * ::cudaStreamWaitEvent */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaGraphEventRecordNodeSetEvent(cudaGraphNode_t node, cudaEvent_t event); #endif /** * \brief Creates an event wait node and adds it to a graph * * Creates a new event wait node and adds it to \p hGraph with \p numDependencies * dependencies specified via \p dependencies and event specified in \p event. * It is possible for \p numDependencies to be 0, in which case the node will be placed * at the root of the graph. \p dependencies may not have any duplicate entries. * A handle to the new node will be returned in \p phGraphNode. * * The graph node will wait for all work captured in \p event. See ::cuEventRecord() * for details on what is captured by an event. The synchronization will be performed * efficiently on the device when applicable. \p event may be from a different context * or device than the launch stream. * * These nodes may not be used in loops or conditionals. * * \param phGraphNode - Returns newly created node * \param hGraph - Graph to which to add the node * \param dependencies - Dependencies of the node * \param numDependencies - Number of dependencies * \param event - Event for the node * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddNode, * ::cudaGraphAddEventRecordNode, * ::cudaEventRecordWithFlags, * ::cudaStreamWaitEvent, * ::cudaGraphCreate, * ::cudaGraphDestroyNode, * ::cudaGraphAddChildGraphNode, * ::cudaGraphAddEmptyNode, * ::cudaGraphAddKernelNode, * ::cudaGraphAddMemcpyNode, * ::cudaGraphAddMemsetNode */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaGraphAddEventWaitNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, cudaEvent_t event); #endif /** * \brief Returns the event associated with an event wait node * * Returns the event of event wait node \p hNode in \p event_out. * * \param hNode - Node to get the event for * \param event_out - Pointer to return the event * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddEventWaitNode, * ::cudaGraphEventWaitNodeSetEvent, * ::cudaGraphEventRecordNodeGetEvent, * ::cudaEventRecordWithFlags, * ::cudaStreamWaitEvent */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaGraphEventWaitNodeGetEvent(cudaGraphNode_t node, cudaEvent_t *event_out); #endif /** * \brief Sets an event wait node's event * * Sets the event of event wait node \p hNode to \p event. * * \param hNode - Node to set the event for * \param event - Event to use * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphNodeSetParams, * ::cudaGraphAddEventWaitNode, * ::cudaGraphEventWaitNodeGetEvent, * ::cudaGraphEventRecordNodeSetEvent, * ::cudaEventRecordWithFlags, * ::cudaStreamWaitEvent */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaGraphEventWaitNodeSetEvent(cudaGraphNode_t node, cudaEvent_t event); #endif /** * \brief Creates an external semaphore signal node and adds it to a graph * * Creates a new external semaphore signal node and adds it to \p graph with \p * numDependencies dependencies specified via \p dependencies and arguments specified * in \p nodeParams. It is possible for \p numDependencies to be 0, in which case the * node will be placed at the root of the graph. \p dependencies may not have any * duplicate entries. A handle to the new node will be returned in \p pGraphNode. * * Performs a signal operation on a set of externally allocated semaphore objects * when the node is launched. The operation(s) will occur after all of the node's * dependencies have completed. * * \param pGraphNode - Returns newly created node * \param graph - Graph to which to add the node * \param pDependencies - Dependencies of the node * \param numDependencies - Number of dependencies * \param nodeParams - Parameters for the node * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddNode, * ::cudaGraphExternalSemaphoresSignalNodeGetParams, * ::cudaGraphExternalSemaphoresSignalNodeSetParams, * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams, * ::cudaGraphAddExternalSemaphoresWaitNode, * ::cudaImportExternalSemaphore, * ::cudaSignalExternalSemaphoresAsync, * ::cudaWaitExternalSemaphoresAsync, * ::cudaGraphCreate, * ::cudaGraphDestroyNode, * ::cudaGraphAddEventRecordNode, * ::cudaGraphAddEventWaitNode, * ::cudaGraphAddChildGraphNode, * ::cudaGraphAddEmptyNode, * ::cudaGraphAddKernelNode, * ::cudaGraphAddMemcpyNode, * ::cudaGraphAddMemsetNode */ #if __CUDART_API_VERSION >= 11020 extern __host__ cudaError_t CUDARTAPI cudaGraphAddExternalSemaphoresSignalNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, const struct cudaExternalSemaphoreSignalNodeParams *nodeParams); #endif /** * \brief Returns an external semaphore signal node's parameters * * Returns the parameters of an external semaphore signal node \p hNode in \p params_out. * The \p extSemArray and \p paramsArray returned in \p params_out, * are owned by the node. This memory remains valid until the node is destroyed or its * parameters are modified, and should not be modified * directly. Use ::cudaGraphExternalSemaphoresSignalNodeSetParams to update the * parameters of this node. * * \param hNode - Node to get the parameters for * \param params_out - Pointer to return the parameters * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaLaunchKernel, * ::cudaGraphAddExternalSemaphoresSignalNode, * ::cudaGraphExternalSemaphoresSignalNodeSetParams, * ::cudaGraphAddExternalSemaphoresWaitNode, * ::cudaSignalExternalSemaphoresAsync, * ::cudaWaitExternalSemaphoresAsync */ #if __CUDART_API_VERSION >= 11020 extern __host__ cudaError_t CUDARTAPI cudaGraphExternalSemaphoresSignalNodeGetParams(cudaGraphNode_t hNode, struct cudaExternalSemaphoreSignalNodeParams *params_out); #endif /** * \brief Sets an external semaphore signal node's parameters * * Sets the parameters of an external semaphore signal node \p hNode to \p nodeParams. * * \param hNode - Node to set the parameters for * \param nodeParams - Parameters to copy * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphNodeSetParams, * ::cudaGraphAddExternalSemaphoresSignalNode, * ::cudaGraphExternalSemaphoresSignalNodeSetParams, * ::cudaGraphAddExternalSemaphoresWaitNode, * ::cudaSignalExternalSemaphoresAsync, * ::cudaWaitExternalSemaphoresAsync */ #if __CUDART_API_VERSION >= 11020 extern __host__ cudaError_t CUDARTAPI cudaGraphExternalSemaphoresSignalNodeSetParams(cudaGraphNode_t hNode, const struct cudaExternalSemaphoreSignalNodeParams *nodeParams); #endif /** * \brief Creates an external semaphore wait node and adds it to a graph * * Creates a new external semaphore wait node and adds it to \p graph with \p numDependencies * dependencies specified via \p dependencies and arguments specified in \p nodeParams. * It is possible for \p numDependencies to be 0, in which case the node will be placed * at the root of the graph. \p dependencies may not have any duplicate entries. A handle * to the new node will be returned in \p pGraphNode. * * Performs a wait operation on a set of externally allocated semaphore objects * when the node is launched. The node's dependencies will not be launched until * the wait operation has completed. * * \param pGraphNode - Returns newly created node * \param graph - Graph to which to add the node * \param pDependencies - Dependencies of the node * \param numDependencies - Number of dependencies * \param nodeParams - Parameters for the node * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddNode, * ::cudaGraphExternalSemaphoresWaitNodeGetParams, * ::cudaGraphExternalSemaphoresWaitNodeSetParams, * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams, * ::cudaGraphAddExternalSemaphoresSignalNode, * ::cudaImportExternalSemaphore, * ::cudaSignalExternalSemaphoresAsync, * ::cudaWaitExternalSemaphoresAsync, * ::cudaGraphCreate, * ::cudaGraphDestroyNode, * ::cudaGraphAddEventRecordNode, * ::cudaGraphAddEventWaitNode, * ::cudaGraphAddChildGraphNode, * ::cudaGraphAddEmptyNode, * ::cudaGraphAddKernelNode, * ::cudaGraphAddMemcpyNode, * ::cudaGraphAddMemsetNode */ #if __CUDART_API_VERSION >= 11020 extern __host__ cudaError_t CUDARTAPI cudaGraphAddExternalSemaphoresWaitNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, const struct cudaExternalSemaphoreWaitNodeParams *nodeParams); #endif /** * \brief Returns an external semaphore wait node's parameters * * Returns the parameters of an external semaphore wait node \p hNode in \p params_out. * The \p extSemArray and \p paramsArray returned in \p params_out, * are owned by the node. This memory remains valid until the node is destroyed or its * parameters are modified, and should not be modified * directly. Use ::cudaGraphExternalSemaphoresSignalNodeSetParams to update the * parameters of this node. * * \param hNode - Node to get the parameters for * \param params_out - Pointer to return the parameters * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaLaunchKernel, * ::cudaGraphAddExternalSemaphoresWaitNode, * ::cudaGraphExternalSemaphoresWaitNodeSetParams, * ::cudaGraphAddExternalSemaphoresWaitNode, * ::cudaSignalExternalSemaphoresAsync, * ::cudaWaitExternalSemaphoresAsync */ #if __CUDART_API_VERSION >= 11020 extern __host__ cudaError_t CUDARTAPI cudaGraphExternalSemaphoresWaitNodeGetParams(cudaGraphNode_t hNode, struct cudaExternalSemaphoreWaitNodeParams *params_out); #endif /** * \brief Sets an external semaphore wait node's parameters * * Sets the parameters of an external semaphore wait node \p hNode to \p nodeParams. * * \param hNode - Node to set the parameters for * \param nodeParams - Parameters to copy * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphNodeSetParams, * ::cudaGraphAddExternalSemaphoresWaitNode, * ::cudaGraphExternalSemaphoresWaitNodeSetParams, * ::cudaGraphAddExternalSemaphoresWaitNode, * ::cudaSignalExternalSemaphoresAsync, * ::cudaWaitExternalSemaphoresAsync */ #if __CUDART_API_VERSION >= 11020 extern __host__ cudaError_t CUDARTAPI cudaGraphExternalSemaphoresWaitNodeSetParams(cudaGraphNode_t hNode, const struct cudaExternalSemaphoreWaitNodeParams *nodeParams); #endif /** * \brief Creates an allocation node and adds it to a graph * * Creates a new allocation node and adds it to \p graph with \p numDependencies * dependencies specified via \p pDependencies and arguments specified in \p nodeParams. * It is possible for \p numDependencies to be 0, in which case the node will be placed * at the root of the graph. \p pDependencies may not have any duplicate entries. A handle * to the new node will be returned in \p pGraphNode. * * \param pGraphNode - Returns newly created node * \param graph - Graph to which to add the node * \param pDependencies - Dependencies of the node * \param numDependencies - Number of dependencies * \param nodeParams - Parameters for the node * * When ::cudaGraphAddMemAllocNode creates an allocation node, it returns the address of the allocation in * \p nodeParams.dptr. The allocation's address remains fixed across instantiations and launches. * * If the allocation is freed in the same graph, by creating a free node using ::cudaGraphAddMemFreeNode, * the allocation can be accessed by nodes ordered after the allocation node but before the free node. * These allocations cannot be freed outside the owning graph, and they can only be freed once in the * owning graph. * * If the allocation is not freed in the same graph, then it can be accessed not only by nodes in the * graph which are ordered after the allocation node, but also by stream operations ordered after the * graph's execution but before the allocation is freed. * * Allocations which are not freed in the same graph can be freed by: * - passing the allocation to ::cudaMemFreeAsync or ::cudaMemFree; * - launching a graph with a free node for that allocation; or * - specifying ::cudaGraphInstantiateFlagAutoFreeOnLaunch during instantiation, which makes * each launch behave as though it called ::cudaMemFreeAsync for every unfreed allocation. * * It is not possible to free an allocation in both the owning graph and another graph. If the allocation * is freed in the same graph, a free node cannot be added to another graph. If the allocation is freed * in another graph, a free node can no longer be added to the owning graph. * * The following restrictions apply to graphs which contain allocation and/or memory free nodes: * - Nodes and edges of the graph cannot be deleted. * - The graph cannot be used in a child node. * - Only one instantiation of the graph may exist at any point in time. * - The graph cannot be cloned. * * \return * ::cudaSuccess, * ::cudaErrorCudartUnloading, * ::cudaErrorInitializationError, * ::cudaErrorNotSupported, * ::cudaErrorInvalidValue, * ::cudaErrorOutOfMemory * \note_graph_thread_safety * \notefnerr * * \sa * ::cudaGraphAddNode, * ::cudaGraphAddMemFreeNode, * ::cudaGraphMemAllocNodeGetParams, * ::cudaDeviceGraphMemTrim, * ::cudaDeviceGetGraphMemAttribute, * ::cudaDeviceSetGraphMemAttribute, * ::cudaMallocAsync, * ::cudaFreeAsync, * ::cudaGraphCreate, * ::cudaGraphDestroyNode, * ::cudaGraphAddChildGraphNode, * ::cudaGraphAddEmptyNode, * ::cudaGraphAddEventRecordNode, * ::cudaGraphAddEventWaitNode, * ::cudaGraphAddExternalSemaphoresSignalNode, * ::cudaGraphAddExternalSemaphoresWaitNode, * ::cudaGraphAddKernelNode, * ::cudaGraphAddMemcpyNode, * ::cudaGraphAddMemsetNode */ #if __CUDART_API_VERSION >= 11040 extern __host__ cudaError_t CUDARTAPI cudaGraphAddMemAllocNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, struct cudaMemAllocNodeParams *nodeParams); #endif /** * \brief Returns a memory alloc node's parameters * * Returns the parameters of a memory alloc node \p hNode in \p params_out. * The \p poolProps and \p accessDescs returned in \p params_out, are owned by the * node. This memory remains valid until the node is destroyed. The returned * parameters must not be modified. * * \param node - Node to get the parameters for * \param params_out - Pointer to return the parameters * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddMemAllocNode, * ::cudaGraphMemFreeNodeGetParams */ #if __CUDART_API_VERSION >= 11040 extern __host__ cudaError_t CUDARTAPI cudaGraphMemAllocNodeGetParams(cudaGraphNode_t node, struct cudaMemAllocNodeParams *params_out); #endif /** * \brief Creates a memory free node and adds it to a graph * * Creates a new memory free node and adds it to \p graph with \p numDependencies * dependencies specified via \p pDependencies and address specified in \p dptr. * It is possible for \p numDependencies to be 0, in which case the node will be placed * at the root of the graph. \p pDependencies may not have any duplicate entries. A handle * to the new node will be returned in \p pGraphNode. * * \param pGraphNode - Returns newly created node * \param graph - Graph to which to add the node * \param pDependencies - Dependencies of the node * \param numDependencies - Number of dependencies * \param dptr - Address of memory to free * * ::cudaGraphAddMemFreeNode will return ::cudaErrorInvalidValue if the user attempts to free: * - an allocation twice in the same graph. * - an address that was not returned by an allocation node. * - an invalid address. * * The following restrictions apply to graphs which contain allocation and/or memory free nodes: * - Nodes and edges of the graph cannot be deleted. * - The graph cannot be used in a child node. * - Only one instantiation of the graph may exist at any point in time. * - The graph cannot be cloned. * * \return * ::cudaSuccess, * ::cudaErrorCudartUnloading, * ::cudaErrorInitializationError, * ::cudaErrorNotSupported, * ::cudaErrorInvalidValue, * ::cudaErrorOutOfMemory * \note_graph_thread_safety * \notefnerr * * \sa * ::cudaGraphAddNode, * ::cudaGraphAddMemAllocNode, * ::cudaGraphMemFreeNodeGetParams, * ::cudaDeviceGraphMemTrim, * ::cudaDeviceGetGraphMemAttribute, * ::cudaDeviceSetGraphMemAttribute, * ::cudaMallocAsync, * ::cudaFreeAsync, * ::cudaGraphCreate, * ::cudaGraphDestroyNode, * ::cudaGraphAddChildGraphNode, * ::cudaGraphAddEmptyNode, * ::cudaGraphAddEventRecordNode, * ::cudaGraphAddEventWaitNode, * ::cudaGraphAddExternalSemaphoresSignalNode, * ::cudaGraphAddExternalSemaphoresWaitNode, * ::cudaGraphAddKernelNode, * ::cudaGraphAddMemcpyNode, * ::cudaGraphAddMemsetNode */ #if __CUDART_API_VERSION >= 11040 extern __host__ cudaError_t CUDARTAPI cudaGraphAddMemFreeNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, void *dptr); #endif /** * \brief Returns a memory free node's parameters * * Returns the address of a memory free node \p hNode in \p dptr_out. * * \param node - Node to get the parameters for * \param dptr_out - Pointer to return the device address * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddMemFreeNode, * ::cudaGraphMemFreeNodeGetParams */ #if __CUDART_API_VERSION >= 11040 extern __host__ cudaError_t CUDARTAPI cudaGraphMemFreeNodeGetParams(cudaGraphNode_t node, void *dptr_out); #endif /** * \brief Free unused memory that was cached on the specified device for use with graphs back to the OS. * * Blocks which are not in use by a graph that is either currently executing or scheduled to execute are * freed back to the operating system. * * \param device - The device for which cached memory should be freed. * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddMemAllocNode, * ::cudaGraphAddMemFreeNode, * ::cudaDeviceGetGraphMemAttribute, * ::cudaDeviceSetGraphMemAttribute, * ::cudaMallocAsync, * ::cudaFreeAsync */ #if __CUDART_API_VERSION >= 11040 extern __host__ cudaError_t CUDARTAPI cudaDeviceGraphMemTrim(int device); #endif /** * \brief Query asynchronous allocation attributes related to graphs * * Valid attributes are: * * - ::cudaGraphMemAttrUsedMemCurrent: Amount of memory, in bytes, currently associated with graphs * - ::cudaGraphMemAttrUsedMemHigh: High watermark of memory, in bytes, associated with graphs since the * last time it was reset. High watermark can only be reset to zero. * - ::cudaGraphMemAttrReservedMemCurrent: Amount of memory, in bytes, currently allocated for use by * the CUDA graphs asynchronous allocator. * - ::cudaGraphMemAttrReservedMemHigh: High watermark of memory, in