/** * Author......: See docs/credits.txt * License.....: MIT */ #ifndef _EXT_CUDA_H #define _EXT_CUDA_H /** * from cuda.h (/usr/local/cuda-10.1/targets/x86_64-linux/include/cuda.h) */ #define __CUDA_API_VERSION 10010 /** * CUDA device pointer * CUdeviceptr is defined as an unsigned integer type whose size matches the size of a pointer on the target platform. */ #if __CUDA_API_VERSION >= 3020 #if defined(_WIN64) || defined(__LP64__) typedef unsigned long long CUdeviceptr; #else typedef unsigned int CUdeviceptr; #endif #endif /* __CUDA_API_VERSION >= 3020 */ typedef int CUdevice; /**< CUDA device */ typedef struct CUctx_st *CUcontext; /**< CUDA context */ typedef struct CUevent_st *CUevent; /**< CUDA event */ typedef struct CUfunc_st *CUfunction; /**< CUDA function */ typedef struct CUmod_st *CUmodule; /**< CUDA module */ typedef struct CUstream_st *CUstream; /**< CUDA stream */ typedef enum cudaError_enum { /** * The API call returned with no errors. In the case of query calls, this * also means that the operation being queried is complete (see * ::cuEventQuery() and ::cuStreamQuery()). */ CUDA_SUCCESS = 0, /** * This indicates that one or more of the parameters passed to the API call * is not within an acceptable range of values. */ CUDA_ERROR_INVALID_VALUE = 1, /** * The API call failed because it was unable to allocate enough memory to * perform the requested operation. */ CUDA_ERROR_OUT_OF_MEMORY = 2, /** * This indicates that the CUDA driver has not been initialized with * ::cuInit() or that initialization has failed. */ CUDA_ERROR_NOT_INITIALIZED = 3, /** * This indicates that the CUDA driver is in the process of shutting down. */ CUDA_ERROR_DEINITIALIZED = 4, /** * This indicates profiler is not initialized for this run. This can * happen when the application is running with external profiling tools * like visual profiler. */ CUDA_ERROR_PROFILER_DISABLED = 5, /** * \deprecated * This error return is deprecated as of CUDA 5.0. It is no longer an error * to attempt to enable/disable the profiling via ::cuProfilerStart or * ::cuProfilerStop without initialization. */ CUDA_ERROR_PROFILER_NOT_INITIALIZED = 6, /** * \deprecated * This error return is deprecated as of CUDA 5.0. It is no longer an error * to call cuProfilerStart() when profiling is already enabled. */ CUDA_ERROR_PROFILER_ALREADY_STARTED = 7, /** * \deprecated * This error return is deprecated as of CUDA 5.0. It is no longer an error * to call cuProfilerStop() when profiling is already disabled. */ CUDA_ERROR_PROFILER_ALREADY_STOPPED = 8, /** * This indicates that no CUDA-capable devices were detected by the installed * CUDA driver. */ CUDA_ERROR_NO_DEVICE = 100, /** * This indicates that the device ordinal supplied by the user does not * correspond to a valid CUDA device. */ CUDA_ERROR_INVALID_DEVICE = 101, /** * This indicates that the device kernel image is invalid. This can also * indicate an invalid CUDA module. */ CUDA_ERROR_INVALID_IMAGE = 200, /** * This most frequently indicates that there is no context bound to the * current thread. This can also be returned if the context passed to an * API call is not a valid handle (such as a context that has had * ::cuCtxDestroy() invoked on it). This can also be returned if a user * mixes different API versions (i.e. 3010 context with 3020 API calls). * See ::cuCtxGetApiVersion() for more details. */ CUDA_ERROR_INVALID_CONTEXT = 201, /** * This indicated that the context being supplied as a parameter to the * API call was already the active context. * \deprecated * This error return is deprecated as of CUDA 3.2. It is no longer an * error to attempt to push the active context via ::cuCtxPushCurrent(). */ CUDA_ERROR_CONTEXT_ALREADY_CURRENT = 202, /** * This indicates that a map or register operation has failed. */ CUDA_ERROR_MAP_FAILED = 205, /** * This indicates that an unmap or unregister operation has failed. */ CUDA_ERROR_UNMAP_FAILED = 206, /** * This indicates that the specified array is currently mapped and thus * cannot be destroyed. */ CUDA_ERROR_ARRAY_IS_MAPPED = 207, /** * This indicates that the resource is already mapped. */ CUDA_ERROR_ALREADY_MAPPED = 208, /** * This indicates that there is no kernel image available that is suitable * for the device. This can occur when a user specifies code generation * options for a particular CUDA source file that do not include the * corresponding device configuration. */ CUDA_ERROR_NO_BINARY_FOR_GPU = 209, /** * This indicates that a resource has already been acquired. */ CUDA_ERROR_ALREADY_ACQUIRED = 210, /** * This indicates that a resource is not mapped. */ CUDA_ERROR_NOT_MAPPED = 211, /** * This indicates that a mapped resource is not available for access as an * array. */ CUDA_ERROR_NOT_MAPPED_AS_ARRAY = 212, /** * This indicates that a mapped resource is not available for access as a * pointer. */ CUDA_ERROR_NOT_MAPPED_AS_POINTER = 213, /** * This indicates that an uncorrectable ECC error was detected during * execution. */ CUDA_ERROR_ECC_UNCORRECTABLE = 214, /** * This indicates that the ::CUlimit passed to the