bytes, currently allocated for use by * the CUDA graphs asynchronous allocator. * * \param device - Specifies the scope of the query * \param attr - attribute to get * \param value - retrieved value * * \return * ::cudaSuccess, * ::cudaErrorInvalidDevice * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaDeviceSetGraphMemAttribute, * ::cudaGraphAddMemAllocNode, * ::cudaGraphAddMemFreeNode, * ::cudaDeviceGraphMemTrim, * ::cudaMallocAsync, * ::cudaFreeAsync */ #if __CUDART_API_VERSION >= 11040 extern __host__ cudaError_t CUDARTAPI cudaDeviceGetGraphMemAttribute(int device, enum cudaGraphMemAttributeType attr, void* value); #endif /** * \brief Set asynchronous allocation attributes related to graphs * * Valid attributes are: * * - ::cudaGraphMemAttrUsedMemHigh: High watermark of memory, in bytes, associated with graphs since the * last time it was reset. High watermark can only be reset to zero. * - ::cudaGraphMemAttrReservedMemHigh: High watermark of memory, in bytes, currently allocated for use by * the CUDA graphs asynchronous allocator. * * \param device - Specifies the scope of the query * \param attr - attribute to get * \param value - pointer to value to set * * \return * ::cudaSuccess, * ::cudaErrorInvalidDevice * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaDeviceGetGraphMemAttribute, * ::cudaGraphAddMemAllocNode, * ::cudaGraphAddMemFreeNode, * ::cudaDeviceGraphMemTrim, * ::cudaMallocAsync, * ::cudaFreeAsync */ #if __CUDART_API_VERSION >= 11040 extern __host__ cudaError_t CUDARTAPI cudaDeviceSetGraphMemAttribute(int device, enum cudaGraphMemAttributeType attr, void* value); #endif /** * \brief Clones a graph * * This function creates a copy of \p originalGraph and returns it in \p pGraphClone. * All parameters are copied into the cloned graph. The original graph may be modified * after this call without affecting the clone. * * Child graph nodes in the original graph are recursively copied into the clone. * * \param pGraphClone - Returns newly created cloned graph * \param originalGraph - Graph to clone * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorMemoryAllocation * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphCreate, * ::cudaGraphNodeFindInClone */ extern __host__ cudaError_t CUDARTAPI cudaGraphClone(cudaGraph_t *pGraphClone, cudaGraph_t originalGraph); /** * \brief Finds a cloned version of a node * * This function returns the node in \p clonedGraph corresponding to \p originalNode * in the original graph. * * \p clonedGraph must have been cloned from \p originalGraph via ::cudaGraphClone. * \p originalNode must have been in \p originalGraph at the time of the call to * ::cudaGraphClone, and the corresponding cloned node in \p clonedGraph must not have * been removed. The cloned node is then returned via \p pClonedNode. * * \param pNode - Returns handle to the cloned node * \param originalNode - Handle to the original node * \param clonedGraph - Cloned graph to query * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphClone */ extern __host__ cudaError_t CUDARTAPI cudaGraphNodeFindInClone(cudaGraphNode_t *pNode, cudaGraphNode_t originalNode, cudaGraph_t clonedGraph); /** * \brief Returns a node's type * * Returns the node type of \p node in \p pType. * * \param node - Node to query * \param pType - Pointer to return the node type * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphGetNodes, * ::cudaGraphGetRootNodes, * ::cudaGraphChildGraphNodeGetGraph, * ::cudaGraphKernelNodeGetParams, * ::cudaGraphKernelNodeSetParams, * ::cudaGraphHostNodeGetParams, * ::cudaGraphHostNodeSetParams, * ::cudaGraphMemcpyNodeGetParams, * ::cudaGraphMemcpyNodeSetParams, * ::cudaGraphMemsetNodeGetParams, * ::cudaGraphMemsetNodeSetParams */ extern __host__ cudaError_t CUDARTAPI cudaGraphNodeGetType(cudaGraphNode_t node, enum cudaGraphNodeType *pType); /** * \brief Returns a graph's nodes * * Returns a list of \p graph's nodes. \p nodes may be NULL, in which case this * function will return the number of nodes in \p numNodes. Otherwise, * \p numNodes entries will be filled in. If \p numNodes is higher than the actual * number of nodes, the remaining entries in \p nodes will be set to NULL, and the * number of nodes actually obtained will be returned in \p numNodes. * * \param graph - Graph to query * \param nodes - Pointer to return the nodes * \param numNodes - See description * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphCreate, * ::cudaGraphGetRootNodes, * ::cudaGraphGetEdges, * ::cudaGraphNodeGetType, * ::cudaGraphNodeGetDependencies, * ::cudaGraphNodeGetDependentNodes */ extern __host__ cudaError_t CUDARTAPI cudaGraphGetNodes(cudaGraph_t graph, cudaGraphNode_t *nodes, size_t *numNodes); /** * \brief Returns a graph's root nodes * * Returns a list of \p graph's root nodes. \p pRootNodes may be NULL, in which case this * function will return the number of root nodes in \p pNumRootNodes. Otherwise, * \p pNumRootNodes entries will be filled in. If \p pNumRootNodes is higher than the actual * number of root nodes, the remaining entries in \p pRootNodes will be set to NULL, and the * number of nodes actually obtained will be returned in \p pNumRootNodes. * * \param graph - Graph to query * \param pRootNodes - Pointer to return the root nodes * \param pNumRootNodes - See description * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphCreate, * ::cudaGraphGetNodes, * ::cudaGraphGetEdges, * ::cudaGraphNodeGetType, * ::cudaGraphNodeGetDependencies, * ::cudaGraphNodeGetDependentNodes */ extern __host__ cudaError_t CUDARTAPI cudaGraphGetRootNodes(cudaGraph_t graph, cudaGraphNode_t *pRootNodes, size_t *pNumRootNodes); /** * \brief Returns a graph's dependency edges * * Returns a list of \p graph's dependency edges. Edges are returned via corresponding * indices in \p from and \p to; that is, the node in \p to[i] has a dependency on the * node in \p from[i]. \p from and \p to may both be NULL, in which * case this function only returns the number of edges in \p numEdges. Otherwise, * \p numEdges entries will be filled in. If \p numEdges is higher than the actual * number of edges, the remaining entries in \p from and \p to will be set to NULL, and * the number of edges actually returned will be written to \p numEdges. * * \param graph - Graph to get the edges from * \param from - Location to return edge endpoints * \param to - Location to return edge endpoints * \param numEdges - See description * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphGetNodes, * ::cudaGraphGetRootNodes, * ::cudaGraphAddDependencies, * ::cudaGraphRemoveDependencies, * ::cudaGraphNodeGetDependencies, * ::cudaGraphNodeGetDependentNodes */ extern __host__ cudaError_t CUDARTAPI cudaGraphGetEdges(cudaGraph_t graph, cudaGraphNode_t *from, cudaGraphNode_t *to, size_t *numEdges); /** * \brief Returns a graph's dependency edges (12.3+) * * Returns a list of \p graph's dependency edges. Edges are returned via corresponding * indices in \p from, \p to and \p edgeData; that is, the node in \p to[i] has a * dependency on the node in \p from[i] with data \p edgeData[i]. \p from and \p to may * both be NULL, in which case this function only returns the number of edges in * \p numEdges. Otherwise, \p numEdges entries will be filled in. If \p numEdges is higher * than the actual number of edges, the remaining entries in \p from and \p to will be * set to NULL, and the number of edges actually returned will be written to \p numEdges. * \p edgeData may alone be NULL, in which case the edges must all have default (zeroed) * edge data. Attempting a losst query via NULL \p edgeData will result in * ::cudaErrorLossyQuery. If \p edgeData is non-NULL then \p from and \p to must be as * well. * * \param graph - Graph to get the edges from * \param from - Location to return edge endpoints * \param to - Location to return edge endpoints * \param edgeData - Optional location to return edge data * \param numEdges - See description * * \return * ::cudaSuccess, * ::cudaErrorLossyQuery, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphGetNodes, * ::cudaGraphGetRootNodes, * ::cudaGraphAddDependencies, * ::cudaGraphRemoveDependencies, * ::cudaGraphNodeGetDependencies, * ::cudaGraphNodeGetDependentNodes */ extern __host__ cudaError_t CUDARTAPI cudaGraphGetEdges_v2(cudaGraph_t graph, cudaGraphNode_t *from, cudaGraphNode_t *to, cudaGraphEdgeData *edgeData, size_t *numEdges); /** * \brief Returns a node's dependencies * * Returns a list of \p node's dependencies. \p pDependencies may be NULL, in which case this * function will return the number of dependencies in \p pNumDependencies. Otherwise, * \p pNumDependencies entries will be filled in. If \p pNumDependencies is higher than the actual * number of dependencies, the remaining entries in \p pDependencies will be set to NULL, and the * number of nodes actually obtained will be returned in \p pNumDependencies. * * \param node - Node to query * \param pDependencies - Pointer to return the dependencies * \param pNumDependencies - See description * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphNodeGetDependentNodes, * ::cudaGraphGetNodes, * ::cudaGraphGetRootNodes, * ::cudaGraphGetEdges, * ::cudaGraphAddDependencies, * ::cudaGraphRemoveDependencies */ extern __host__ cudaError_t CUDARTAPI cudaGraphNodeGetDependencies(cudaGraphNode_t node, cudaGraphNode_t *pDependencies, size_t *pNumDependencies); /** * \brief Returns a node's dependencies (12.3+) * * Returns a list of \p node's dependencies. \p pDependencies may be NULL, in which case this * function will return the number of dependencies in \p pNumDependencies. Otherwise, * \p pNumDependencies entries will be filled in. If \p pNumDependencies is higher than the actual * number of dependencies, the remaining entries in \p pDependencies will be set to NULL, and the * number of nodes actually obtained will be returned in \p pNumDependencies. * * Note that if an edge has non-zero (non-default) edge data and \p edgeData is NULL, * this API will return ::cudaErrorLossyQuery. If \p edgeData is non-NULL, then * \p pDependencies must be as well. * * \param node - Node to query * \param pDependencies - Pointer to return the dependencies * \param edgeData - Optional array to return edge data for each dependency * \param pNumDependencies - See description * * \return * ::cudaSuccess, * ::cudaErrorLossyQuery, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphNodeGetDependentNodes, * ::cudaGraphGetNodes, * ::cudaGraphGetRootNodes, * ::cudaGraphGetEdges, * ::cudaGraphAddDependencies, * ::cudaGraphRemoveDependencies */ extern __host__ cudaError_t CUDARTAPI cudaGraphNodeGetDependencies_v2(cudaGraphNode_t node, cudaGraphNode_t *pDependencies, cudaGraphEdgeData *edgeData, size_t *pNumDependencies); /** * \brief Returns a node's dependent nodes * * Returns a list of \p node's dependent nodes. \p pDependentNodes may be NULL, in which * case this function will return the number of dependent nodes in \p pNumDependentNodes. * Otherwise, \p pNumDependentNodes entries will be filled in. If \p pNumDependentNodes is * higher than the actual number of dependent nodes, the remaining entries in * \p pDependentNodes will be set to NULL, and the number of nodes actually obtained will * be returned in \p pNumDependentNodes. * * \param node - Node to query * \param pDependentNodes - Pointer to return the dependent nodes * \param pNumDependentNodes - See description * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphNodeGetDependencies, * ::cudaGraphGetNodes, * ::cudaGraphGetRootNodes, * ::cudaGraphGetEdges, * ::cudaGraphAddDependencies, * ::cudaGraphRemoveDependencies */ extern __host__ cudaError_t CUDARTAPI cudaGraphNodeGetDependentNodes(cudaGraphNode_t node, cudaGraphNode_t *pDependentNodes, size_t *pNumDependentNodes); /** * \brief Returns a node's dependent nodes (12.3+) * * Returns a list of \p node's dependent nodes. \p pDependentNodes may be NULL, in which * case this function will return the number of dependent nodes in \p pNumDependentNodes. * Otherwise, \p pNumDependentNodes entries will be filled in. If \p pNumDependentNodes is * higher than the actual number of dependent nodes, the remaining entries in * \p pDependentNodes will be set to NULL, and the number of nodes actually obtained will * be returned in \p pNumDependentNodes. * * Note that if an edge has non-zero (non-default) edge data and \p edgeData is NULL, * this API will return ::cudaErrorLossyQuery. If \p edgeData is non-NULL, then * \p pDependentNodes must be as well. * * \param node - Node to query * \param pDependentNodes - Pointer to return the dependent nodes * \param edgeData - Optional pointer to return edge data for dependent nodes * \param pNumDependentNodes - See description * * \return * ::cudaSuccess, * ::cudaErrorLossyQuery, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphNodeGetDependencies, * ::cudaGraphGetNodes, * ::cudaGraphGetRootNodes, * ::cudaGraphGetEdges, * ::cudaGraphAddDependencies, * ::cudaGraphRemoveDependencies */ extern __host__ cudaError_t CUDARTAPI cudaGraphNodeGetDependentNodes_v2(cudaGraphNode_t node, cudaGraphNode_t *pDependentNodes, cudaGraphEdgeData *edgeData, size_t *pNumDependentNodes); /** * \brief Adds dependency edges to a graph. * * The number of dependencies to be added is defined by \p numDependencies * Elements in \p pFrom and \p pTo at corresponding indices define a dependency. * Each node in \p pFrom and \p pTo must belong to \p graph. * * If \p numDependencies is 0, elements in \p pFrom and \p pTo will be ignored. * Specifying an existing dependency will return an error. * * \param graph - Graph to which dependencies are added * \param from - Array of nodes that provide the dependencies * \param to - Array of dependent nodes * \param numDependencies - Number of dependencies to be added * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphRemoveDependencies, * ::cudaGraphGetEdges, * ::cudaGraphNodeGetDependencies, * ::cudaGraphNodeGetDependentNodes */ extern __host__ cudaError_t CUDARTAPI cudaGraphAddDependencies(cudaGraph_t graph, const cudaGraphNode_t *from, const cudaGraphNode_t *to, size_t numDependencies); /** * \brief Adds dependency edges to a graph. (12.3+) * * The number of dependencies to be added is defined by \p numDependencies * Elements in \p pFrom and \p pTo at corresponding indices define a dependency. * Each node in \p pFrom and \p pTo must belong to \p graph. * * If \p numDependencies is 0, elements in \p pFrom and \p pTo will be ignored. * Specifying an existing dependency will return an error. * * \param graph - Graph to which dependencies are added * \param from - Array of nodes that provide the dependencies * \param to - Array of dependent nodes * \param edgeData - Optional array of edge data. If NULL, default (zeroed) edge data is assumed. * \param numDependencies - Number of dependencies to be added * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphRemoveDependencies, * ::cudaGraphGetEdges, * ::cudaGraphNodeGetDependencies, * ::cudaGraphNodeGetDependentNodes */ extern __host__ cudaError_t CUDARTAPI cudaGraphAddDependencies_v2(cudaGraph_t graph, const cudaGraphNode_t *from, const cudaGraphNode_t *to, const cudaGraphEdgeData *edgeData, size_t numDependencies); /** * \brief Removes dependency edges from a graph. * * The number of \p pDependencies to be removed is defined by \p numDependencies. * Elements in \p pFrom and \p pTo at corresponding indices define a dependency. * Each node in \p pFrom and \p pTo must belong to \p graph. * * If \p numDependencies is 0, elements in \p pFrom and \p pTo will be ignored. * Specifying a non-existing dependency will return an error. * * \param graph - Graph from which to remove dependencies * \param from - Array of nodes that provide the dependencies * \param to - Array of dependent nodes * \param numDependencies - Number of dependencies to be removed * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddDependencies, * ::cudaGraphGetEdges, * ::cudaGraphNodeGetDependencies, * ::cudaGraphNodeGetDependentNodes */ extern __host__ cudaError_t CUDARTAPI cudaGraphRemoveDependencies(cudaGraph_t graph, const cudaGraphNode_t *from, const cudaGraphNode_t *to, size_t numDependencies); /** * \brief Removes dependency edges from a graph. (12.3+) * * The number of \p pDependencies to be removed is defined by \p numDependencies. * Elements in \p pFrom and \p pTo at corresponding indices define a dependency. * Each node in \p pFrom and \p pTo must belong to \p graph. * * If \p numDependencies is 0, elements in \p pFrom and \p pTo will be ignored. * Specifying an edge that does not exist in the graph, with data matching * \p edgeData, results in an error. \p edgeData is nullable, which is equivalent * to passing default (zeroed) data for each edge. * * \param graph - Graph from which to remove dependencies * \param from - Array of nodes that provide the dependencies * \param to - Array of dependent nodes * \param edgeData - Optional array of edge data. If NULL, edge data is assumed to * be default (zeroed). * \param numDependencies - Number of dependencies to be removed * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddDependencies, * ::cudaGraphGetEdges, * ::cudaGraphNodeGetDependencies, * ::cudaGraphNodeGetDependentNodes */ extern __host__ cudaError_t CUDARTAPI cudaGraphRemoveDependencies_v2(cudaGraph_t graph, const cudaGraphNode_t *from, const cudaGraphNode_t *to, const cudaGraphEdgeData *edgeData, size_t numDependencies); /** * \brief Remove a node from the graph * * Removes \p node from its graph. This operation also severs any dependencies of other nodes * on \p node and vice versa. * * Dependencies cannot be removed from graphs which contain allocation or free nodes. * Any attempt to do so will return an error. * * \param node - Node to remove * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * \note_destroy_ub * * \sa * ::cudaGraphAddChildGraphNode, * ::cudaGraphAddEmptyNode, * ::cudaGraphAddKernelNode, * ::cudaGraphAddHostNode, * ::cudaGraphAddMemcpyNode, * ::cudaGraphAddMemsetNode */ extern __host__ cudaError_t CUDARTAPI cudaGraphDestroyNode(cudaGraphNode_t node); /** * \brief Creates an executable graph from a graph * * Instantiates \p graph as an executable graph. The graph is validated for any * structural constraints or intra-node constraints which were not previously * validated. If instantiation is successful, a handle to the instantiated graph * is returned in \p pGraphExec. * * The \p flags parameter controls the behavior of instantiation and subsequent * graph launches. Valid flags are: * * - ::cudaGraphInstantiateFlagAutoFreeOnLaunch, which configures a * graph containing memory allocation nodes to automatically free any * unfreed memory allocations before the graph is relaunched. * * - ::cudaGraphInstantiateFlagDeviceLaunch, which configures the graph for launch * from the device. If this flag is passed, the executable graph handle returned can be * used to launch the graph from both the host and device. This flag cannot be used in * conjunction with ::cudaGraphInstantiateFlagAutoFreeOnLaunch. * * - ::cudaGraphInstantiateFlagUseNodePriority, which causes the graph * to use the priorities from the per-node attributes rather than the priority * of the launch stream during execution. Note that priorities are only available * on kernel nodes, and are copied from stream priority during stream capture. * * If \p graph contains any allocation or free nodes, there can be at most one * executable graph in existence for that graph at a time. An attempt to * instantiate a second executable graph before destroying the first with * ::cudaGraphExecDestroy will result in an error. * The same also applies if \p graph contains any device-updatable kernel nodes. * * Graphs instantiated for launch on the device have additional restrictions which do not * apply to host graphs: * * - The graph's nodes must reside on a single device. * - The graph can only contain kernel nodes, memcpy nodes, memset nodes, and child graph nodes. * - The graph cannot be empty and must contain at least one kernel, memcpy, or memset node. * Operation-specific restrictions are outlined below. * - Kernel nodes: * - Use of CUDA Dynamic Parallelism is not permitted. * - Cooperative launches are permitted as long as MPS is not in use. * - Memcpy nodes: * - Only copies involving device memory and/or pinned device-mapped host memory are permitted. * - Copies involving CUDA arrays are not permitted. * - Both operands must be accessible from the current device, and the current device must * match the device of other nodes in the graph. * * If \p graph is not instantiated for launch on the device but contains kernels which * call device-side cudaGraphLaunch() from multiple devices, this will result in an error. * * \param pGraphExec - Returns instantiated graph * \param graph - Graph to instantiate * \param flags - Flags to control instantiation. See ::CUgraphInstantiate_flags. * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphInstantiateWithFlags, * ::cudaGraphCreate, * ::cudaGraphUpload, * ::cudaGraphLaunch, * ::cudaGraphExecDestroy */ extern __host__ cudaError_t CUDARTAPI cudaGraphInstantiate(cudaGraphExec_t *pGraphExec, cudaGraph_t graph, unsigned long long flags __dv(0)); /** * \brief Creates an executable graph from a graph * * Instantiates \p graph as an executable graph. The graph is validated for any * structural constraints or intra-node constraints which were not previously * validated. If instantiation is successful, a handle to the instantiated graph * is returned in \p pGraphExec. * * The \p flags parameter controls the behavior of instantiation and subsequent * graph launches. Valid flags are: * * - ::cudaGraphInstantiateFlagAutoFreeOnLaunch, which configures a * graph containing memory allocation nodes to automatically free any * unfreed memory allocations before the graph is relaunched. * * - ::cudaGraphInstantiateFlagDeviceLaunch, which configures the graph for launch * from the device. If this flag is passed, the executable graph handle returned can be * used to launch the graph from both the host and device. This flag can only be used * on platforms which support unified addressing. This flag cannot be used in * conjunction with ::cudaGraphInstantiateFlagAutoFreeOnLaunch. * * - ::cudaGraphInstantiateFlagUseNodePriority, which causes the graph * to use the priorities from the per-node attributes rather than the priority * of the launch stream during execution. Note that priorities are only available * on kernel nodes, and are copied from stream priority during stream capture. * * If \p graph contains any allocation or free nodes, there can be at most one * executable graph in existence for that graph at a time. An attempt to * instantiate a second executable graph before destroying the first with * ::cudaGraphExecDestroy will result in an error. * The same also applies if \p graph contains any device-updatable kernel nodes. * * If \p graph contains kernels which call device-side cudaGraphLaunch() from multiple * devices, this will result in an error. * * Graphs instantiated for launch on the device have additional restrictions which do not * apply to host graphs: * * - The graph's nodes must reside on a single device. * - The graph can only contain kernel nodes, memcpy nodes, memset nodes, and child graph nodes. * - The graph cannot be empty and must contain at least one kernel, memcpy, or memset node. * Operation-specific restrictions are outlined below. * - Kernel nodes: * - Use of CUDA Dynamic Parallelism is not permitted. * - Cooperative launches are permitted as long as MPS is not in use. * - Memcpy nodes: * - Only copies involving device memory and/or pinned device-mapped host memory are permitted. * - Copies involving CUDA arrays are not permitted. * - Both operands must be accessible from the current device, and the current device must * match the device of other nodes in the graph. * * \param pGraphExec - Returns instantiated graph * \param graph - Graph to instantiate * \param flags - Flags to control instantiation. See ::CUgraphInstantiate_flags. * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphInstantiate, * ::cudaGraphCreate, * ::cudaGraphUpload, * ::cudaGraphLaunch, * ::cudaGraphExecDestroy */ #if __CUDART_API_VERSION >= 11040 extern __host__ cudaError_t CUDARTAPI cudaGraphInstantiateWithFlags(cudaGraphExec_t *pGraphExec, cudaGraph_t graph, unsigned long long flags __dv(0)); #endif /** * \brief Creates an executable graph from a graph * * Instantiates \p graph as an executable graph according to the \p instantiateParams structure. * The graph is validated for any structural constraints or intra-node constraints * which were not previously validated. If instantiation is successful, a handle to * the instantiated graph is returned in \p pGraphExec. * * \p instantiateParams controls the behavior of instantiation and subsequent * graph launches, as well as returning more detailed information in the event of an error. * ::cudaGraphInstantiateParams is defined as: * * \code typedef struct { unsigned long long flags; cudaStream_t uploadStream; cudaGraphNode_t errNode_out; cudaGraphInstantiateResult result_out; } cudaGraphInstantiateParams; * \endcode * * The \p flags field controls the behavior of instantiation and subsequent * graph launches. Valid flags are: * * - ::cudaGraphInstantiateFlagAutoFreeOnLaunch, which configures a * graph containing memory allocation nodes to automatically free any * unfreed memory allocations before the graph is relaunched. * * - ::cudaGraphInstantiateFlagUpload, which will perform an upload of the graph * into \p uploadStream once the graph has been instantiated. * * - ::cudaGraphInstantiateFlagDeviceLaunch, which configures the graph for launch * from the device. If this flag is passed, the executable graph handle returned can be * used to launch the graph from both the host and device. This flag can only be used * on platforms which support unified addressing. This flag cannot be used in * conjunction with ::cudaGraphInstantiateFlagAutoFreeOnLaunch. * * - ::cudaGraphInstantiateFlagUseNodePriority, which causes the graph * to use the priorities from the per-node attributes rather than the priority * of the launch stream during execution. Note that priorities are only available * on kernel nodes, and are copied from stream priority during stream capture. * * If \p graph contains any allocation or free nodes, there can be at most one * executable graph in existence for that graph at a time. An attempt to instantiate a * second executable graph before destroying the first with ::cudaGraphExecDestroy will * result in an error. * The same also applies if \p graph contains any device-updatable kernel nodes. * * If \p graph contains kernels which call device-side cudaGraphLaunch() from multiple * devices, this will result in an error. * * Graphs instantiated for launch on the device have additional restrictions which do not * apply to host graphs: * * - The graph's nodes must reside on a single device. * - The graph can only contain kernel nodes, memcpy nodes, memset nodes, and child graph nodes. * - The graph cannot be empty and must contain at least one kernel, memcpy, or memset node. * Operation-specific restrictions are outlined below. * - Kernel nodes: * - Use of CUDA Dynamic Parallelism is not permitted. * - Cooperative launches are permitted as long as MPS is not in use. * - Memcpy nodes: * - Only copies involving device memory and/or pinned device-mapped host memory are permitted. * - Copies involving CUDA arrays are not permitted. * - Both operands must be accessible from the current device, and the current device must * match the device of other nodes in the graph. * * In the event of an error, the \p result_out and \p errNode_out fields will contain more * information about the nature of the error. Possible error reporting includes: * * - ::cudaGraphInstantiateError, if passed an invalid value or if an unexpected error occurred * which is described by the return value of the function. \p errNode_out will be set to NULL. * - ::cudaGraphInstantiateInvalidStructure, if the graph structure is invalid. \p errNode_out * will be set to one of the offending nodes. * - ::cudaGraphInstantiateNodeOperationNotSupported, if the graph is instantiated for device * launch but contains a node of an unsupported node type, or a node which performs unsupported * operations, such as use of CUDA dynamic parallelism within a kernel node. \p errNode_out will * be set to this node. * - ::cudaGraphInstantiateMultipleDevicesNotSupported, if the graph is instantiated for device * launch but a node’s device differs from that of another node. This error can also be returned * if a graph is not instantiated for device launch and it contains kernels which call device-side * cudaGraphLaunch() from multiple devices. \p errNode_out will be set to this node. * * If instantiation is successful, \p result_out will be set to ::cudaGraphInstantiateSuccess, * and \p hErrNode_out will be set to NULL. * * \param pGraphExec - Returns instantiated graph * \param graph - Graph to instantiate * \param instantiateParams - Instantiation parameters * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphCreate, * ::cudaGraphInstantiate, * ::cudaGraphInstantiateWithFlags, * ::cudaGraphExecDestroy */ extern __host__ cudaError_t CUDARTAPI cudaGraphInstantiateWithParams(cudaGraphExec_t *pGraphExec, cudaGraph_t graph, cudaGraphInstantiateParams *instantiateParams); /** * \brief Query the instantiation flags of an executable graph * * Returns the flags that were passed to instantiation for the given executable graph. * ::cudaGraphInstantiateFlagUpload will not be returned by this API as it does * not affect the resulting executable graph. * * \param graphExec - The executable graph to query * \param flags - Returns the instantiation flags * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphInstantiate, * ::cudaGraphInstantiateWithFlags, * ::cudaGraphInstantiateWithParams */ extern __host__ cudaError_t CUDARTAPI cudaGraphExecGetFlags(cudaGraphExec_t graphExec, unsigned long long *flags); /** * \brief Sets the parameters for a kernel node in the given graphExec * * Sets the parameters of a kernel node in an executable graph \p hGraphExec. * The node is identified by the corresponding node \p node in the * non-executable graph, from which the executable graph was instantiated. * * \p node must not have been removed from the original graph. All \p nodeParams * fields may change, but the following restrictions apply to \p func updates: * * - The owning device of the function cannot change. * - A node whose function originally did not use CUDA dynamic parallelism cannot be updated * to a function which uses CDP * - A node whose function originally did not make device-side update calls cannot be updated * to a function which makes device-side update calls. * - If \p hGraphExec was not instantiated for device launch, a node whose function originally * did not use device-side cudaGraphLaunch() cannot be updated to a function which uses * device-side cudaGraphLaunch() unless the node resides on the same device as nodes which * contained such calls at instantiate-time. If no such calls were present at instantiation, * these updates cannot be performed at all. * * The modifications only affect future launches of \p hGraphExec. Already * enqueued or running launches of \p hGraphExec are not affected by this call. * \p node is also not modified by this call. * * If \p node is a device-updatable kernel node, the next upload/launch of \p hGraphExec * will overwrite any previous device-side updates. Additionally, applying host updates to a * device-updatable kernel node while it is being updated from the device will result in * undefined behavior. * * \param hGraphExec - The executable graph in which to set the specified node * \param node - kernel node from the graph from which graphExec was instantiated * \param pNodeParams - Updated Parameters to set * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * \note_cudaKernel_t * * \sa * ::cudaGraphExecNodeSetParams, * ::cudaGraphAddKernelNode, * ::cudaGraphKernelNodeSetParams, * ::cudaGraphExecMemcpyNodeSetParams, * ::cudaGraphExecMemsetNodeSetParams, * ::cudaGraphExecHostNodeSetParams, * ::cudaGraphExecChildGraphNodeSetParams, * ::cudaGraphExecEventRecordNodeSetEvent, * ::cudaGraphExecEventWaitNodeSetEvent, * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams, * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams, * ::cudaGraphExecUpdate, * ::cudaGraphInstantiate */ extern __host__ cudaError_t CUDARTAPI cudaGraphExecKernelNodeSetParams(cudaGraphExec_t hGraphExec, cudaGraphNode_t node, const struct cudaKernelNodeParams *pNodeParams); /** * \brief Sets the parameters for a memcpy node in the given graphExec. * * Updates the work represented by \p node in \p hGraphExec as though \p node had * contained \p pNodeParams at instantiation. \p node must remain in the graph which was * used to instantiate \p hGraphExec. Changed edges to and from \p node are ignored. * * The source and destination memory in \p pNodeParams must be allocated from the same * contexts as the original source and destination memory. Both the instantiation-time * memory operands and the memory operands in \p pNodeParams must be 1-dimensional. * Zero-length operations are not supported. * * The modifications only affect future launches of \p hGraphExec. Already enqueued * or running launches of \p hGraphExec are not affected by this call. \p node is also * not modified by this call. * * Returns ::cudaErrorInvalidValue if the memory operands' mappings changed or * either the original or new memory operands are multidimensional. * * \param hGraphExec - The executable graph in which to set the specified node * \param node - Memcpy node from the graph which was used to instantiate graphExec * \param pNodeParams - Updated Parameters to set * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphExecNodeSetParams, * ::cudaGraphAddMemcpyNode, * ::cudaGraphMemcpyNodeSetParams, * ::cudaGraphExecMemcpyNodeSetParamsToSymbol, * ::cudaGraphExecMemcpyNodeSetParamsFromSymbol, * ::cudaGraphExecMemcpyNodeSetParams1D, * ::cudaGraphExecKernelNodeSetParams, * ::cudaGraphExecMemsetNodeSetParams, * ::cudaGraphExecHostNodeSetParams, * ::cudaGraphExecChildGraphNodeSetParams, * ::cudaGraphExecEventRecordNodeSetEvent, * ::cudaGraphExecEventWaitNodeSetEvent, * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams, * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams, * ::cudaGraphExecUpdate, * ::cudaGraphInstantiate */ extern __host__ cudaError_t CUDARTAPI cudaGraphExecMemcpyNodeSetParams(cudaGraphExec_t hGraphExec, cudaGraphNode_t node, const struct cudaMemcpy3DParms *pNodeParams); /** * \brief Sets the parameters for a memcpy node in the given graphExec to copy to a symbol on the device * * Updates the work represented by \p node in \p hGraphExec as though \p node had * contained the given params at instantiation. \p node must remain in the graph which was * used to instantiate \p hGraphExec. Changed edges to and from \p node are ignored. * * \p src and \p symbol must be allocated from the same contexts as the original source and * destination memory. The instantiation-time memory operands must be 1-dimensional. * Zero-length operations are not supported. * * The modifications only affect future launches of \p hGraphExec. Already enqueued * or running launches of \p hGraphExec are not affected by this call. \p node is also * not modified by this call. * * Returns ::cudaErrorInvalidValue if the memory operands' mappings changed or * the original memory operands are multidimensional. * * \param hGraphExec - The executable graph in which to set the specified node * \param node - Memcpy node from the graph which was used to instantiate graphExec * \param symbol - Device symbol address * \param src - Source memory address * \param count - Size in bytes to copy * \param offset - Offset from start of symbol in bytes * \param kind - Type of