API call is not * supported by the active device. */ CUDA_ERROR_UNSUPPORTED_LIMIT = 215, /** * This indicates that the ::CUcontext passed to the API call can * only be bound to a single CPU thread at a time but is already * bound to a CPU thread. */ CUDA_ERROR_CONTEXT_ALREADY_IN_USE = 216, /** * This indicates that peer access is not supported across the given * devices. */ CUDA_ERROR_PEER_ACCESS_UNSUPPORTED = 217, /** * This indicates that a PTX JIT compilation failed. */ CUDA_ERROR_INVALID_PTX = 218, /** * This indicates an error with OpenGL or DirectX context. */ CUDA_ERROR_INVALID_GRAPHICS_CONTEXT = 219, /** * This indicates that an uncorrectable NVLink error was detected during the * execution. */ CUDA_ERROR_NVLINK_UNCORRECTABLE = 220, /** * This indicates that the PTX JIT compiler library was not found. */ CUDA_ERROR_JIT_COMPILER_NOT_FOUND = 221, /** * This indicates that the device kernel source is invalid. */ CUDA_ERROR_INVALID_SOURCE = 300, /** * This indicates that the file specified was not found. */ CUDA_ERROR_FILE_NOT_FOUND = 301, /** * This indicates that a link to a shared object failed to resolve. */ CUDA_ERROR_SHARED_OBJECT_SYMBOL_NOT_FOUND = 302, /** * This indicates that initialization of a shared object failed. */ CUDA_ERROR_SHARED_OBJECT_INIT_FAILED = 303, /** * This indicates that an OS call failed. */ CUDA_ERROR_OPERATING_SYSTEM = 304, /** * This indicates that a resource handle passed to the API call was not * valid. Resource handles are opaque types like ::CUstream and ::CUevent. */ CUDA_ERROR_INVALID_HANDLE = 400, /** * This indicates that a resource required by the API call is not in a * valid state to perform the requested operation. */ CUDA_ERROR_ILLEGAL_STATE = 401, /** * This indicates that a named symbol was not found. Examples of symbols * are global/constant variable names, texture names, and surface names. */ CUDA_ERROR_NOT_FOUND = 500, /** * This indicates that asynchronous operations issued previously have not * completed yet. This result is not actually an error, but must be indicated * differently than ::CUDA_SUCCESS (which indicates completion). Calls that * may return this value include ::cuEventQuery() and ::cuStreamQuery(). */ CUDA_ERROR_NOT_READY = 600, /** * While executing a kernel, the device encountered a * load or store instruction on an invalid memory address. * This leaves the process in an inconsistent state and any further CUDA work * will return the same error. To continue using CUDA, the process must be terminated * and relaunched. */ CUDA_ERROR_ILLEGAL_ADDRESS = 700, /** * This indicates that a launch did not occur because it did not have * appropriate resources. This error usually indicates that the user has * attempted to pass too many arguments to the device kernel, or the * kernel launch specifies too many threads for the kernel's register * count. Passing arguments of the wrong size (i.e. a 64-bit pointer * when a 32-bit int is expected) is equivalent to passing too many * arguments and can also result in this error. */ CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES = 701, /** * This indicates that the device kernel took too long to execute. This can * only occur if timeouts are enabled - see the device attribute * ::CU_DEVICE_ATTRIBUTE_KERNEL_EXEC_TIMEOUT for more information. * This leaves the process in an inconsistent state and any further CUDA work * will return the same error. To continue using CUDA, the process must be terminated * and relaunched. */ CUDA_ERROR_LAUNCH_TIMEOUT = 702, /** * This error indicates a kernel launch that uses an incompatible texturing * mode. */ CUDA_ERROR_LAUNCH_INCOMPATIBLE_TEXTURING = 703, /** * This error indicates that a call to ::cuCtxEnablePeerAccess() is * trying to re-enable peer access to a context which has already * had peer access to it enabled. */ CUDA_ERROR_PEER_ACCESS_ALREADY_ENABLED = 704, /** * This error indicates that ::cuCtxDisablePeerAccess() is * trying to disable peer access which has not been enabled yet * via ::cuCtxEnablePeerAccess(). */ CUDA_ERROR_PEER_ACCESS_NOT_ENABLED = 705, /** * This error indicates that the primary context for the specified device * has already been initialized. */ CUDA_ERROR_PRIMARY_CONTEXT_ACTIVE = 708, /** * This error indicates that the context current to the calling thread * has been destroyed using ::cuCtxDestroy, or is a primary context which * has not yet been initialized. */ CUDA_ERROR_CONTEXT_IS_DESTROYED = 709, /** * A device-side assert triggered during kernel execution. The context * cannot be used anymore, and must be destroyed. All existing device * memory allocations from this context are invalid and must be * reconstructed if the program is to continue using CUDA. */ CUDA_ERROR_ASSERT = 710, /** * This error indicates that the hardware resources required to enable * peer access have been exhausted for one or more of the devices * passed to ::cuCtxEnablePeerAccess(). */ CUDA_ERROR_TOO_MANY_PEERS = 711, /** * This error indicates that the memory range passed to ::cuMemHostRegister() * has already been registered. */ CUDA_ERROR_HOST_MEMORY_ALREADY_REGISTERED = 712, /** * This error indicates that the pointer passed to ::cuMemHostUnregister() * does not correspond to any currently registered memory region. */ CUDA_ERROR_HOST_MEMORY_NOT_REGISTERED = 713, /** * While executing a kernel, the device encountered a stack error. * This can be due to stack corruption or exceeding the stack size limit. * This leaves the process in an inconsistent state and any further CUDA work * will return the same error. To continue using CUDA, the process must be terminated * and relaunched. */ CUDA_ERROR_HARDWARE_STACK_ERROR = 714, /** * While executing a kernel, the device encountered an illegal instruction. * This leaves the process in an inconsistent state and any further CUDA work * will return the same error. To continue using CUDA, the process must be terminated * and relaunched. */ CUDA_ERROR_ILLEGAL_INSTRUCTION = 715, /** * While executing a kernel, the device encountered a load or store instruction * on a memory address which is not aligned. * This leaves the process in an inconsistent state and any further CUDA work * will return the same error. To continue using CUDA, the process must be terminated * and relaunched. */ CUDA_ERROR_MISALIGNED_ADDRESS = 716, /** * While executing a kernel, the device encountered an instruction * which can only operate on memory locations in certain address spaces * (global, shared, or local), but was supplied a memory address not * belonging to an allowed address space. * This leaves the process in an inconsistent state and any further CUDA work * will return the same error. To continue using CUDA, the process must be terminated * and relaunched. */ CUDA_ERROR_INVALID_ADDRESS_SPACE = 717, /** * While executing a kernel, the device program counter wrapped its address space. * This leaves the process in an inconsistent state and any further CUDA work * will return the same error. To continue using CUDA, the process must be terminated * and relaunched. */ CUDA_ERROR_INVALID_PC = 718, /** * An exception occurred on the device while executing a kernel. Common * causes include dereferencing an invalid device pointer and accessing * out of bounds shared memory. Less common cases can be system specific - more * information about these cases can be found in the system specific user guide. * This leaves the process in an inconsistent state and any further CUDA work * will return the same error. To continue using CUDA, the process must be terminated * and relaunched. */ CUDA_ERROR_LAUNCH_FAILED = 719, /** * This error indicates that the number of blocks launched per grid for a kernel that was * launched via either ::cuLaunchCooperativeKernel or ::cuLaunchCooperativeKernelMultiDevice * exceeds the maximum number of blocks as allowed by ::cuOccupancyMaxActiveBlocksPerMultiprocessor * or ::cuOccupancyMaxActiveBlocksPerMultiprocessorWithFlags times the number of multiprocessors * as specified by the device attribute ::CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT. */ CUDA_ERROR_COOPERATIVE_LAUNCH_TOO_LARGE = 720, /** * This error indicates that the attempted operation is not permitted. */ CUDA_ERROR_NOT_PERMITTED = 800, /** * This error indicates that the attempted operation is not supported * on the current system or device. */ CUDA_ERROR_NOT_SUPPORTED = 801, /** * This error indicates that the system is not yet ready to start any CUDA * work. To continue using CUDA, verify the system configuration is in a * valid state and all required driver daemons are actively running. * More information about this error can be found in the system specific * user guide. */ CUDA_ERROR_SYSTEM_NOT_READY = 802, /** * This error indicates that there is a mismatch between the versions of * the display driver and the CUDA driver. Refer to the compatibility documentation * for supported versions. */ CUDA_ERROR_SYSTEM_DRIVER_MISMATCH = 803, /** * This error indicates that the system was upgraded to run with forward compatibility * but the visible hardware detected by CUDA does not support this configuration. * Refer to the compatibility documentation for the supported hardware matrix or ensure * that only supported hardware is visible during initialization via the CUDA_VISIBLE_DEVICES * environment variable. */ CUDA_ERROR_COMPAT_NOT_SUPPORTED_ON_DEVICE = 804, /** * This error indicates that the operation is not permitted when * the stream is capturing. */ CUDA_ERROR_STREAM_CAPTURE_UNSUPPORTED = 900, /** * This error indicates that the current capture sequence on the stream * has been invalidated due to a previous error. */ CUDA_ERROR_STREAM_CAPTURE_INVALIDATED = 901, /** * This error indicates that the operation would have resulted in a merge * of two independent capture sequences. */ CUDA_ERROR_STREAM_CAPTURE_MERGE = 902, /** * This error indicates that the capture was not initiated in this stream. */ CUDA_ERROR_STREAM_CAPTURE_UNMATCHED = 903, /** * This error indicates that the capture sequence contains a fork that was * not joined to the primary stream. */ CUDA_ERROR_STREAM_CAPTURE_UNJOINED = 904, /** * This error indicates that a dependency would have been created which * crosses the capture sequence boundary. Only implicit in-stream ordering * dependencies are allowed to cross the boundary. */ CUDA_ERROR_STREAM_CAPTURE_ISOLATION = 905, /** * This error indicates a disallowed implicit dependency on a current capture * sequence from cudaStreamLegacy. */ CUDA_ERROR_STREAM_CAPTURE_IMPLICIT = 906, /** * This error indicates that the operation is not permitted on an event which * was last recorded in a capturing stream. */ CUDA_ERROR_CAPTURED_EVENT = 907, /** * A stream capture sequence not initiated with the ::CU_STREAM_CAPTURE_MODE_RELAXED * argument to ::cuStreamBeginCapture was passed to ::cuStreamEndCapture in a * different thread. */ CUDA_ERROR_STREAM_CAPTURE_WRONG_THREAD = 908, /** * This indicates that an unknown internal error has occurred. */ CUDA_ERROR_UNKNOWN = 999 } CUresult; /** * Online compiler and linker options */ typedef enum CUjit_option_enum { /** * Max number of registers that a thread may use.\n * Option type: unsigned int\n * Applies to: compiler only */ CU_JIT_MAX_REGISTERS = 0, /** * IN: Specifies minimum number of threads per block to target compilation * for\n * OUT: Returns the number of threads the compiler actually targeted. * This restricts the resource utilization fo the compiler (e.g. max * registers) such that a block with the given number of threads should be * able to launch based on register limitations. Note, this option does not * currently take into account any other resource limitations, such as * shared memory utilization.\n * Cannot be combined with ::CU_JIT_TARGET.\n * Option type: unsigned int\n * Applies to: compiler only */ CU_JIT_THREADS_PER_BLOCK, /** * Overwrites the option value with the total wall clock time, in * milliseconds, spent in the compiler and linker\n * Option type: float\n * Applies to: compiler and linker */ CU_JIT_WALL_TIME, /** * Pointer to a buffer in which to print any log messages * that are informational in nature (the buffer size is specified via * option ::CU_JIT_INFO_LOG_BUFFER_SIZE_BYTES)\n * Option type: char *\n * Applies to: compiler and linker */ CU_JIT_INFO_LOG_BUFFER, /** * IN: Log buffer size in bytes. Log messages will be capped at this size * (including null terminator)\n * OUT: Amount of log buffer filled with messages\n * Option type: unsigned int\n * Applies to: compiler and linker */ CU_JIT_INFO_LOG_BUFFER_SIZE_BYTES, /** * Pointer to a buffer in which to print any log messages that * reflect errors (the buffer size is specified via option * ::CU_JIT_ERROR_LOG_BUFFER_SIZE_BYTES)\n * Option type: char *\n * Applies to: compiler and linker */ CU_JIT_ERROR_LOG_BUFFER, /** * IN: Log buffer size in bytes. Log messages will be capped at this size * (including null terminator)\n * OUT: Amount of log buffer filled with messages\n * Option type: unsigned int\n * Applies to: compiler and linker */ CU_JIT_ERROR_LOG_BUFFER_SIZE_BYTES, /** * Level of optimizations to apply to generated code (0 - 4), with 4 * being the default and highest level of optimizations.\n * Option type: unsigned int\n * Applies to: compiler only */ CU_JIT_OPTIMIZATION_LEVEL, /** * No option value required. Determines the target based on the current * attached context (default)\n * Option type: No option value needed\n * Applies to: compiler and linker */ CU_JIT_TARGET_FROM_CUCONTEXT, /** * Target is chosen based on supplied ::CUjit_target. Cannot be * combined with ::CU_JIT_THREADS_PER_BLOCK.\n * Option type: unsigned int for enumerated type ::CUjit_target\n * Applies to: compiler and linker */ CU_JIT_TARGET, /** * Specifies choice of fallback strategy if matching cubin is not found. * Choice is based on supplied ::CUjit_fallback. This option cannot be * used with cuLink* APIs as the linker requires exact matches.\n * Option type: unsigned int for enumerated type ::CUjit_fallback\n * Applies to: compiler only */ CU_JIT_FALLBACK_STRATEGY, /** * Specifies whether to create debug information in output (-g) * (0: false, default)\n * Option type: int\n * Applies to: compiler and linker */ CU_JIT_GENERATE_DEBUG_INFO, /** * Generate verbose log messages (0: false, default)\n * Option type: int\n * Applies to: compiler and linker */ CU_JIT_LOG_VERBOSE, /** * Generate line number information (-lineinfo) (0: false, default)\n * Option type: int\n * Applies to: compiler only */ CU_JIT_GENERATE_LINE_INFO, /** * Specifies whether to enable caching explicitly (-dlcm) \n * Choice is based on supplied ::CUjit_cacheMode_enum.\n * Option type: unsigned int for enumerated type ::CUjit_cacheMode_enum\n * Applies to: compiler only */ CU_JIT_CACHE_MODE, /** * The below jit options are used for internal purposes only, in this version of CUDA */ CU_JIT_NEW_SM3X_OPT, CU_JIT_FAST_COMPILE, /** * Array of device symbol names that will be relocated to the corresponing * host addresses stored in ::CU_JIT_GLOBAL_SYMBOL_ADDRESSES.\n * Must contain ::CU_JIT_GLOBAL_SYMBOL_COUNT entries.\n * When loding a device module, driver will relocate all encountered * unresolved symbols to the host addresses.\n * It is only allowed to register symbols that correspond to unresolved * global variables.\n * It is illegal to register the same device symbol at multiple addresses.\n * Option type: const char **\n * Applies to: dynamic linker only */ CU_JIT_GLOBAL_SYMBOL_NAMES, /** * Array of host addresses that will be used to relocate corresponding * device symbols stored in ::CU_JIT_GLOBAL_SYMBOL_NAMES.\n * Must contain ::CU_JIT_GLOBAL_SYMBOL_COUNT entries.\n * Option type: void **\n * Applies to: dynamic linker only */ CU_JIT_GLOBAL_SYMBOL_ADDRESSES, /** * Number of entries in ::CU_JIT_GLOBAL_SYMBOL_NAMES and * ::CU_JIT_GLOBAL_SYMBOL_ADDRESSES arrays.\n * Option type: unsigned int\n * Applies to: dynamic linker only */ CU_JIT_GLOBAL_SYMBOL_COUNT, CU_JIT_NUM_OPTIONS } CUjit_option; /** * Device properties */ typedef enum CUdevice_attribute_enum { CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_BLOCK = 1, /**< Maximum number of threads per block */ CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_X = 2, /**< Maximum block dimension X */ CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Y = 3, /**< Maximum block dimension Y */ CU_DEVICE_ATTRIBUTE_MAX_BLOCK_DIM_Z = 4, /**< Maximum block dimension Z */ CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_X = 5, /**< Maximum grid dimension X */ CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Y = 6, /**< Maximum grid dimension Y */ CU_DEVICE_ATTRIBUTE_MAX_GRID_DIM_Z = 7, /**< Maximum grid dimension Z */ CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK = 8, /**< Maximum shared memory available per block in bytes */ CU_DEVICE_ATTRIBUTE_SHARED_MEMORY_PER_BLOCK = 8, /**< Deprecated, use CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK */ CU_DEVICE_ATTRIBUTE_TOTAL_CONSTANT_MEMORY = 9, /**< Memory available on device for __constant__ variables in a CUDA C kernel in bytes */ CU_DEVICE_ATTRIBUTE_WARP_SIZE = 10, /**< Warp size in threads */ CU_DEVICE_ATTRIBUTE_MAX_PITCH = 11, /**< Maximum pitch in bytes allowed by memory copies */ CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_BLOCK = 12, /**< Maximum number of 32-bit registers available per block */ CU_DEVICE_ATTRIBUTE_REGISTERS_PER_BLOCK = 12, /**< Deprecated, use CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_BLOCK */ CU_DEVICE_ATTRIBUTE_CLOCK_RATE = 13, /**< Typical clock frequency in kilohertz */ CU_DEVICE_ATTRIBUTE_TEXTURE_ALIGNMENT = 14, /**< Alignment requirement for textures */ CU_DEVICE_ATTRIBUTE_GPU_OVERLAP = 15, /**< Device can possibly copy memory and execute a kernel concurrently. Deprecated. Use instead CU_DEVICE_ATTRIBUTE_ASYNC_ENGINE_COUNT. */ CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT = 16, /**< Number of multiprocessors on device */ CU_DEVICE_ATTRIBUTE_KERNEL_EXEC_TIMEOUT = 17, /**< Specifies whether there is a run time limit on kernels */ CU_DEVICE_ATTRIBUTE_INTEGRATED = 18, /**< Device is integrated with host memory */ CU_DEVICE_ATTRIBUTE_CAN_MAP_HOST_MEMORY = 19, /**< Device can map host memory into CUDA address space */ CU_DEVICE_ATTRIBUTE_COMPUTE_MODE = 20, /**< Compute mode (See ::CUcomputemode for details) */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_WIDTH = 21, /**< Maximum 1D texture width */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_WIDTH = 22, /**< Maximum 2D texture width */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_HEIGHT = 23, /**< Maximum 2D texture height */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_WIDTH = 24, /**< Maximum 3D texture width */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_HEIGHT = 25, /**< Maximum 3D texture height */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_DEPTH = 26, /**< Maximum 3D texture depth */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LAYERED_WIDTH = 27, /**< Maximum 2D layered texture width */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LAYERED_HEIGHT = 28, /**< Maximum 2D layered texture height */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LAYERED_LAYERS = 29, /**< Maximum layers in a 2D layered texture */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_ARRAY_WIDTH = 27, /**< Deprecated, use CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LAYERED_WIDTH */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_ARRAY_HEIGHT = 28, /**< Deprecated, use CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LAYERED_HEIGHT */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_ARRAY_NUMSLICES = 29, /**< Deprecated, use CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LAYERED_LAYERS */ CU_DEVICE_ATTRIBUTE_SURFACE_ALIGNMENT = 30, /**< Alignment requirement for surfaces */ CU_DEVICE_ATTRIBUTE_CONCURRENT_KERNELS = 31, /**< Device can possibly execute multiple kernels concurrently */ CU_DEVICE_ATTRIBUTE_ECC_ENABLED = 32, /**< Device has ECC support enabled */ CU_DEVICE_ATTRIBUTE_PCI_BUS_ID = 33, /**< PCI bus ID of the device */ CU_DEVICE_ATTRIBUTE_PCI_DEVICE_ID = 34, /**< PCI device ID of the device */ CU_DEVICE_ATTRIBUTE_TCC_DRIVER = 