transfer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddMemcpyNode, * ::cudaGraphAddMemcpyNodeToSymbol, * ::cudaGraphMemcpyNodeSetParams, * ::cudaGraphMemcpyNodeSetParamsToSymbol, * ::cudaGraphExecMemcpyNodeSetParams, * ::cudaGraphExecMemcpyNodeSetParamsFromSymbol, * ::cudaGraphExecKernelNodeSetParams, * ::cudaGraphExecMemsetNodeSetParams, * ::cudaGraphExecHostNodeSetParams, * ::cudaGraphExecChildGraphNodeSetParams, * ::cudaGraphExecEventRecordNodeSetEvent, * ::cudaGraphExecEventWaitNodeSetEvent, * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams, * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams, * ::cudaGraphExecUpdate, * ::cudaGraphInstantiate */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaGraphExecMemcpyNodeSetParamsToSymbol( cudaGraphExec_t hGraphExec, cudaGraphNode_t node, const void* symbol, const void* src, size_t count, size_t offset, enum cudaMemcpyKind kind); #endif /** * \brief Sets the parameters for a memcpy node in the given graphExec to copy from a symbol on the device * * Updates the work represented by \p node in \p hGraphExec as though \p node had * contained the given params at instantiation. \p node must remain in the graph which was * used to instantiate \p hGraphExec. Changed edges to and from \p node are ignored. * * \p symbol and \p dst must be allocated from the same contexts as the original source and * destination memory. The instantiation-time memory operands must be 1-dimensional. * Zero-length operations are not supported. * * The modifications only affect future launches of \p hGraphExec. Already enqueued * or running launches of \p hGraphExec are not affected by this call. \p node is also * not modified by this call. * * Returns ::cudaErrorInvalidValue if the memory operands' mappings changed or * the original memory operands are multidimensional. * * \param hGraphExec - The executable graph in which to set the specified node * \param node - Memcpy node from the graph which was used to instantiate graphExec * \param dst - Destination memory address * \param symbol - Device symbol address * \param count - Size in bytes to copy * \param offset - Offset from start of symbol in bytes * \param kind - Type of transfer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddMemcpyNode, * ::cudaGraphAddMemcpyNodeFromSymbol, * ::cudaGraphMemcpyNodeSetParams, * ::cudaGraphMemcpyNodeSetParamsFromSymbol, * ::cudaGraphExecMemcpyNodeSetParams, * ::cudaGraphExecMemcpyNodeSetParamsToSymbol, * ::cudaGraphExecKernelNodeSetParams, * ::cudaGraphExecMemsetNodeSetParams, * ::cudaGraphExecHostNodeSetParams, * ::cudaGraphExecChildGraphNodeSetParams, * ::cudaGraphExecEventRecordNodeSetEvent, * ::cudaGraphExecEventWaitNodeSetEvent, * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams, * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams, * ::cudaGraphExecUpdate, * ::cudaGraphInstantiate */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaGraphExecMemcpyNodeSetParamsFromSymbol( cudaGraphExec_t hGraphExec, cudaGraphNode_t node, void* dst, const void* symbol, size_t count, size_t offset, enum cudaMemcpyKind kind); #endif /** * \brief Sets the parameters for a memcpy node in the given graphExec to perform a 1-dimensional copy * * Updates the work represented by \p node in \p hGraphExec as though \p node had * contained the given params at instantiation. \p node must remain in the graph which was * used to instantiate \p hGraphExec. Changed edges to and from \p node are ignored. * * \p src and \p dst must be allocated from the same contexts as the original source * and destination memory. The instantiation-time memory operands must be 1-dimensional. * Zero-length operations are not supported. * * The modifications only affect future launches of \p hGraphExec. Already enqueued * or running launches of \p hGraphExec are not affected by this call. \p node is also * not modified by this call. * * Returns ::cudaErrorInvalidValue if the memory operands' mappings changed or * the original memory operands are multidimensional. * * \param hGraphExec - The executable graph in which to set the specified node * \param node - Memcpy node from the graph which was used to instantiate graphExec * \param dst - Destination memory address * \param src - Source memory address * \param count - Size in bytes to copy * \param kind - Type of transfer * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddMemcpyNode, * ::cudaGraphAddMemcpyNode1D, * ::cudaGraphMemcpyNodeSetParams, * ::cudaGraphMemcpyNodeSetParams1D, * ::cudaGraphExecMemcpyNodeSetParams, * ::cudaGraphExecKernelNodeSetParams, * ::cudaGraphExecMemsetNodeSetParams, * ::cudaGraphExecHostNodeSetParams, * ::cudaGraphExecChildGraphNodeSetParams, * ::cudaGraphExecEventRecordNodeSetEvent, * ::cudaGraphExecEventWaitNodeSetEvent, * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams, * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams, * ::cudaGraphExecUpdate, * ::cudaGraphInstantiate */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaGraphExecMemcpyNodeSetParams1D( cudaGraphExec_t hGraphExec, cudaGraphNode_t node, void* dst, const void* src, size_t count, enum cudaMemcpyKind kind); #endif /** * \brief Sets the parameters for a memset node in the given graphExec. * * Updates the work represented by \p node in \p hGraphExec as though \p node had * contained \p pNodeParams at instantiation. \p node must remain in the graph which was * used to instantiate \p hGraphExec. Changed edges to and from \p node are ignored. * * Zero sized operations are not supported. * * The new destination pointer in \p pNodeParams must be to the same kind of allocation * as the original destination pointer and have the same context association and device mapping * as the original destination pointer. * * Both the value and pointer address may be updated. * Changing other aspects of the memset (width, height, element size or pitch) may cause the update to be rejected. * Specifically, for 2d memsets, all dimension changes are rejected. * For 1d memsets, changes in height are explicitly rejected and other changes are oportunistically allowed * if the resulting work maps onto the work resources already allocated for the node. * The modifications only affect future launches of \p hGraphExec. Already enqueued * or running launches of \p hGraphExec are not affected by this call. \p node is also * not modified by this call. * * \param hGraphExec - The executable graph in which to set the specified node * \param node - Memset node from the graph which was used to instantiate graphExec * \param pNodeParams - Updated Parameters to set * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphExecNodeSetParams, * ::cudaGraphAddMemsetNode, * ::cudaGraphMemsetNodeSetParams, * ::cudaGraphExecKernelNodeSetParams, * ::cudaGraphExecMemcpyNodeSetParams, * ::cudaGraphExecHostNodeSetParams, * ::cudaGraphExecChildGraphNodeSetParams, * ::cudaGraphExecEventRecordNodeSetEvent, * ::cudaGraphExecEventWaitNodeSetEvent, * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams, * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams, * ::cudaGraphExecUpdate, * ::cudaGraphInstantiate */ extern __host__ cudaError_t CUDARTAPI cudaGraphExecMemsetNodeSetParams(cudaGraphExec_t hGraphExec, cudaGraphNode_t node, const struct cudaMemsetParams *pNodeParams); /** * \brief Sets the parameters for a host node in the given graphExec. * * Updates the work represented by \p node in \p hGraphExec as though \p node had * contained \p pNodeParams at instantiation. \p node must remain in the graph which was * used to instantiate \p hGraphExec. Changed edges to and from \p node are ignored. * * The modifications only affect future launches of \p hGraphExec. Already enqueued * or running launches of \p hGraphExec are not affected by this call. \p node is also * not modified by this call. * * \param hGraphExec - The executable graph in which to set the specified node * \param node - Host node from the graph which was used to instantiate graphExec * \param pNodeParams - Updated Parameters to set * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphExecNodeSetParams, * ::cudaGraphAddHostNode, * ::cudaGraphHostNodeSetParams, * ::cudaGraphExecKernelNodeSetParams, * ::cudaGraphExecMemcpyNodeSetParams, * ::cudaGraphExecMemsetNodeSetParams, * ::cudaGraphExecChildGraphNodeSetParams, * ::cudaGraphExecEventRecordNodeSetEvent, * ::cudaGraphExecEventWaitNodeSetEvent, * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams, * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams, * ::cudaGraphExecUpdate, * ::cudaGraphInstantiate */ extern __host__ cudaError_t CUDARTAPI cudaGraphExecHostNodeSetParams(cudaGraphExec_t hGraphExec, cudaGraphNode_t node, const struct cudaHostNodeParams *pNodeParams); /** * \brief Updates node parameters in the child graph node in the given graphExec. * * Updates the work represented by \p node in \p hGraphExec as though the nodes contained * in \p node's graph had the parameters contained in \p childGraph's nodes at instantiation. * \p node must remain in the graph which was used to instantiate \p hGraphExec. * Changed edges to and from \p node are ignored. * * The modifications only affect future launches of \p hGraphExec. Already enqueued * or running launches of \p hGraphExec are not affected by this call. \p node is also * not modified by this call. * * The topology of \p childGraph, as well as the node insertion order, must match that * of the graph contained in \p node. See ::cudaGraphExecUpdate() for a list of restrictions * on what can be updated in an instantiated graph. The update is recursive, so child graph * nodes contained within the top level child graph will also be updated. * \param hGraphExec - The executable graph in which to set the specified node * \param node - Host node from the graph which was used to instantiate graphExec * \param childGraph - The graph supplying the updated parameters * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphExecNodeSetParams, * ::cudaGraphAddChildGraphNode, * ::cudaGraphChildGraphNodeGetGraph, * ::cudaGraphExecKernelNodeSetParams, * ::cudaGraphExecMemcpyNodeSetParams, * ::cudaGraphExecMemsetNodeSetParams, * ::cudaGraphExecHostNodeSetParams, * ::cudaGraphExecEventRecordNodeSetEvent, * ::cudaGraphExecEventWaitNodeSetEvent, * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams, * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams, * ::cudaGraphExecUpdate, * ::cudaGraphInstantiate */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaGraphExecChildGraphNodeSetParams(cudaGraphExec_t hGraphExec, cudaGraphNode_t node, cudaGraph_t childGraph); #endif /** * \brief Sets the event for an event record node in the given graphExec * * Sets the event of an event record node in an executable graph \p hGraphExec. * The node is identified by the corresponding node \p hNode in the * non-executable graph, from which the executable graph was instantiated. * * The modifications only affect future launches of \p hGraphExec. Already * enqueued or running launches of \p hGraphExec are not affected by this call. * \p hNode is also not modified by this call. * * \param hGraphExec - The executable graph in which to set the specified node * \param hNode - Event record node from the graph from which graphExec was instantiated * \param event - Updated event to use * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphExecNodeSetParams, * ::cudaGraphAddEventRecordNode, * ::cudaGraphEventRecordNodeGetEvent, * ::cudaGraphEventWaitNodeSetEvent, * ::cudaEventRecordWithFlags, * ::cudaStreamWaitEvent, * ::cudaGraphExecKernelNodeSetParams, * ::cudaGraphExecMemcpyNodeSetParams, * ::cudaGraphExecMemsetNodeSetParams, * ::cudaGraphExecHostNodeSetParams, * ::cudaGraphExecChildGraphNodeSetParams, * ::cudaGraphExecEventWaitNodeSetEvent, * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams, * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams, * ::cudaGraphExecUpdate, * ::cudaGraphInstantiate */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaGraphExecEventRecordNodeSetEvent(cudaGraphExec_t hGraphExec, cudaGraphNode_t hNode, cudaEvent_t event); #endif /** * \brief Sets the event for an event wait node in the given graphExec * * Sets the event of an event wait node in an executable graph \p hGraphExec. * The node is identified by the corresponding node \p hNode in the * non-executable graph, from which the executable graph was instantiated. * * The modifications only affect future launches of \p hGraphExec. Already * enqueued or running launches of \p hGraphExec are not affected by this call. * \p hNode is also not modified by this call. * * \param hGraphExec - The executable graph in which to set the specified node * \param hNode - Event wait node from the graph from which graphExec was instantiated * \param event - Updated event to use * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphExecNodeSetParams, * ::cudaGraphAddEventWaitNode, * ::cudaGraphEventWaitNodeGetEvent, * ::cudaGraphEventRecordNodeSetEvent, * ::cudaEventRecordWithFlags, * ::cudaStreamWaitEvent, * ::cudaGraphExecKernelNodeSetParams, * ::cudaGraphExecMemcpyNodeSetParams, * ::cudaGraphExecMemsetNodeSetParams, * ::cudaGraphExecHostNodeSetParams, * ::cudaGraphExecChildGraphNodeSetParams, * ::cudaGraphExecEventRecordNodeSetEvent, * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams, * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams, * ::cudaGraphExecUpdate, * ::cudaGraphInstantiate */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaGraphExecEventWaitNodeSetEvent(cudaGraphExec_t hGraphExec, cudaGraphNode_t hNode, cudaEvent_t event); #endif /** * \brief Sets the parameters for an external semaphore signal node in the given graphExec * * Sets the parameters of an external semaphore signal node in an executable graph \p hGraphExec. * The node is identified by the corresponding node \p hNode in the * non-executable graph, from which the executable graph was instantiated. * * \p hNode must not have been removed from the original graph. * * The modifications only affect future launches of \p hGraphExec. Already * enqueued or running launches of \p hGraphExec are not affected by this call. * \p hNode is also not modified by this call. * * Changing \p nodeParams->numExtSems is not supported. * * \param hGraphExec - The executable graph in which to set the specified node * \param hNode - semaphore signal node from the graph from which graphExec was instantiated * \param nodeParams - Updated Parameters to set * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphExecNodeSetParams, * ::cudaGraphAddExternalSemaphoresSignalNode, * ::cudaImportExternalSemaphore, * ::cudaSignalExternalSemaphoresAsync, * ::cudaWaitExternalSemaphoresAsync, * ::cudaGraphExecKernelNodeSetParams, * ::cudaGraphExecMemcpyNodeSetParams, * ::cudaGraphExecMemsetNodeSetParams, * ::cudaGraphExecHostNodeSetParams, * ::cudaGraphExecChildGraphNodeSetParams, * ::cudaGraphExecEventRecordNodeSetEvent, * ::cudaGraphExecEventWaitNodeSetEvent, * ::cudaGraphExecExternalSemaphoresWaitNodeSetParams, * ::cudaGraphExecUpdate, * ::cudaGraphInstantiate */ #if __CUDART_API_VERSION >= 11020 extern __host__ cudaError_t CUDARTAPI cudaGraphExecExternalSemaphoresSignalNodeSetParams(cudaGraphExec_t hGraphExec, cudaGraphNode_t hNode, const struct cudaExternalSemaphoreSignalNodeParams *nodeParams); #endif /** * \brief Sets the parameters for an external semaphore wait node in the given graphExec * * Sets the parameters of an external semaphore wait node in an executable graph \p hGraphExec. * The node is identified by the corresponding node \p hNode in the * non-executable graph, from which the executable graph was instantiated. * * \p hNode must not have been removed from the original graph. * * The modifications only affect future launches of \p hGraphExec. Already * enqueued or running launches of \p hGraphExec are not affected by this call. * \p hNode is also not modified by this call. * * Changing \p nodeParams->numExtSems is not supported. * * \param hGraphExec - The executable graph in which to set the specified node * \param hNode - semaphore wait node from the graph from which graphExec was instantiated * \param nodeParams - Updated Parameters to set * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphExecNodeSetParams, * ::cudaGraphAddExternalSemaphoresWaitNode, * ::cudaImportExternalSemaphore, * ::cudaSignalExternalSemaphoresAsync, * ::cudaWaitExternalSemaphoresAsync, * ::cudaGraphExecKernelNodeSetParams, * ::cudaGraphExecMemcpyNodeSetParams, * ::cudaGraphExecMemsetNodeSetParams, * ::cudaGraphExecHostNodeSetParams, * ::cudaGraphExecChildGraphNodeSetParams, * ::cudaGraphExecEventRecordNodeSetEvent, * ::cudaGraphExecEventWaitNodeSetEvent, * ::cudaGraphExecExternalSemaphoresSignalNodeSetParams, * ::cudaGraphExecUpdate, * ::cudaGraphInstantiate */ #if __CUDART_API_VERSION >= 11020 extern __host__ cudaError_t CUDARTAPI cudaGraphExecExternalSemaphoresWaitNodeSetParams(cudaGraphExec_t hGraphExec, cudaGraphNode_t hNode, const struct cudaExternalSemaphoreWaitNodeParams *nodeParams); #endif /** * \brief Enables or disables the specified node in the given graphExec * * Sets \p hNode to be either enabled or disabled. Disabled nodes are functionally equivalent * to empty nodes until they are reenabled. Existing node parameters are not affected by * disabling/enabling the node. * * The node is identified by the corresponding node \p hNode in the non-executable * graph, from which the executable graph was instantiated. * * \p hNode must not have been removed from the original graph. * * The modifications only affect future launches of \p hGraphExec. Already * enqueued or running launches of \p hGraphExec are not affected by this call. * \p hNode is also not modified by this call. * * \note Currently only kernel, memset and memcpy nodes are supported. * * \param hGraphExec - The executable graph in which to set the specified node * \param hNode - Node from the graph from which graphExec was instantiated * \param isEnabled - Node is enabled if != 0, otherwise the node is disabled * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphNodeGetEnabled, * ::cudaGraphExecUpdate, * ::cudaGraphInstantiate * ::cudaGraphLaunch */ #if __CUDART_API_VERSION >= 11060 extern __host__ cudaError_t CUDARTAPI cudaGraphNodeSetEnabled(cudaGraphExec_t hGraphExec, cudaGraphNode_t hNode, unsigned int isEnabled); #endif /** * \brief Query whether a node in the given graphExec is enabled * * Sets isEnabled to 1 if \p hNode is enabled, or 0 if \p hNode is disabled. * * The node is identified by the corresponding node \p hNode in the non-executable * graph, from which the executable graph was instantiated. * * \p hNode must not have been removed from the original graph. * * \note Currently only kernel, memset and memcpy nodes are supported. * * \param hGraphExec - The executable graph in which to set the specified node * \param hNode - Node from the graph from which graphExec was instantiated * \param isEnabled - Location to return the enabled status of the node * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphNodeSetEnabled, * ::cudaGraphExecUpdate, * ::cudaGraphInstantiate * ::cudaGraphLaunch */ #if __CUDART_API_VERSION >= 11060 extern __host__ cudaError_t CUDARTAPI cudaGraphNodeGetEnabled(cudaGraphExec_t hGraphExec, cudaGraphNode_t hNode, unsigned int *isEnabled); #endif /** * \brief Check whether an executable graph can be updated with a graph and perform the update if possible * * Updates the node parameters in the instantiated graph specified by \p hGraphExec with the * node parameters in a topologically identical graph specified by \p hGraph. * * Limitations: * * - Kernel nodes: * - The owning context of the function cannot change. * - A node whose function originally did not use CUDA dynamic parallelism cannot be updated * to a function which uses CDP. * - A node whose function originally did not make device-side update calls cannot be updated * to a function which makes device-side update calls. * - A cooperative node cannot be updated to a non-cooperative node, and vice-versa. * - If the graph was instantiated with cudaGraphInstantiateFlagUseNodePriority, the * priority attribute cannot change. Equality is checked on the originally requested * priority values, before they are clamped to the device's supported range. * - If \p hGraphExec was not instantiated for device launch, a node whose function originally * did not use device-side cudaGraphLaunch() cannot be updated to a function which uses * device-side cudaGraphLaunch() unless the node resides on the same device as nodes which * contained such calls at instantiate-time. If no such calls were present at instantiation, * these updates cannot be performed at all. * - Neither \p hGraph nor \p hGraphExec may contain device-updatable kernel nodes. * - Memset and memcpy nodes: * - The CUDA device(s) to which the operand(s) was allocated/mapped cannot change. * - The source/destination memory must be allocated from the same contexts as the original * source/destination memory. * - For 2d memsets, only address and assinged value may be updated. * - For 1d memsets, updating dimensions is also allowed, but may fail if the resulting operation doesn't * map onto the work resources already allocated for the node. * - Additional memcpy node restrictions: * - Changing either the source or destination memory type(i.e. CU_MEMORYTYPE_DEVICE, * CU_MEMORYTYPE_ARRAY, etc.) is not supported. * - Conditional nodes: * - Changing node parameters is not supported. * - Changeing parameters of nodes within the conditional body graph is subject to the rules above. * - Conditional handle flags and default values are updated as part of the graph update. * * Note: The API may add further restrictions in future releases. The return code should always be checked. * * cudaGraphExecUpdate sets the result member of \p resultInfo to cudaGraphExecUpdateErrorTopologyChanged * under the following conditions: * - The count of nodes directly in \p hGraphExec and \p hGraph differ, in which case resultInfo->errorNode * is set to NULL. * - \p hGraph has more exit nodes than \p hGraph, in which case resultInfo->errorNode is set to one of * the exit nodes in hGraph. * - A node in \p hGraph has a different number of dependencies than the node from \p hGraphExec it is paired with, * in which case resultInfo->errorNode is set to the node from \p hGraph. * - A node in \p hGraph has a dependency that does not match with the corresponding dependency of the paired node * from \p hGraphExec. resultInfo->errorNode will be set to the node from \p hGraph. resultInfo->errorFromNode * will be set to the mismatched dependency. The dependencies are paired based on edge order and a dependency * does not match when the nodes are already paired based on other edges examined in the graph. * * cudaGraphExecUpdate sets \p the result member of \p resultInfo to: * - cudaGraphExecUpdateError if passed an invalid value. * - cudaGraphExecUpdateErrorTopologyChanged if the graph topology changed * - cudaGraphExecUpdateErrorNodeTypeChanged if the type of a node changed, in which case * \p hErrorNode_out is set to the node from \p hGraph. * - cudaGraphExecUpdateErrorFunctionChanged if the function of a kernel node changed (CUDA driver < 11.2) * - cudaGraphExecUpdateErrorUnsupportedFunctionChange if the func field of a kernel changed in an * unsupported way(see note above), in which case \p hErrorNode_out is set to the node from \p hGraph * - cudaGraphExecUpdateErrorParametersChanged if any parameters to a node changed in a way * that is not supported, in which case \p hErrorNode_out is set to the node from \p hGraph * - cudaGraphExecUpdateErrorAttributesChanged if any attributes of a node changed in a way * that is not supported, in which case \p hErrorNode_out is set to the node from \p hGraph * - cudaGraphExecUpdateErrorNotSupported if something about a node is unsupported, like * the node's type or configuration, in which case \p hErrorNode_out is set to the node from \p hGraph * * If the update fails for a reason not listed above, the result member of \p resultInfo will be set * to cudaGraphExecUpdateError. If the update succeeds, the result member will be set to cudaGraphExecUpdateSuccess. * * cudaGraphExecUpdate returns cudaSuccess when the updated was performed successfully. It returns * cudaErrorGraphExecUpdateFailure if the graph update was not performed because it included * changes which violated constraints specific to instantiated graph update. * * \param hGraphExec The instantiated graph to be updated * \param hGraph The graph containing the updated parameters \param resultInfo the error info structure * * \return * ::cudaSuccess, * ::cudaErrorGraphExecUpdateFailure, * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphInstantiate */ extern __host__ cudaError_t CUDARTAPI cudaGraphExecUpdate(cudaGraphExec_t hGraphExec, cudaGraph_t hGraph, cudaGraphExecUpdateResultInfo *resultInfo); /** * \brief Uploads an executable graph in a stream * * Uploads \p hGraphExec to the device in \p hStream without executing it. Uploads of * the same \p hGraphExec will be serialized. Each upload is ordered behind both any * previous work in \p hStream and any previous launches of \p hGraphExec. * Uses memory cached by \p stream to back the allocations owned by \p graphExec. * * \param hGraphExec - Executable graph to upload * \param hStream - Stream in which to upload the graph * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * \notefnerr * \note_init_rt * * \sa * ::cudaGraphInstantiate, * ::cudaGraphLaunch, * ::cudaGraphExecDestroy */ #if __CUDART_API_VERSION >= 11010 extern __host__ cudaError_t CUDARTAPI cudaGraphUpload(cudaGraphExec_t graphExec, cudaStream_t stream); #endif /** * \brief Launches an executable graph in a stream * * Executes \p graphExec in \p stream. Only one instance of \p graphExec may be executing * at a time. Each launch is ordered behind both any previous work in \p stream * and any previous launches of \p graphExec. To execute a graph concurrently, it must be * instantiated multiple times into multiple executable graphs. * * If any allocations created by \p graphExec remain unfreed (from a previous launch) and * \p graphExec was not instantiated with ::cudaGraphInstantiateFlagAutoFreeOnLaunch, * the launch will fail with ::cudaErrorInvalidValue. * * \param graphExec - Executable graph to launch * \param stream - Stream in which to launch the graph * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphInstantiate, * ::cudaGraphUpload, * ::cudaGraphExecDestroy */ extern __host__ cudaError_t CUDARTAPI cudaGraphLaunch(cudaGraphExec_t graphExec, cudaStream_t stream); /** * \brief Destroys an executable graph * * Destroys the executable graph specified by \p graphExec. * * \param graphExec - Executable graph to destroy * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * \note_destroy_ub * * \sa * ::cudaGraphInstantiate, * ::cudaGraphUpload, * ::cudaGraphLaunch */ extern __host__ cudaError_t CUDARTAPI cudaGraphExecDestroy(cudaGraphExec_t graphExec); /** * \brief Destroys a graph * * Destroys the graph specified by \p graph, as well as all of its nodes. * * \param graph - Graph to destroy * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * \note_destroy_ub * * \sa * ::cudaGraphCreate */ extern __host__ cudaError_t CUDARTAPI cudaGraphDestroy(cudaGraph_t graph); /** * \brief Write a DOT file describing graph structure * * Using the provided \p graph, write to \p path a DOT formatted description of the graph. * By default this includes the graph topology, node types, node id, kernel names and memcpy direction. * \p flags can be specified to write more detailed information about each node type such as * parameter values, kernel attributes, node and function handles. * * \param graph - The graph to create a DOT file from * \param path - The path to write the DOT file to * \param flags - Flags from cudaGraphDebugDotFlags for specifying which additional node information to write * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorOperatingSystem */ extern __host__ cudaError_t CUDARTAPI cudaGraphDebugDotPrint(cudaGraph_t graph, const char *path, unsigned int flags); /** * \brief Create a user object * * Create a user object with the specified destructor callback and initial reference count. The * initial references are owned by the caller. * * Destructor callbacks cannot make CUDA API calls and should avoid blocking behavior, as they * are executed by a shared internal thread. Another thread may be signaled to perform such * actions, if it does not block forward progress of tasks scheduled through CUDA. * * See CUDA User Objects in the CUDA C++ Programming Guide for more information on user objects. * * \param object_out - Location to return the user object handle * \param ptr - The pointer to pass to the destroy function * \param destroy - Callback to free the user object when it is no longer in use * \param initialRefcount - The initial refcount to create the object with, typically 1. The * initial references are owned by the calling thread. * \param flags - Currently it is required to pass ::cudaUserObjectNoDestructorSync, * which is the only defined flag. This indicates that the destroy * callback cannot be waited on by any CUDA API. Users requiring * synchronization of the callback should signal its completion * manually. * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * * \sa * ::cudaUserObjectRetain, * ::cudaUserObjectRelease, * ::cudaGraphRetainUserObject, * ::cudaGraphReleaseUserObject, * ::cudaGraphCreate */ extern __host__ cudaError_t CUDARTAPI cudaUserObjectCreate(cudaUserObject_t *object_out, void *ptr, cudaHostFn_t destroy, unsigned int initialRefcount, unsigned int flags); /** * \brief Retain a reference to a user object * * Retains new references to a user object. The new references are owned by the caller. * * See CUDA User Objects in the CUDA C++ Programming Guide for more information on user objects. * * \param object - The object to retain * \param count - The number of references to retain, typically 1. Must be nonzero * and not larger than INT_MAX. * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * * \sa * ::cudaUserObjectCreate, * ::cudaUserObjectRelease, * ::cudaGraphRetainUserObject, * ::cudaGraphReleaseUserObject, * ::cudaGraphCreate */ extern __host__ cudaError_t CUDARTAPI cudaUserObjectRetain(cudaUserObject_t object, unsigned int count __dv(1)); /** * \brief Release a reference to a user object * * Releases user object references owned by the caller. The object's destructor is invoked if * the reference count reaches zero. * * It is undefined behavior to release references not owned by the caller, or to use a user * object handle after all references are released. * * See CUDA User Objects in the CUDA C++ Programming Guide for more information on user objects. * * \param object - The object to release * \param count - The number of references to release, typically 1. Must be nonzero * and not larger than INT_MAX. * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * * \sa * ::cudaUserObjectCreate, * ::cudaUserObjectRetain, * ::cudaGraphRetainUserObject, * ::cudaGraphReleaseUserObject, * ::cudaGraphCreate */ extern __host__ cudaError_t CUDARTAPI cudaUserObjectRelease(cudaUserObject_t object, unsigned int count __dv(1)); /** * \brief Retain a reference to a user object from a graph * * Creates or moves user object references that will be owned by a CUDA graph. * * See CUDA User Objects in the CUDA C++ Programming Guide for more information on user objects. * * \param graph - The graph to associate the reference with * \param object - The user object to retain a reference for * \param count - The number of references to add to the graph, typically 1. Must be * nonzero and not larger than INT_MAX. * \param flags - The optional flag ::cudaGraphUserObjectMove transfers references * from the calling thread, rather than create new references. Pass 0 * to create new references. * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * * \sa * ::cudaUserObjectCreate * ::cudaUserObjectRetain, * ::cudaUserObjectRelease, * ::cudaGraphReleaseUserObject, * ::cudaGraphCreate */ extern __host__ cudaError_t CUDARTAPI cudaGraphRetainUserObject(cudaGraph_t graph, cudaUserObject_t object, unsigned int count __dv(1), unsigned int flags __dv(0)); /** * \brief Release a user object reference from a graph * * Releases user object references owned by a graph. * * See CUDA User Objects in the CUDA C++ Programming Guide for more information on user objects. * * \param graph - The graph that will release the reference * \param object - The user object to release a reference for * \param count - The number of references to release, typically 1. Must be nonzero * and not larger than INT_MAX. * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue * * \sa * ::cudaUserObjectCreate * ::cudaUserObjectRetain, * ::cudaUserObjectRelease, * ::cudaGraphRetainUserObject, * ::cudaGraphCreate */ extern __host__ cudaError_t CUDARTAPI cudaGraphReleaseUserObject(cudaGraph_t graph, cudaUserObject_t object, unsigned int count __dv(1)); /** * \brief Adds a node of arbitrary type to a graph * * Creates a new node in \p graph described by \p nodeParams with \p numDependencies * dependencies specified via \p pDependencies. \p numDependencies may be 0. * \p pDependencies may be null if \p numDependencies is 0. \p pDependencies may not have * any duplicate entries. * * \p nodeParams is a tagged union. The node type should be specified in the \p type field, * and type-specific parameters in the corresponding union member. All unused bytes - that * is, \p reserved0 and all bytes past the utilized union member - must be set to zero. * It is recommended to use brace initialization or memset to ensure all bytes are * initialized. * * Note that for some node types, \p nodeParams may contain "out parameters" which are * modified during the call, such as \p nodeParams->alloc.dptr. * * A handle to the new node will be returned in \p phGraphNode. * * \param pGraphNode - Returns newly created node * \param graph - Graph to which to add the node * \param pDependencies - Dependencies of the node * \param numDependencies - Number of dependencies * \param nodeParams - Specification of the node * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidDeviceFunction, * ::cudaErrorNotSupported * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphCreate, * ::cudaGraphNodeSetParams, * ::cudaGraphExecNodeSetParams */ extern __host__ cudaError_t CUDARTAPI cudaGraphAddNode(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, size_t numDependencies, struct cudaGraphNodeParams *nodeParams); /** * \brief Adds a node of arbitrary type to a graph (12.3+) * * Creates a new node in \p graph described by \p nodeParams with \p numDependencies * dependencies specified via \p pDependencies. \p numDependencies may be 0. * \p pDependencies may be null if \p numDependencies is 0. \p pDependencies may not have * any duplicate entries. * * \p nodeParams is a tagged union. The node type should be specified in the \p type field, * and type-specific parameters in the corresponding union member. All unused bytes - that * is, \p reserved0 and all bytes past the utilized union member - must be set to zero. * It is recommended to use brace initialization or memset to ensure all bytes are * initialized. * * Note that for some node types, \p nodeParams may contain "out parameters" which are * modified during the call, such as \p nodeParams->alloc.dptr. * * A handle to the new node will be returned in \p phGraphNode. * * \param pGraphNode - Returns newly created node * \param graph - Graph to which to add the node * \param pDependencies - Dependencies of the node * \param dependencyData - Optional edge data for the dependencies. If NULL, the data is * assumed to be default (zeroed) for all dependencies. * \param numDependencies - Number of dependencies * \param nodeParams - Specification of the node * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidDeviceFunction, * ::cudaErrorNotSupported * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphCreate, * ::cudaGraphNodeSetParams, * ::cudaGraphExecNodeSetParams */ extern __host__ cudaError_t CUDARTAPI cudaGraphAddNode_v2(cudaGraphNode_t *pGraphNode, cudaGraph_t graph, const cudaGraphNode_t *pDependencies, const cudaGraphEdgeData *dependencyData, size_t numDependencies, struct cudaGraphNodeParams *nodeParams); /** * \brief Update's a graph node's parameters * * Sets the parameters of graph node \p node to \p nodeParams. The node type specified by * \p nodeParams->type must match the type of \p node. \p nodeParams must be fully * initialized and all unused bytes (reserved, padding) zeroed. * * Modifying parameters is not supported for node types cudaGraphNodeTypeMemAlloc and * cudaGraphNodeTypeMemFree. * * \param node - Node to set the parameters for * \param nodeParams - Parameters to copy * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidDeviceFunction, * ::cudaErrorNotSupported * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddNode, * ::cudaGraphExecNodeSetParams */ extern __host__ cudaError_t CUDARTAPI cudaGraphNodeSetParams(cudaGraphNode_t node, struct cudaGraphNodeParams *nodeParams); /** * \brief Update's a graph node's parameters in an instantiated graph * * Sets the parameters of a node in an executable graph \p graphExec. The node is identified * by the corresponding node \p node in the non-executable graph from which the executable * graph was instantiated. \p node must not have been removed from the original graph. * * The modifications only affect future launches of \p graphExec. Already * enqueued or running launches of \p graphExec are not affected by this call. * \p node is also not modified by this call. * * Allowed changes to parameters on executable graphs are as follows: * *