35, /**< Device is using TCC driver model */ CU_DEVICE_ATTRIBUTE_MEMORY_CLOCK_RATE = 36, /**< Peak memory clock frequency in kilohertz */ CU_DEVICE_ATTRIBUTE_GLOBAL_MEMORY_BUS_WIDTH = 37, /**< Global memory bus width in bits */ CU_DEVICE_ATTRIBUTE_L2_CACHE_SIZE = 38, /**< Size of L2 cache in bytes */ CU_DEVICE_ATTRIBUTE_MAX_THREADS_PER_MULTIPROCESSOR = 39, /**< Maximum resident threads per multiprocessor */ CU_DEVICE_ATTRIBUTE_ASYNC_ENGINE_COUNT = 40, /**< Number of asynchronous engines */ CU_DEVICE_ATTRIBUTE_UNIFIED_ADDRESSING = 41, /**< Device shares a unified address space with the host */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_LAYERED_WIDTH = 42, /**< Maximum 1D layered texture width */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_LAYERED_LAYERS = 43, /**< Maximum layers in a 1D layered texture */ CU_DEVICE_ATTRIBUTE_CAN_TEX2D_GATHER = 44, /**< Deprecated, do not use. */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_GATHER_WIDTH = 45, /**< Maximum 2D texture width if CUDA_ARRAY3D_TEXTURE_GATHER is set */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_GATHER_HEIGHT = 46, /**< Maximum 2D texture height if CUDA_ARRAY3D_TEXTURE_GATHER is set */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_WIDTH_ALTERNATE = 47, /**< Alternate maximum 3D texture width */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_HEIGHT_ALTERNATE = 48,/**< Alternate maximum 3D texture height */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE3D_DEPTH_ALTERNATE = 49, /**< Alternate maximum 3D texture depth */ CU_DEVICE_ATTRIBUTE_PCI_DOMAIN_ID = 50, /**< PCI domain ID of the device */ CU_DEVICE_ATTRIBUTE_TEXTURE_PITCH_ALIGNMENT = 51, /**< Pitch alignment requirement for textures */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURECUBEMAP_WIDTH = 52, /**< Maximum cubemap texture width/height */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURECUBEMAP_LAYERED_WIDTH = 53, /**< Maximum cubemap layered texture width/height */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURECUBEMAP_LAYERED_LAYERS = 54, /**< Maximum layers in a cubemap layered texture */ CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE1D_WIDTH = 55, /**< Maximum 1D surface width */ CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_WIDTH = 56, /**< Maximum 2D surface width */ CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_HEIGHT = 57, /**< Maximum 2D surface height */ CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE3D_WIDTH = 58, /**< Maximum 3D surface width */ CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE3D_HEIGHT = 59, /**< Maximum 3D surface height */ CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE3D_DEPTH = 60, /**< Maximum 3D surface depth */ CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE1D_LAYERED_WIDTH = 61, /**< Maximum 1D layered surface width */ CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE1D_LAYERED_LAYERS = 62, /**< Maximum layers in a 1D layered surface */ CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_LAYERED_WIDTH = 63, /**< Maximum 2D layered surface width */ CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_LAYERED_HEIGHT = 64, /**< Maximum 2D layered surface height */ CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACE2D_LAYERED_LAYERS = 65, /**< Maximum layers in a 2D layered surface */ CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACECUBEMAP_WIDTH = 66, /**< Maximum cubemap surface width */ CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACECUBEMAP_LAYERED_WIDTH = 67, /**< Maximum cubemap layered surface width */ CU_DEVICE_ATTRIBUTE_MAXIMUM_SURFACECUBEMAP_LAYERED_LAYERS = 68, /**< Maximum layers in a cubemap layered surface */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_LINEAR_WIDTH = 69, /**< Maximum 1D linear texture width */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LINEAR_WIDTH = 70, /**< Maximum 2D linear texture width */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LINEAR_HEIGHT = 71, /**< Maximum 2D linear texture height */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_LINEAR_PITCH = 72, /**< Maximum 2D linear texture pitch in bytes */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_MIPMAPPED_WIDTH = 73, /**< Maximum mipmapped 2D texture width */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE2D_MIPMAPPED_HEIGHT = 74,/**< Maximum mipmapped 2D texture height */ CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR = 75, /**< Major compute capability version number */ CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR = 76, /**< Minor compute capability version number */ CU_DEVICE_ATTRIBUTE_MAXIMUM_TEXTURE1D_MIPMAPPED_WIDTH = 77, /**< Maximum mipmapped 1D texture width */ CU_DEVICE_ATTRIBUTE_STREAM_PRIORITIES_SUPPORTED = 78, /**< Device supports stream priorities */ CU_DEVICE_ATTRIBUTE_GLOBAL_L1_CACHE_SUPPORTED = 79, /**< Device supports caching globals in L1 */ CU_DEVICE_ATTRIBUTE_LOCAL_L1_CACHE_SUPPORTED = 80, /**< Device supports caching locals in L1 */ CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_MULTIPROCESSOR = 81, /**< Maximum shared memory available per multiprocessor in bytes */ CU_DEVICE_ATTRIBUTE_MAX_REGISTERS_PER_MULTIPROCESSOR = 82, /**< Maximum number of 32-bit registers available per multiprocessor */ CU_DEVICE_ATTRIBUTE_MANAGED_MEMORY = 83, /**< Device can allocate managed memory on this system */ CU_DEVICE_ATTRIBUTE_MULTI_GPU_BOARD = 84, /**< Device is on a multi-GPU board */ CU_DEVICE_ATTRIBUTE_MULTI_GPU_BOARD_GROUP_ID = 85, /**< Unique id for a group of devices on the same multi-GPU board */ CU_DEVICE_ATTRIBUTE_HOST_NATIVE_ATOMIC_SUPPORTED = 86, /**< Link between the device and the host supports native atomic operations (this is a placeholder attribute, and is not supported on any current hardware)*/ CU_DEVICE_ATTRIBUTE_SINGLE_TO_DOUBLE_PRECISION_PERF_RATIO = 87, /**< Ratio of single precision performance (in floating-point operations per second) to double precision performance */ CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS = 88, /**< Device supports coherently accessing pageable memory without calling cudaHostRegister on it */ CU_DEVICE_ATTRIBUTE_CONCURRENT_MANAGED_ACCESS = 89, /**< Device can coherently access managed memory concurrently with the CPU */ CU_DEVICE_ATTRIBUTE_COMPUTE_PREEMPTION_SUPPORTED = 90, /**< Device supports compute preemption. */ CU_DEVICE_ATTRIBUTE_CAN_USE_HOST_POINTER_FOR_REGISTERED_MEM = 91, /**< Device can access host registered memory at the same virtual address as the CPU */ CU_DEVICE_ATTRIBUTE_CAN_USE_STREAM_MEM_OPS = 92, /**< ::cuStreamBatchMemOp and related APIs are supported. */ CU_DEVICE_ATTRIBUTE_CAN_USE_64_BIT_STREAM_MEM_OPS = 93, /**< 64-bit operations are supported in ::cuStreamBatchMemOp and related APIs. */ CU_DEVICE_ATTRIBUTE_CAN_USE_STREAM_WAIT_VALUE_NOR = 94, /**< ::CU_STREAM_WAIT_VALUE_NOR is supported. */ CU_DEVICE_ATTRIBUTE_COOPERATIVE_LAUNCH = 95, /**< Device supports launching cooperative kernels via ::cuLaunchCooperativeKernel */ CU_DEVICE_ATTRIBUTE_COOPERATIVE_MULTI_DEVICE_LAUNCH = 96, /**< Device can participate in cooperative kernels launched via ::cuLaunchCooperativeKernelMultiDevice */ CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_BLOCK_OPTIN = 97, /**< Maximum optin shared memory per block */ CU_DEVICE_ATTRIBUTE_CAN_FLUSH_REMOTE_WRITES = 98, /**< Both the ::CU_STREAM_WAIT_VALUE_FLUSH flag and the ::CU_STREAM_MEM_OP_FLUSH_REMOTE_WRITES MemOp are supported on the device. See \ref CUDA_MEMOP for additional details. */ CU_DEVICE_ATTRIBUTE_HOST_REGISTER_SUPPORTED = 99, /**< Device supports host memory registration via ::cudaHostRegister. */ CU_DEVICE_ATTRIBUTE_PAGEABLE_MEMORY_ACCESS_USES_HOST_PAGE_TABLES = 100, /**< Device accesses pageable memory via the host's page tables. */ CU_DEVICE_ATTRIBUTE_DIRECT_MANAGED_MEM_ACCESS_FROM_HOST = 101, /**< The host can directly access managed memory on the device without migration. */ CU_DEVICE_ATTRIBUTE_MAX } CUdevice_attribute; /** * Function cache configurations */ typedef enum CUfunc_cache_enum { CU_FUNC_CACHE_PREFER_NONE = 0x00, /**< no preference for shared memory or L1 (default) */ CU_FUNC_CACHE_PREFER_SHARED = 0x01, /**< prefer larger shared memory and smaller L1 cache */ CU_FUNC_CACHE_PREFER_L1 = 0x02, /**< prefer larger L1 cache and smaller shared memory */ CU_FUNC_CACHE_PREFER_EQUAL = 0x03 /**< prefer equal sized L1 cache and shared memory */ } CUfunc_cache; /** * Shared memory configurations */ typedef enum CUsharedconfig_enum { CU_SHARED_MEM_CONFIG_DEFAULT_BANK_SIZE = 0x00, /**< set default shared memory bank size */ CU_SHARED_MEM_CONFIG_FOUR_BYTE_BANK_SIZE = 0x01, /**< set shared memory bank width to four bytes */ CU_SHARED_MEM_CONFIG_EIGHT_BYTE_BANK_SIZE = 0x02 /**< set shared memory bank width to eight bytes */ } CUsharedconfig; /** * Function properties */ typedef enum CUfunction_attribute_enum { /** * The maximum number of threads per block, beyond which a launch of the * function would fail. This number depends on both the function and the * device on which the function is currently loaded. */ CU_FUNC_ATTRIBUTE_MAX_THREADS_PER_BLOCK = 0, /** * The size in bytes of statically-allocated shared memory required by * this function. This does not include dynamically-allocated shared * memory requested by the user at runtime. */ CU_FUNC_ATTRIBUTE_SHARED_SIZE_BYTES = 1, /** * The size in bytes of user-allocated constant memory required by this * function. */ CU_FUNC_ATTRIBUTE_CONST_SIZE_BYTES = 2, /** * The size in bytes of local memory used by each thread of this function. */ CU_FUNC_ATTRIBUTE_LOCAL_SIZE_BYTES = 3, /** * The number of registers used by each thread of this function. */ CU_FUNC_ATTRIBUTE_NUM_REGS = 4, /** * The PTX virtual architecture version for which the function was * compiled. This value is the major PTX version * 10 + the minor PTX * version, so a PTX version 1.3 function would return the value 13. * Note that this may return the undefined value of 0 for cubins * compiled prior to CUDA 3.0. */ CU_FUNC_ATTRIBUTE_PTX_VERSION = 5, /** * The binary architecture version for which the function was compiled. * This value is the