Node typeAllowed changes *
kernelSee ::cudaGraphExecKernelNodeSetParams *
memcpyAddresses for 1-dimensional copies if allocated in same context; see ::cudaGraphExecMemcpyNodeSetParams *
memsetAddresses for 1-dimensional memsets if allocated in same context; see ::cudaGraphExecMemsetNodeSetParams *
hostUnrestricted *
child graphTopology must match and restrictions apply recursively; see ::cudaGraphExecUpdate *
event waitUnrestricted *
event recordUnrestricted *
external semaphore signalNumber of semaphore operations cannot change *
external semaphore waitNumber of semaphore operations cannot change *
memory allocationAPI unsupported *
memory freeAPI unsupported *
* * \param graphExec - The executable graph in which to update the specified node * \param node - Corresponding node from the graph from which graphExec was instantiated * \param nodeParams - Updated Parameters to set * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidDeviceFunction, * ::cudaErrorNotSupported * \note_graph_thread_safety * \notefnerr * \note_init_rt * \note_callback * * \sa * ::cudaGraphAddNode, * ::cudaGraphNodeSetParams * ::cudaGraphExecUpdate, * ::cudaGraphInstantiate */ extern __host__ cudaError_t CUDARTAPI cudaGraphExecNodeSetParams(cudaGraphExec_t graphExec, cudaGraphNode_t node, struct cudaGraphNodeParams *nodeParams); /** * \brief Create a conditional handle * * Creates a conditional handle associated with \p hGraph. * * The conditional handle must be associated with a conditional node in this graph or one of its children. * * Handles not associated with a conditional node may cause graph instantiation to fail. * * \param pHandle_out - Pointer used to return the handle to the caller. * \param hGraph - Graph which will contain the conditional node using this handle. * \param defaultLaunchValue - Optional initial value for the conditional variable. * Applied at the beginning of each graph execution if cudaGraphCondAssignDefault is set in \p flags. * \param flags - Currently must be cudaGraphCondAssignDefault or 0. * * \return * ::CUDA_SUCCESS, * ::CUDA_ERROR_INVALID_VALUE, * ::CUDA_ERROR_NOT_SUPPORTED * \note_graph_thread_safety * \notefnerr * * \sa * ::cuGraphAddNode, */ extern __host__ cudaError_t CUDARTAPI cudaGraphConditionalHandleCreate(cudaGraphConditionalHandle *pHandle_out, cudaGraph_t graph, unsigned int defaultLaunchValue __dv(0), unsigned int flags __dv(0)); /** @} */ /* END CUDART_GRAPH */ /** * \defgroup CUDART_DRIVER_ENTRY_POINT Driver Entry Point Access * * ___MANBRIEF___ driver entry point access functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the driver entry point access functions of CUDA * runtime application programming interface. * * @{ */ /** * \brief Returns the requested driver API function pointer * * Returns in \p **funcPtr the address of the CUDA driver function for the requested flags. * * For a requested driver symbol, if the CUDA version in which the driver symbol was * introduced is less than or equal to the CUDA runtime version, the API will return * the function pointer to the corresponding versioned driver function. * * The pointer returned by the API should be cast to a function pointer matching the * requested driver function's definition in the API header file. The function pointer * typedef can be picked up from the corresponding typedefs header file. For example, * cudaTypedefs.h consists of function pointer typedefs for driver APIs defined in cuda.h. * * The API will return ::cudaSuccess and set the returned \p funcPtr if the * requested driver function is valid and supported on the platform. * * The API will return ::cudaSuccess and set the returned \p funcPtr to NULL if the * requested driver function is not supported on the platform, no ABI * compatible driver function exists for the CUDA runtime version or if the * driver symbol is invalid. * * It will also set the optional \p driverStatus to one of the values in * ::cudaDriverEntryPointQueryResult with the following meanings: * - ::cudaDriverEntryPointSuccess - The requested symbol was succesfully found based * on input arguments and \p pfn is valid * - ::cudaDriverEntryPointSymbolNotFound - The requested symbol was not found * - ::cudaDriverEntryPointVersionNotSufficent - The requested symbol was found but is * not supported by the current runtime version (CUDART_VERSION) * * The requested flags can be: * - ::cudaEnableDefault: This is the default mode. This is equivalent to * ::cudaEnablePerThreadDefaultStream if the code is compiled with * --default-stream per-thread compilation flag or the macro CUDA_API_PER_THREAD_DEFAULT_STREAM * is defined; ::cudaEnableLegacyStream otherwise. * - ::cudaEnableLegacyStream: This will enable the search for all driver symbols * that match the requested driver symbol name except the corresponding per-thread versions. * - ::cudaEnablePerThreadDefaultStream: This will enable the search for all * driver symbols that match the requested driver symbol name including the per-thread * versions. If a per-thread version is not found, the API will return the legacy version * of the driver function. * * \param symbol - The base name of the driver API function to look for. As an example, * for the driver API ::cuMemAlloc_v2, \p symbol would be cuMemAlloc. * Note that the API will use the CUDA runtime version to return the * address to the most recent ABI compatible driver symbol, ::cuMemAlloc * or ::cuMemAlloc_v2. * \param funcPtr - Location to return the function pointer to the requested driver function * \param flags - Flags to specify search options. * \param driverStatus - Optional location to store the status of finding the symbol from * the driver. See ::cudaDriverEntryPointQueryResult for * possible values. * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorNotSupported * \note_version_mixing * \note_init_rt * \note_callback * * \sa * ::cuGetProcAddress */ #if defined(__cplusplus) extern __host__ cudaError_t CUDARTAPI cudaGetDriverEntryPoint(const char *symbol, void **funcPtr, unsigned long long flags, enum cudaDriverEntryPointQueryResult *driverStatus = NULL); #else extern __host__ cudaError_t CUDARTAPI cudaGetDriverEntryPoint(const char *symbol, void **funcPtr, unsigned long long flags, enum cudaDriverEntryPointQueryResult *driverStatus); #endif /** * \brief Returns the requested driver API function pointer by CUDA version * * Returns in \p **funcPtr the address of the CUDA driver function for the requested flags and CUDA driver version. * * The CUDA version is specified as (1000 * major + 10 * minor), so CUDA 11.2 * should be specified as 11020. For a requested driver symbol, if the specified * CUDA version is greater than or equal to the CUDA version in which the driver symbol * was introduced, this API will return the function pointer to the corresponding * versioned function. * * The pointer returned by the API should be cast to a function pointer matching the * requested driver function's definition in the API header file. The function pointer * typedef can be picked up from the corresponding typedefs header file. For example, * cudaTypedefs.h consists of function pointer typedefs for driver APIs defined in cuda.h. * * For the case where the CUDA version requested is greater than the CUDA Toolkit * installed, there may not be an appropriate function pointer typedef in the * corresponding header file and may need a custom typedef to match the driver * function signature returned. This can be done by getting the typedefs from a later * toolkit or creating appropriately matching custom function typedefs. * * The API will return ::cudaSuccess and set the returned \p funcPtr if the * requested driver function is valid and supported on the platform. * * The API will return ::cudaSuccess and set the returned \p funcPtr to NULL if the * requested driver function is not supported on the platform, no ABI * compatible driver function exists for the requested version or if the * driver symbol is invalid. * * It will also set the optional \p driverStatus to one of the values in * ::cudaDriverEntryPointQueryResult with the following meanings: * - ::cudaDriverEntryPointSuccess - The requested symbol was succesfully found based * on input arguments and \p pfn is valid * - ::cudaDriverEntryPointSymbolNotFound - The requested symbol was not found * - ::cudaDriverEntryPointVersionNotSufficent - The requested symbol was found but is * not supported by the specified version \p cudaVersion * * The requested flags can be: * - ::cudaEnableDefault: This is the default mode. This is equivalent to * ::cudaEnablePerThreadDefaultStream if the code is compiled with * --default-stream per-thread compilation flag or the macro CUDA_API_PER_THREAD_DEFAULT_STREAM * is defined; ::cudaEnableLegacyStream otherwise. * - ::cudaEnableLegacyStream: This will enable the search for all driver symbols * that match the requested driver symbol name except the corresponding per-thread versions. * - ::cudaEnablePerThreadDefaultStream: This will enable the search for all * driver symbols that match the requested driver symbol name including the per-thread * versions. If a per-thread version is not found, the API will return the legacy version * of the driver function. * * \param symbol - The base name of the driver API function to look for. As an example, * for the driver API ::cuMemAlloc_v2, \p symbol would be cuMemAlloc. * \param funcPtr - Location to return the function pointer to the requested driver function * \param cudaVersion - The CUDA version to look for the requested driver symbol * \param flags - Flags to specify search options. * \param driverStatus - Optional location to store the status of finding the symbol from * the driver. See ::cudaDriverEntryPointQueryResult for * possible values. * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorNotSupported * \note_version_mixing * \note_init_rt * \note_callback * * \sa * ::cuGetProcAddress */ #if defined(__cplusplus) extern __host__ cudaError_t CUDARTAPI cudaGetDriverEntryPointByVersion(const char *symbol, void **funcPtr, unsigned int cudaVersion, unsigned long long flags, enum cudaDriverEntryPointQueryResult *driverStatus = NULL); #else extern __host__ cudaError_t CUDARTAPI cudaGetDriverEntryPointByVersion(const char *symbol, void **funcPtr, unsigned int cudaVersion, unsigned long long flags, enum cudaDriverEntryPointQueryResult *driverStatus); #endif /** @} */ /* END CUDART_DRIVER_ENTRY_POINT */ /** * \defgroup CUDART_LIBRARY Library Management * * ___MANBRIEF___ library management functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the library management functions of the CUDA runtime * application programming interface. * * @{ */ /** * \brief Load a library with specified code and options * * Takes a pointer \p code and loads the corresponding library \p library based on * the application defined library loading mode: * - If module loading is set to EAGER, via the environment variables described in "Module loading", * \p library is loaded eagerly into all contexts at the time of the call and future contexts * at the time of creation until the library is unloaded with ::cudaLibraryUnload(). * - If the environment variables are set to LAZY, \p library * is not immediately loaded onto all existent contexts and will only be * loaded when a function is needed for that context, such as a kernel launch. * * These environment variables are described in the CUDA programming guide under the * "CUDA environment variables" section. * * The \p code may be a \e cubin or \e fatbin as output by \b nvcc, * or a NULL-terminated \e PTX, either as output by \b nvcc or hand-written. * A fatbin should also contain relocatable code when doing separate compilation. * Please also see the documentation for nvrtc (https://docs.nvidia.com/cuda/nvrtc/index.html), * nvjitlink (https://docs.nvidia.com/cuda/nvjitlink/index.html), and nvfatbin * (https://docs.nvidia.com/cuda/nvfatbin/index.html) for more information on generating * loadable code at runtime. * * Options are passed as an array via \p jitOptions and any corresponding parameters are passed in * \p jitOptionsValues. The number of total JIT options is supplied via \p numJitOptions. * Any outputs will be returned via \p jitOptionsValues. * * Library load options are passed as an array via \p libraryOptions and any corresponding parameters are passed in * \p libraryOptionValues. The number of total library load options is supplied via \p numLibraryOptions. * * \param library - Returned library * \param code - Code to load * \param jitOptions - Options for JIT * \param jitOptionsValues - Option values for JIT * \param numJitOptions - Number of options * \param libraryOptions - Options for loading * \param libraryOptionValues - Option values for loading * \param numLibraryOptions - Number of options for loading * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorMemoryAllocation, * ::cudaErrorInitializationError, * ::cudaErrorCudartUnloading, * ::cudaErrorInvalidPtx, * ::cudaErrorUnsupportedPtxVersion, * ::cudaErrorNoKernelImageForDevice, * ::cudaErrorSharedObjectSymbolNotFound, * ::cudaErrorSharedObjectInitFailed, * ::cudaErrorJitCompilerNotFound * * \sa ::cudaLibraryLoadFromFile, * ::cudaLibraryUnload, * ::cuLibraryLoadData */ extern __host__ cudaError_t CUDARTAPI cudaLibraryLoadData(cudaLibrary_t *library, const void *code, enum cudaJitOption *jitOptions, void **jitOptionsValues, unsigned int numJitOptions, enum cudaLibraryOption *libraryOptions, void** libraryOptionValues, unsigned int numLibraryOptions); /** * \brief Load a library with specified file and options * * Takes a pointer \p code and loads the corresponding library \p library based on * the application defined library loading mode: * - If module loading is set to EAGER, via the environment variables described in "Module loading", * \p library is loaded eagerly into all contexts at the time of the call and future contexts * at the time of creation until the library is unloaded with ::cudaLibraryUnload(). * - If the environment variables are set to LAZY, \p library * is not immediately loaded onto all existent contexts and will only be * loaded when a function is needed for that context, such as a kernel launch. * * These environment variables are described in the CUDA programming guide under the * "CUDA environment variables" section. * * The file should be a \e cubin file as output by \b nvcc, or a \e PTX file either * as output by \b nvcc or handwritten, or a \e fatbin file as output by \b nvcc. * A fatbin should also contain relocatable code when doing separate compilation. * Please also see the documentation for nvrtc (https://docs.nvidia.com/cuda/nvrtc/index.html), * nvjitlink (https://docs.nvidia.com/cuda/nvjitlink/index.html), and nvfatbin * (https://docs.nvidia.com/cuda/nvfatbin/index.html) for more information on generating * loadable code at runtime. * * Options are passed as an array via \p jitOptions and any corresponding parameters are * passed in \p jitOptionsValues. The number of total options is supplied via \p numJitOptions. * Any outputs will be returned via \p jitOptionsValues. * * Library load options are passed as an array via \p libraryOptions and any corresponding parameters are passed in * \p libraryOptionValues. The number of total library load options is supplied via \p numLibraryOptions. * * \param library - Returned library * \param fileName - File to load from * \param jitOptions - Options for JIT * \param jitOptionsValues - Option values for JIT * \param numJitOptions - Number of options * \param libraryOptions - Options for loading * \param libraryOptionValues - Option values for loading * \param numLibraryOptions - Number of options for loading * * \return * ::cudaSuccess, * ::cudaErrorInvalidValue, * ::cudaErrorMemoryAllocation, * ::cudaErrorInitializationError, * ::cudaErrorCudartUnloading, * ::cudaErrorInvalidPtx, * ::cudaErrorUnsupportedPtxVersion, * ::cudaErrorNoKernelImageForDevice, * ::cudaErrorSharedObjectSymbolNotFound, * ::cudaErrorSharedObjectInitFailed, * ::cudaErrorJitCompilerNotFound * * \sa ::cudaLibraryLoadData, * ::cudaLibraryUnload, * ::cuLibraryLoadFromFile */ extern __host__ cudaError_t CUDARTAPI cudaLibraryLoadFromFile(cudaLibrary_t *library, const char *fileName, enum cudaJitOption *jitOptions, void **jitOptionsValues, unsigned int numJitOptions, enum cudaLibraryOption *libraryOptions, void **libraryOptionValues, unsigned int numLibraryOptions); /** * \brief Unloads a library * * Unloads the library specified with \p library * * \param library - Library to unload * * \return * ::cudaSuccess, * ::cudaErrorCudartUnloading, * ::cudaErrorInitializationError, * ::cudaErrorInvalidValue * * \sa ::cudaLibraryLoadData, * ::cudaLibraryLoadFromFile, * ::cuLibraryUnload */ extern __host__ cudaError_t CUDARTAPI cudaLibraryUnload(cudaLibrary_t library); /** * \brief Returns a kernel handle * * Returns in \p pKernel the handle of the kernel with name \p name located in library \p library. * If kernel handle is not found, the call returns ::cudaErrorSymbolNotFound. * * \param pKernel - Returned kernel handle * \param library - Library to retrieve kernel from * \param name - Name of kernel to retrieve * * \return * ::cudaSuccess, * ::cudaErrorCudartUnloading, * ::cudaErrorInitializationError, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorSymbolNotFound * * \sa ::cudaLibraryLoadData, * ::cudaLibraryLoadFromFile, * ::cudaLibraryUnload, * ::cuLibraryGetKernel */ extern __host__ cudaError_t CUDARTAPI cudaLibraryGetKernel(cudaKernel_t *pKernel, cudaLibrary_t library, const char *name); /** * \brief Returns a global device pointer * * Returns in \p *dptr and \p *bytes the base pointer and size of the global with * name \p name for the requested library \p library and the current device. * If no global for the requested name \p name exists, the call returns ::cudaErrorSymbolNotFound. * One of the parameters \p dptr or \p bytes (not both) can be NULL in which * case it is ignored. The returned \p dptr cannot be passed to the Symbol APIs * such as ::cudaMemcpyToSymbol, ::cudaMemcpyFromSymbol, ::cudaGetSymbolAddress, or * ::cudaGetSymbolSize. * * \param dptr - Returned global device pointer for the requested library * \param bytes - Returned global size in bytes * \param library - Library to retrieve global from * \param name - Name of global to retrieve * * \return * ::cudaSuccess, * ::cudaErrorCudartUnloading, * ::cudaErrorInitializationError, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorSymbolNotFound * ::cudaErrorDeviceUninitialized, * ::cudaErrorContextIsDestroyed * * \sa ::cudaLibraryLoadData, * ::cudaLibraryLoadFromFile, * ::cudaLibraryUnload, * ::cudaLibraryGetManaged, * ::cuLibraryGetGlobal */ extern __host__ cudaError_t CUDARTAPI cudaLibraryGetGlobal(void **dptr, size_t *bytes, cudaLibrary_t library, const char *name); /** * \brief Returns a pointer to managed memory * * Returns in \p *dptr and \p *bytes the base pointer and size of the managed memory with * name \p name for the requested library \p library. If no managed memory with the * requested name \p name exists, the call returns ::cudaErrorSymbolNotFound. One of the parameters * \p dptr or \p bytes (not both) can be NULL in which case it is ignored. * Note that managed memory for library \p library is shared across devices and is registered * when the library is loaded. The returned \p dptr cannot be passed to the Symbol APIs * such as ::cudaMemcpyToSymbol, ::cudaMemcpyFromSymbol, ::cudaGetSymbolAddress, or * ::cudaGetSymbolSize. * * \param dptr - Returned pointer to the managed memory * \param bytes - Returned memory size in bytes * \param library - Library to retrieve managed memory from * \param name - Name of managed memory to retrieve * * \return * ::cudaSuccess, * ::cudaErrorCudartUnloading, * ::cudaErrorInitializationError, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorSymbolNotFound * * \sa ::cudaLibraryLoadData, * ::cudaLibraryLoadFromFile, * ::cudaLibraryUnload, * ::cudaLibraryGetGlobal, * ::cuLibraryGetManaged */ extern __host__ cudaError_t CUDARTAPI cudaLibraryGetManaged(void **dptr, size_t *bytes, cudaLibrary_t library, const char *name); /** * \brief Returns a pointer to a unified function * * Returns in \p *fptr the function pointer to a unified function denoted by \p symbol. * If no unified function with name \p symbol exists, the call returns ::cudaErrorSymbolNotFound. * If there is no device with attribute ::cudaDeviceProp::unifiedFunctionPointers present in the system, * the call may return ::cudaErrorSymbolNotFound. * * \param fptr - Returned pointer to a unified function * \param library - Library to retrieve function pointer memory from * \param symbol - Name of function pointer to retrieve * * \return * ::cudaSuccess, * ::cudaErrorCudartUnloading, * ::cudaErrorInitializationError, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle, * ::cudaErrorSymbolNotFound * * \sa ::cudaLibraryLoadData, * ::cudaLibraryLoadFromFile, * ::cudaLibraryUnload, * ::cuLibraryGetUnifiedFunction */ extern __host__ cudaError_t CUDARTAPI cudaLibraryGetUnifiedFunction(void **fptr, cudaLibrary_t library, const char *symbol); /** * \brief Returns the number of kernels within a library * * Returns in \p count the number of kernels in \p lib. * * \param count - Number of kernels found within the library * \param lib - Library to query * * \return * ::cudaSuccess, * ::cudaErrorCudartUnloading, * ::cudaErrorInitializationError, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle * * \sa ::cudaLibraryEnumerateKernels, * ::cudaLibraryLoadFromFile, * ::cudaLibraryLoadData, * ::cuLibraryGetKernelCount */ extern __host__ cudaError_t CUDARTAPI cudaLibraryGetKernelCount(unsigned int *count, cudaLibrary_t lib); /** * \brief Retrieve the kernel handles within a library. * * Returns in \p kernels a maximum number of \p numKernels kernel handles within \p lib. * The returned kernel handle becomes invalid when the library is unloaded. * * \param kernels - Buffer where the kernel handles are returned to * \param numKernels - Maximum number of kernel handles may be returned to the buffer * \param lib - Library to query from * * \return * ::cudaSuccess, * ::cudaErrorCudartUnloading, * ::cudaErrorInitializationError, * ::cudaErrorInvalidValue, * ::cudaErrorInvalidResourceHandle * * \sa ::cudaLibraryGetKernelCount, * ::cuLibraryEnumerateKernels */ extern __host__ cudaError_t CUDARTAPI cudaLibraryEnumerateKernels(cudaKernel_t *kernels, unsigned int numKernels, cudaLibrary_t lib); /** * \brief Sets information about a kernel * * This call sets the value of a specified attribute \p attr on the kernel \p kernel * for the requested device \p device to an integer value specified by \p value. * This function returns ::cudaSuccess if the new value of the attribute could be * successfully set. If the set fails, this call will return an error. * Not all attributes can have values set. Attempting to set a value on a read-only * attribute will result in an error (::cudaErrorInvalidValue) * * Note that attributes set using ::cudaFuncSetAttribute() will override the attribute * set by this API irrespective of whether the call to ::cudaFuncSetAttribute() is made * before or after this API call. Because of this and the stricter locking requirements * mentioned below it is suggested that this call be used during the initialization path * and not on each thread accessing \p kernel such as on kernel launches or on the * critical path. * * Valid values for \p attr are: * - ::cudaFuncAttributeMaxDynamicSharedMemorySize - The requested maximum size in bytes of dynamically-allocated shared memory. The sum of this value and the function attribute ::sharedSizeBytes * cannot exceed the device attribute ::cudaDevAttrMaxSharedMemoryPerBlockOptin. The maximal size of requestable dynamic shared memory may differ by GPU architecture. * - ::cudaFuncAttributePreferredSharedMemoryCarveout - On devices where the L1 cache and shared memory use the same hardware resources, * this sets the shared memory carveout preference, in percent of the total shared memory. See ::cudaDevAttrMaxSharedMemoryPerMultiprocessor. * This is only a hint, and the driver can choose a different ratio if required to execute the function. * - ::cudaFuncAttributeRequiredClusterWidth: The required cluster width in * blocks. The width, height, and depth values must either all be 0 or all be * positive. The validity of the cluster dimensions is checked at launch time. * If the value is set during compile time, it cannot be set at runtime. * Setting it at runtime will return cudaErrorNotPermitted. * - ::cudaFuncAttributeRequiredClusterHeight: The required cluster height in * blocks. The width, height, and depth values must either all be 0 or all be * positive. The validity of the cluster dimensions is checked at launch time. * If the value is set during compile time, it cannot be set at runtime. * Setting it at runtime will return cudaErrorNotPermitted. * - ::cudaFuncAttributeRequiredClusterDepth: The required cluster depth in * blocks. The width, height, and depth values must either all be 0 or all be * positive. The validity of the cluster dimensions is checked at launch time. * If the value is set during compile time, it cannot be set at runtime. * Setting it at runtime will return cudaErrorNotPermitted. * - ::cudaFuncAttributeNonPortableClusterSizeAllowed: Indicates whether the * function can be launched with non-portable cluster size. 1 is allowed, 0 is * disallowed. * - ::cudaFuncAttributeClusterSchedulingPolicyPreference: The block * scheduling policy of a function. The value type is cudaClusterSchedulingPolicy. * * \note The API has stricter locking requirements in comparison to its legacy counterpart * ::cudaFuncSetAttribute() due to device-wide semantics. If multiple threads are trying to * set the same attribute on the same device simultaneously, the attribute setting will depend * on the interleavings chosen by the OS scheduler and memory consistency. * * \param kernel - Kernel to set attribute of * \param attr - Attribute requested * \param value - Value to set * \param device - Device to set attribute of * * \return * ::cudaSuccess, * ::cudaErrorInvalidDeviceFunction, * ::cudaErrorInvalidValue * * \sa ::cudaLibraryLoadData, * ::cudaLibraryLoadFromFile, * ::cudaLibraryUnload, * ::cudaLibraryGetKernel, * ::cudaLaunchKernel, * ::cudaFuncSetAttribute, * ::cuKernelSetAttribute */ extern __host__ cudaError_t CUDARTAPI cudaKernelSetAttributeForDevice(cudaKernel_t kernel, enum cudaFuncAttribute attr, int value, int device); /** @} */ /* END CUDART_LIBRARY */ /** \cond impl_private */ extern __host__ cudaError_t CUDARTAPI cudaGetExportTable(const void **ppExportTable, const cudaUUID_t *pExportTableId); /** \endcond impl_private */ /** * \defgroup CUDART_HIGHLEVEL C++ API Routines * * ___MANBRIEF___ C++ high level API functions of the CUDA runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the C++ high level API functions of the CUDA runtime * application programming interface. To use these functions, your * application needs to be compiled with the \p nvcc compiler. * * \brief C++-style interface built on top of CUDA runtime API */ /** * \defgroup CUDART_DRIVER Interactions with the CUDA Driver API * * ___MANBRIEF___ interactions between CUDA Driver API and CUDA Runtime API * (___CURRENT_FILE___) ___ENDMANBRIEF___ * * This section describes the interactions between the CUDA Driver API and the CUDA Runtime API * * @{ * * \section CUDART_CUDA_primary Primary Contexts * * There exists a one to one relationship between CUDA devices in the CUDA Runtime * API and ::CUcontext s in the CUDA Driver API within a process. The specific * context which the CUDA Runtime API uses for a device is called the device's * primary context. From the perspective of the CUDA Runtime API, a device and * its primary context are synonymous. * * \section CUDART_CUDA_init Initialization and Tear-Down * * CUDA Runtime API calls operate on the CUDA Driver API ::CUcontext which is current to * to the calling host thread. * * The function ::cudaInitDevice() ensures that the primary context is initialized * for the requested device but does not make it current to the calling thread. * * The function ::cudaSetDevice() initializes the primary context for the * specified device and makes it current to the calling thread by calling ::cuCtxSetCurrent(). * * The CUDA Runtime API will automatically initialize the primary context for * a device at the first CUDA Runtime API call which requires an active context. * If no ::CUcontext is current to the calling thread when a CUDA Runtime API call * which requires an active context is made, then the primary context for a device * will be selected, made current to the calling thread, and initialized. * * The context which the CUDA Runtime API initializes will be initialized using * the parameters specified by the CUDA Runtime API functions * ::cudaSetDeviceFlags(), * ::cudaD3D9SetDirect3DDevice(), * ::cudaD3D10SetDirect3DDevice(), * ::cudaD3D11SetDirect3DDevice(), * ::cudaGLSetGLDevice(), and * ::cudaVDPAUSetVDPAUDevice(). * Note that these functions will fail with ::cudaErrorSetOnActiveProcess if they are * called when the primary context for the specified device has already been initialized, * except for ::cudaSetDeviceFlags() which will simply overwrite the previous settings. * * Primary contexts will remain active until they are explicitly deinitialized * using ::cudaDeviceReset(). The function ::cudaDeviceReset() will deinitialize the * primary context for the calling thread's current device immediately. The context * will remain current to all of the threads that it was current to. The next CUDA * Runtime API call on any thread which requires an active context will trigger the * reinitialization of that device's primary context. * * Note that primary contexts are shared resources. It is recommended that * the primary context not be reset except just before exit or to recover from an * unspecified launch failure. * * \section CUDART_CUDA_context Context Interoperability * * Note that the use of multiple ::CUcontext s per device within a single process * will substantially degrade performance and is strongly discouraged. Instead, * it is highly recommended that the implicit one-to-one device-to-context mapping * for the process provided by the CUDA Runtime API be used. * * If a non-primary ::CUcontext created by the CUDA Driver API is current to a * thread then the CUDA Runtime API calls to that thread will operate on that * ::CUcontext, with some exceptions listed below. Interoperability between data * types is discussed in the following sections. * * The function ::cudaPointerGetAttributes() will return the error * ::cudaErrorIncompatibleDriverContext if the pointer being queried was allocated by a * non-primary context. The function ::cudaDeviceEnablePeerAccess() and the rest of * the peer access API may not be called when a non-primary ::CUcontext is current. * To use the pointer query and peer access APIs with a context created using the * CUDA Driver API, it is necessary that the CUDA Driver API be used to access * these features. * * All CUDA Runtime API state (e.g, global variables' addresses and values) travels * with its underlying ::CUcontext. In particular, if a ::CUcontext is moved from one * thread to another then all CUDA Runtime API state will move to that thread as well. * * Please note that attaching to legacy contexts (those with a version of 3010 as returned * by ::cuCtxGetApiVersion()) is not possible. The CUDA Runtime will return * ::cudaErrorIncompatibleDriverContext in such cases. * * \section CUDART_CUDA_stream Interactions between CUstream and cudaStream_t * * The types ::CUstream and ::cudaStream_t are identical and may be used interchangeably. * * \section CUDART_CUDA_event Interactions between CUevent and cudaEvent_t * * The types ::CUevent and ::cudaEvent_t are identical and may be used interchangeably. * * \section CUDART_CUDA_array Interactions between CUarray and cudaArray_t * * The types ::CUarray and struct ::cudaArray * represent the same data type and may be used * interchangeably by casting the two types between each other. * * In order to use a ::CUarray in a CUDA Runtime API function which takes a struct ::cudaArray *, * it is necessary to explicitly cast the ::CUarray to a struct ::cudaArray *. * * In order to use a struct ::cudaArray * in a CUDA Driver API function which takes a ::CUarray, * it is necessary to explicitly cast the struct ::cudaArray * to a ::CUarray . * * \section CUDART_CUDA_graphicsResource Interactions between CUgraphicsResource and cudaGraphicsResource_t * * The types ::CUgraphicsResource and ::cudaGraphicsResource_t represent the same data type and may be used * interchangeably by casting the two types between each other. * * In order to use a ::CUgraphicsResource in a CUDA Runtime API function which takes a * ::cudaGraphicsResource_t, it is necessary to explicitly cast the ::CUgraphicsResource * to a ::cudaGraphicsResource_t. * * In order to use a ::cudaGraphicsResource_t in a CUDA Driver API function which takes a * ::CUgraphicsResource, it is necessary to explicitly cast the ::cudaGraphicsResource_t * to a ::CUgraphicsResource. * * \section CUDART_CUDA_texture_objects Interactions between CUtexObject and cudaTextureObject_t * * The types ::CUtexObject and ::cudaTextureObject_t represent the same data type and may be used * interchangeably by casting the two types between each other. * * In order to use a ::CUtexObject in a CUDA Runtime API function which takes a ::cudaTextureObject_t, * it is necessary to explicitly cast the ::CUtexObject to a ::cudaTextureObject_t. * * In order to use a ::cudaTextureObject_t in a CUDA Driver API function which takes a ::CUtexObject, * it is necessary to explicitly cast the ::cudaTextureObject_t to a ::CUtexObject. * * \section CUDART_CUDA_surface_objects Interactions between CUsurfObject and cudaSurfaceObject_t * * The types ::CUsurfObject and ::cudaSurfaceObject_t represent the same data type and may be used * interchangeably by casting the two types between each other. * * In order to use a ::CUsurfObject in a CUDA Runtime API function which takes a ::cudaSurfaceObject_t, * it is necessary to explicitly cast the ::CUsurfObject to a ::cudaSurfaceObject_t. * * In order to use a ::cudaSurfaceObject_t in a CUDA Driver API function which takes a ::CUsurfObject, * it is necessary to explicitly cast the ::cudaSurfaceObject_t to a ::CUsurfObject. * * \section CUDART_CUDA_module Interactions between CUfunction and cudaFunction_t * * The types ::CUfunction and ::cudaFunction_t represent the same data type and may be used * interchangeably by casting the two types between each other. * * In order to use a ::cudaFunction_t in a CUDA Driver API function which takes a ::CUfunction, * it is necessary to explicitly cast the ::cudaFunction_t to a ::CUfunction. * * \section CUDART_CUDA_library Interactions between CUkernel and cudaKernel_t * * The types ::CUkernel and ::cudaKernel_t represent the same data type and may be used * interchangeably by casting the two types between each other. * * In order to use a ::cudaKernel_t in a CUDA Driver API function which takes a ::CUkernel, * it is necessary to explicitly cast the ::cudaKernel_t to a ::CUkernel. * */ /** * \brief Get pointer to device entry function that matches entry function \p symbolPtr * * Returns in \p functionPtr the device entry function corresponding to the symbol \p symbolPtr. * * \param functionPtr - Returns the device entry function * \param symbolPtr - Pointer to device entry function to search for * * \return * ::cudaSuccess * */ extern __host__ cudaError_t cudaGetFuncBySymbol(cudaFunction_t* functionPtr, const void* symbolPtr); /** * \brief Get pointer to device kernel that matches entry function \p entryFuncAddr * * Returns in \p kernelPtr the device kernel corresponding to the entry function \p entryFuncAddr. * * Note that it is possible that there are multiple symbols belonging to different * translation units with the same \p entryFuncAddr registered with this CUDA Runtime * and so the order which the translation units are loaded and registered with the * CUDA Runtime can lead to differing return pointers in \p kernelPtr . * Suggested methods of ensuring uniqueness are to limit visibility of __global__ * device functions by using static or hidden visibility attribute in the * respective translation units. * * \param kernelPtr - Returns the device kernel * \param entryFuncAddr - Address of device entry function to search kernel for * * \return * ::cudaSuccess * * \sa * \ref ::cudaGetKernel(cudaKernel_t *kernelPtr, const T *entryFuncAddr) "cudaGetKernel (C++ API)" */ extern __host__ cudaError_t CUDARTAPI cudaGetKernel(cudaKernel_t *kernelPtr, const void *entryFuncAddr); /** @} */ /* END CUDART_DRIVER */ #if defined(__CUDA_API_VERSION_INTERNAL) #undef cudaMemcpy #undef cudaMemcpyToSymbol #undef cudaMemcpyFromSymbol #undef cudaMemcpy2D #undef cudaMemcpyToArray #undef cudaMemcpy2DToArray #undef cudaMemcpyFromArray #undef cudaMemcpy2DFromArray #undef cudaMemcpyArrayToArray #undef cudaMemcpy2DArrayToArray #undef cudaMemcpy3D #undef cudaMemcpy3DPeer #undef cudaMemset #undef cudaMemset2D #undef cudaMemset3D #undef cudaMemcpyAsync #undef cudaMemcpyToSymbolAsync #undef cudaMemcpyFromSymbolAsync #undef cudaMemcpy2DAsync #undef cudaMemcpyToArrayAsync #undef cudaMemcpy2DToArrayAsync #undef cudaMemcpyFromArrayAsync #undef cudaMemcpy2DFromArrayAsync #undef cudaMemcpy3DAsync #undef cudaMemcpy3DPeerAsync #undef cudaMemcpyBatchAsync #undef cudaMemcpy3DBatchAsync #undef cudaMemsetAsync #undef cudaMemset2DAsync #undef cudaMemset3DAsync #undef cudaStreamQuery #undef cudaStreamGetDevice #undef cudaStreamGetFlags #undef cudaStreamGetId #undef cudaStreamGetPriority #undef cudaEventRecord #undef cudaEventRecordWithFlags #undef cudaStreamWaitEvent #undef cudaStreamAddCallback #undef cudaStreamAttachMemAsync #undef cudaStreamSynchronize #undef cudaLaunchKernel #undef cudaLaunchKernelExC #undef cudaLaunchHostFunc #undef cudaMemPrefetchAsync #undef cudaMemPrefetchAsync_v2 #undef cudaLaunchCooperativeKernel #undef cudaSignalExternalSemaphoresAsync #undef cudaWaitExternalSemaphoresAsync #undef cudaGraphInstantiateWithParams #undef cudaGraphUpload #undef cudaGraphLaunch #undef cudaStreamBeginCapture #undef cudaStreamBeginCaptureToGraph #undef cudaStreamEndCapture #undef cudaStreamIsCapturing #undef cudaStreamGetCaptureInfo #undef cudaStreamGetCaptureInfo_v2 #undef cudaStreamGetCaptureInfo_v3 #undef cudaStreamUpdateCaptureDependencies #undef cudaStreamUpdateCaptureDependencies_v2 #undef cudaStreamCopyAttributes #undef cudaStreamGetAttribute #undef cudaStreamSetAttribute #undef cudaMallocAsync #undef cudaFreeAsync #undef cudaMallocFromPoolAsync #undef cudaGetDriverEntryPoint #undef cudaGetDriverEntryPointByVersion #undef cudaGetDeviceProperties extern __host__ cudaError_t CUDARTAPI cudaMemcpy(void *dst, const void *src, size_t count, enum cudaMemcpyKind kind); extern __host__ cudaError_t CUDARTAPI cudaMemcpyToSymbol(const void *symbol, const void *src, size_t count, size_t offset __dv(0), enum cudaMemcpyKind kind __dv(cudaMemcpyHostToDevice)); extern __host__ cudaError_t CUDARTAPI cudaMemcpyFromSymbol(void *dst, const void *symbol, size_t count, size_t offset __dv(0), enum cudaMemcpyKind kind __dv(cudaMemcpyDeviceToHost)); extern __host__ cudaError_t CUDARTAPI cudaMemcpy2D(void *dst, size_t dpitch, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind); extern __host__ cudaError_t CUDARTAPI cudaMemcpyToArray(cudaArray_t dst, size_t wOffset, size_t hOffset, const void *src, size_t count, enum cudaMemcpyKind kind); extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DToArray(cudaArray_t dst, size_t wOffset, size_t hOffset, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind); extern __host__ cudaError_t CUDARTAPI cudaMemcpyFromArray(void *dst, cudaArray_const_t src, size_t wOffset, size_t hOffset, size_t count, enum cudaMemcpyKind kind); extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DFromArray(void *dst, size_t dpitch, cudaArray_const_t src, size_t wOffset, size_t hOffset, size_t width, size_t height, enum cudaMemcpyKind kind); extern __host__ cudaError_t CUDARTAPI cudaMemcpyArrayToArray(cudaArray_t dst, size_t wOffsetDst, size_t hOffsetDst, cudaArray_const_t src, size_t wOffsetSrc, size_t hOffsetSrc, size_t count, enum cudaMemcpyKind kind __dv(cudaMemcpyDeviceToDevice)); extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DArrayToArray(cudaArray_t dst, size_t wOffsetDst, size_t hOffsetDst, cudaArray_const_t src, size_t wOffsetSrc, size_t hOffsetSrc, size_t width, size_t height, enum cudaMemcpyKind kind __dv(cudaMemcpyDeviceToDevice)); extern __host__ cudaError_t CUDARTAPI cudaMemcpy3D(const struct cudaMemcpy3DParms *p); extern __host__ cudaError_t CUDARTAPI cudaMemcpy3DPeer(const struct cudaMemcpy3DPeerParms *p); extern __host__ cudaError_t CUDARTAPI cudaMemcpyBatchAsync(void **dsts, void **srcs, size_t *sizes, size_t count, struct cudaMemcpyAttributes *attrs, size_t *attrsIdxs, size_t numAttrs, size_t *failIdx, cudaStream_t stream); extern __host__ cudaError_t CUDARTAPI cudaMemcpy3DBatchAsync(size_t numOps, struct cudaMemcpy3DBatchOp *opList, size_t *failIdx, unsigned long long flags, cudaStream_t stream); extern __host__ cudaError_t CUDARTAPI cudaMemset(void *devPtr, int value, size_t count); extern __host__ cudaError_t CUDARTAPI cudaMemset2D(void *devPtr, size_t pitch, int value, size_t width, size_t height); extern __host__ cudaError_t CUDARTAPI cudaMemset3D(struct cudaPitchedPtr pitchedDevPtr, int value, struct cudaExtent extent); extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemcpyAsync(void *dst, const void *src, size_t count, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0)); extern __host__ cudaError_t CUDARTAPI cudaMemcpyToSymbolAsync(const void *symbol, const void *src, size_t count, size_t offset, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0)); extern __host__ cudaError_t CUDARTAPI cudaMemcpyFromSymbolAsync(void *dst, const void *symbol, size_t count, size_t offset, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0)); extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemcpy2DAsync(void *dst, size_t dpitch, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0)); extern __host__ cudaError_t CUDARTAPI cudaMemcpyToArrayAsync(cudaArray_t dst, size_t wOffset, size_t hOffset, const void *src, size_t count, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0)); extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DToArrayAsync(cudaArray_t dst, size_t wOffset, size_t hOffset, const void *src, size_t spitch, size_t width, size_t height, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0)); extern __host__ cudaError_t CUDARTAPI cudaMemcpyFromArrayAsync(void *dst, cudaArray_const_t src, size_t wOffset, size_t hOffset, size_t count, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0)); extern __host__ cudaError_t CUDARTAPI cudaMemcpy2DFromArrayAsync(void *dst, size_t dpitch, cudaArray_const_t src, size_t wOffset, size_t hOffset, size_t width, size_t height, enum cudaMemcpyKind kind, cudaStream_t stream __dv(0)); extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemcpy3DAsync(const struct cudaMemcpy3DParms *p, cudaStream_t stream __dv(0)); extern __host__ cudaError_t CUDARTAPI cudaMemcpy3DPeerAsync(const struct cudaMemcpy3DPeerParms *p, cudaStream_t stream __dv(0)); extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemsetAsync(void *devPtr, int value, size_t count, cudaStream_t stream __dv(0)); extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemset2DAsync(void *devPtr, size_t pitch, int value, size_t width, size_t height, cudaStream_t stream __dv(0)); extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaMemset3DAsync(struct cudaPitchedPtr pitchedDevPtr, int value, struct cudaExtent extent, cudaStream_t stream __dv(0)); extern __host__ cudaError_t CUDARTAPI cudaStreamQuery(cudaStream_t stream); extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamGetDevice(cudaStream_t hStream, int *device); extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamGetFlags(cudaStream_t hStream, unsigned int *flags); extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamGetId(cudaStream_t hStream, unsigned long long *streamId); extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamGetPriority(cudaStream_t hStream, int *priority); extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaEventRecord(cudaEvent_t event, cudaStream_t stream __dv(0)); extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaEventRecordWithFlags(cudaEvent_t event, cudaStream_t stream __dv(0), unsigned int flags __dv(0)); extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamWaitEvent(cudaStream_t stream, cudaEvent_t event, unsigned int flags); extern __host__ cudaError_t CUDARTAPI cudaStreamAddCallback(cudaStream_t stream, cudaStreamCallback_t callback, void *userData, unsigned int flags); extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaStreamAttachMemAsync(cudaStream_t stream, void *devPtr, size_t length, unsigned int flags); extern __host__ cudaError_t CUDARTAPI cudaStreamSynchronize(cudaStream_t stream); extern __host__ cudaError_t CUDARTAPI cudaLaunchKernel(const void *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream); extern __host__ cudaError_t CUDARTAPI cudaLaunchKernelExC(const cudaLaunchConfig_t *config, const void *func, void **args); extern __host__ cudaError_t CUDARTAPI cudaLaunchCooperativeKernel(const void *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream); extern __host__ cudaError_t CUDARTAPI cudaLaunchHostFunc(cudaStream_t stream, cudaHostFn_t fn, void *userData); extern __host__ cudaError_t CUDARTAPI cudaMemPrefetchAsync(const void *devPtr, size_t count, int dstDevice, cudaStream_t stream); extern __host__ cudaError_t CUDARTAPI cudaMemPrefetchAsync_v2(const void *devPtr, size_t count, struct cudaMemLocation location, unsigned int flags, cudaStream_t stream); extern __host__ cudaError_t CUDARTAPI cudaSignalExternalSemaphoresAsync(const cudaExternalSemaphore_t *extSemArray, const struct cudaExternalSemaphoreSignalParams_v1 *paramsArray, unsigned int numExtSems, cudaStream_t stream __dv(0)); extern __host__ cudaError_t CUDARTAPI cudaSignalExternalSemaphoresAsync_ptsz(const cudaExternalSemaphore_t *extSemArray, const struct cudaExternalSemaphoreSignalParams_v1 *paramsArray, unsigned int numExtSems, cudaStream_t stream __dv(0)); extern __host__ cudaError_t CUDARTAPI cudaSignalExternalSemaphoresAsync_v2(const cudaExternalSemaphore_t *extSemArray, const struct cudaExternalSemaphoreSignalParams *paramsArray, unsigned int numExtSems, cudaStream_t stream __dv(0)); extern __host__ cudaError_t CUDARTAPI cudaWaitExternalSemaphoresAsync(const cudaExternalSemaphore_t *extSemArray, const struct cudaExternalSemaphoreWaitParams_v1 *paramsArray, unsigned int numExtSems, cudaStream_t stream __dv(0)); extern __host__ cudaError_t CUDARTAPI cudaWaitExternalSemaphoresAsync_ptsz(const cudaExternalSemaphore_t *extSemArray, const struct cudaExternalSemaphoreWaitParams_v1 *paramsArray, unsigned int numExtSems, cudaStream_t stream __dv(0)); extern __host__ cudaError_t CUDARTAPI cudaWaitExternalSemaphoresAsync_v2(const cudaExternalSemaphore_t *extSemArray, const struct cudaExternalSemaphoreWaitParams *paramsArray, unsigned int numExtSems, cudaStream_t stream __dv(0)); extern __host__ cudaError_t CUDARTAPI cudaGraphInstantiateWithParams(cudaGraphExec_t *pGraphExec, cudaGraph_t graph, cudaGraphInstantiateParams *instantiateParams); extern __host__ cudaError_t CUDARTAPI cudaGraphUpload(cudaGraphExec_t graphExec, cudaStream_t stream); extern __host__ cudaError_t CUDARTAPI cudaGraphLaunch(cudaGraphExec_t graphExec, cudaStream_t stream); extern __host__ cudaError_t CUDARTAPI cudaStreamBeginCapture(cudaStream_t stream, enum cudaStreamCaptureMode mode); extern __host__ cudaError_t CUDARTAPI cudaStreamBeginCaptureToGraph(cudaStream_t stream, cudaGraph_t graph, const cudaGraphNode_t *dependencies, const cudaGraphEdgeData *dependencyData, size_t numDependencies, enum cudaStreamCaptureMode mode); extern __host__ cudaError_t CUDARTAPI cudaStreamEndCapture(cudaStream_t stream, cudaGraph_t *pGraph); extern __host__ cudaError_t CUDARTAPI cudaStreamIsCapturing(cudaStream_t stream, enum cudaStreamCaptureStatus *pCaptureStatus); extern __host__ cudaError_t CUDARTAPI cudaStreamGetCaptureInfo(cudaStream_t stream, enum cudaStreamCaptureStatus *captureStatus_out, unsigned long long *id_out); extern __host__ cudaError_t CUDARTAPI cudaStreamGetCaptureInfo_ptsz(cudaStream_t stream, enum cudaStreamCaptureStatus *captureStatus_out, unsigned long long *id_out); extern __host__ cudaError_t CUDARTAPI cudaStreamGetCaptureInfo_v2(cudaStream_t stream, enum cudaStreamCaptureStatus *captureStatus_out, unsigned long long *id_out __dv(0), cudaGraph_t *graph_out __dv(0), const cudaGraphNode_t **dependencies_out __dv(0), size_t *numDependencies_out __dv(0)); extern __host__ cudaError_t CUDARTAPI cudaStreamGetCaptureInfo_v3(cudaStream_t stream, enum cudaStreamCaptureStatus *captureStatus_out, unsigned long long *id_out __dv(0), cudaGraph_t *graph_out __dv(0), const cudaGraphNode_t **dependencies_out __dv(0), const cudaGraphEdgeData **edgeData_out __dv(0), size_t *numDependencies_out __dv(0)); extern __host__ cudaError_t CUDARTAPI cudaStreamUpdateCaptureDependencies(cudaStream_t stream, cudaGraphNode_t *dependencies, size_t numDependencies, unsigned int flags __dv(0)); extern __host__ cudaError_t CUDARTAPI cudaStreamUpdateCaptureDependencies_v2(cudaStream_t stream, cudaGraphNode_t *dependencies, const cudaGraphEdgeData *dependencyData, size_t numDependencies, unsigned int flags __dv(0)); extern __host__ cudaError_t CUDARTAPI cudaStreamCopyAttributes(cudaStream_t dstStream, cudaStream_t srcStream); extern __host__ cudaError_t CUDARTAPI cudaStreamGetAttribute(cudaStream_t stream, cudaStreamAttrID attr, cudaStreamAttrValue *value); extern __host__ cudaError_t CUDARTAPI cudaStreamSetAttribute(cudaStream_t stream, cudaStreamAttrID attr, const cudaStreamAttrValue *param); extern __host__ cudaError_t CUDARTAPI cudaMallocAsync(void **devPtr, size_t size, cudaStream_t hStream); extern __host__ cudaError_t CUDARTAPI cudaFreeAsync(void *devPtr, cudaStream_t hStream); extern __host__ cudaError_t CUDARTAPI cudaMallocFromPoolAsync(void **ptr, size_t size, cudaMemPool_t memPool, cudaStream_t stream); extern __host__ cudaError_t CUDARTAPI cudaGetDriverEntryPoint(const char *symbol, void **funcPtr, unsigned long long flags, enum cudaDriverEntryPointQueryResult *driverStatus); extern __host__ cudaError_t CUDARTAPI cudaGetDriverEntryPointByVersion(const char *symbol, void **funcPtr, unsigned int cudaVersion, unsigned long long flags, enum cudaDriverEntryPointQueryResult *driverStatus); extern __host__ __cudart_builtin__ cudaError_t CUDARTAPI cudaGetDeviceProperties(struct cudaDeviceProp *prop, int device); #elif defined(__CUDART_API_PER_THREAD_DEFAULT_STREAM) // nvcc stubs reference the 'cudaLaunch'/'cudaLaunchKernel' identifier even if it was defined // to 'cudaLaunch_ptsz'/'cudaLaunchKernel_ptsz'. Redirect through a static inline function. #undef cudaLaunchKernel static __inline__ __host__ cudaError_t cudaLaunchKernel(const void *func, dim3 gridDim, dim3 blockDim, void **args, size_t sharedMem, cudaStream_t stream) { return cudaLaunchKernel_ptsz(func, gridDim, blockDim, args, sharedMem, stream); } #define cudaLaunchKernel __CUDART_API_PTSZ(cudaLaunchKernel) #undef cudaLaunchKernelExC static __inline__ __host__ cudaError_t cudaLaunchKernelExC(const cudaLaunchConfig_t *config, const void *func, void **args) { return cudaLaunchKernelExC_ptsz(config, func, args); } #define cudaLaunchKernelExC __CUDART_API_PTSZ(cudaLaunchKernelExC) #endif #if defined(__cplusplus) } #endif /* __cplusplus */ #undef EXCLUDE_FROM_RTC #endif /* !__CUDACC_RTC__ */ #undef __dv #undef __CUDA_DEPRECATED #if defined(__UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_CUDA_RUNTIME_API_H__) #undef __CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS__ #undef __UNDEF_CUDA_INCLUDE_COMPILER_INTERNAL_HEADERS_CUDA_RUNTIME_API_H__ #endif #endif /* !__CUDA_RUNTIME_API_H__ */