major binary version * 10 + the minor binary version, * so a binary version 1.3 function would return the value 13. Note that * this will return a value of 10 for legacy cubins that do not have a * properly-encoded binary architecture version. */ CU_FUNC_ATTRIBUTE_BINARY_VERSION = 6, /** * The attribute to indicate whether the function has been compiled with * user specified option "-Xptxas --dlcm=ca" set . */ CU_FUNC_ATTRIBUTE_CACHE_MODE_CA = 7, /** * The maximum size in bytes of dynamically-allocated shared memory that can be used by * this function. If the user-specified dynamic shared memory size is larger than this * value, the launch will fail. * See ::cuFuncSetAttribute */ CU_FUNC_ATTRIBUTE_MAX_DYNAMIC_SHARED_SIZE_BYTES = 8, /** * 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. * Refer to ::CU_DEVICE_ATTRIBUTE_MAX_SHARED_MEMORY_PER_MULTIPROCESSOR. * This is only a hint, and the driver can choose a different ratio if required to execute the function. * See ::cuFuncSetAttribute */ CU_FUNC_ATTRIBUTE_PREFERRED_SHARED_MEMORY_CARVEOUT = 9, CU_FUNC_ATTRIBUTE_MAX } CUfunction_attribute; /** * Context creation flags */ typedef enum CUctx_flags_enum { CU_CTX_SCHED_AUTO = 0x00, /**< Automatic scheduling */ CU_CTX_SCHED_SPIN = 0x01, /**< Set spin as default scheduling */ CU_CTX_SCHED_YIELD = 0x02, /**< Set yield as default scheduling */ CU_CTX_SCHED_BLOCKING_SYNC = 0x04, /**< Set blocking synchronization as default scheduling */ CU_CTX_BLOCKING_SYNC = 0x04, /**< Set blocking synchronization as default scheduling * \deprecated This flag was deprecated as of CUDA 4.0 * and was replaced with ::CU_CTX_SCHED_BLOCKING_SYNC. */ CU_CTX_SCHED_MASK = 0x07, CU_CTX_MAP_HOST = 0x08, /**< Support mapped pinned allocations */ CU_CTX_LMEM_RESIZE_TO_MAX = 0x10, /**< Keep local memory allocation after launch */ CU_CTX_FLAGS_MASK = 0x1f } CUctx_flags; #ifdef _WIN32 #define CUDAAPI __stdcall #else #define CUDAAPI #endif #define CUDA_API_CALL CUDAAPI typedef CUresult (CUDA_API_CALL *CUDA_CUCTXCREATE) (CUcontext *, unsigned int, CUdevice); typedef CUresult (CUDA_API_CALL *CUDA_CUCTXDESTROY) (CUcontext); typedef CUresult (CUDA_API_CALL *CUDA_CUCTXGETCACHECONFIG) (CUfunc_cache *); typedef CUresult (CUDA_API_CALL *CUDA_CUCTXGETCURRENT) (CUcontext *); typedef CUresult (CUDA_API_CALL *CUDA_CUCTXGETSHAREDMEMCONFIG) (CUsharedconfig *); typedef CUresult (CUDA_API_CALL *CUDA_CUCTXPOPCURRENT) (CUcontext *); typedef CUresult (CUDA_API_CALL *CUDA_CUCTXPUSHCURRENT) (CUcontext); typedef CUresult (CUDA_API_CALL *CUDA_CUCTXSETCACHECONFIG) (CUfunc_cache); typedef CUresult (CUDA_API_CALL *CUDA_CUCTXSETCURRENT) (CUcontext); typedef CUresult (CUDA_API_CALL *CUDA_CUCTXSETSHAREDMEMCONFIG) (CUsharedconfig); typedef CUresult (CUDA_API_CALL *CUDA_CUCTXSYNCHRONIZE) (); typedef CUresult (CUDA_API_CALL *CUDA_CUDEVICEGETATTRIBUTE) (int *, CUdevice_attribute, CUdevice); typedef CUresult (CUDA_API_CALL *CUDA_CUDEVICEGETCOUNT) (int *); typedef CUresult (CUDA_API_CALL *CUDA_CUDEVICEGET) (CUdevice *, int); typedef CUresult (CUDA_API_CALL *CUDA_CUDEVICEGETNAME) (char *, int, CUdevice); typedef CUresult (CUDA_API_CALL *CUDA_CUDEVICETOTALMEM) (size_t *, CUdevice); typedef CUresult (CUDA_API_CALL *CUDA_CUDRIVERGETVERSION) (int *); typedef CUresult (CUDA_API_CALL *CUDA_CUEVENTCREATE) (CUevent *, unsigned int); typedef CUresult (CUDA_API_CALL *CUDA_CUEVENTDESTROY) (CUevent); typedef CUresult (CUDA_API_CALL *CUDA_CUEVENTELAPSEDTIME) (float *, CUevent, CUevent); typedef CUresult (CUDA_API_CALL *CUDA_CUEVENTQUERY) (CUevent); typedef CUresult (CUDA_API_CALL *CUDA_CUEVENTRECORD) (CUevent, CUstream); typedef CUresult (CUDA_API_CALL *CUDA_CUEVENTSYNCHRONIZE) (CUevent); typedef CUresult (CUDA_API_CALL *CUDA_CUFUNCGETATTRIBUTE) (int *, CUfunction_attribute, CUfunction); typedef CUresult (CUDA_API_CALL *CUDA_CUFUNCSETATTRIBUTE) (CUfunction, CUfunction_attribute, int); typedef CUresult (CUDA_API_CALL *CUDA_CUFUNCSETCACHECONFIG) (CUfunction, CUfunc_cache); typedef CUresult (CUDA_API_CALL *CUDA_CUFUNCSETSHAREDMEMCONFIG) (CUfunction, CUsharedconfig); typedef CUresult (CUDA_API_CALL *CUDA_CUGETERRORNAME) (CUresult, const char **); typedef CUresult (CUDA_API_CALL *CUDA_CUGETERRORSTRING) (CUresult, const char **); typedef CUresult (CUDA_API_CALL *CUDA_CUINIT) (unsigned int); typedef CUresult (CUDA_API_CALL *CUDA_CULAUNCHKERNEL) (CUfunction, unsigned int, unsigned int, unsigned int, unsigned int, unsigned int, unsigned int, unsigned int, CUstream, void **, void **); typedef CUresult (CUDA_API_CALL *CUDA_CUMEMALLOC) (CUdeviceptr *, size_t); typedef CUresult (CUDA_API_CALL *CUDA_CUMEMALLOCHOST) (void **, size_t); typedef CUresult (CUDA_API_CALL *CUDA_CUMEMCPYDTOD) (CUdeviceptr, CUdeviceptr, size_t); typedef CUresult (CUDA_API_CALL *CUDA_CUMEMCPYDTOH) (void *, CUdeviceptr, size_t); typedef CUresult (CUDA_API_CALL *CUDA_CUMEMCPYHTOD) (CUdeviceptr, const void *, size_t); typedef CUresult (CUDA_API_CALL *CUDA_CUMEMFREE) (CUdeviceptr); typedef CUresult (CUDA_API_CALL *CUDA_CUMEMFREEHOST) (void *); typedef CUresult (CUDA_API_CALL *CUDA_CUMEMGETINFO) (size_t *, size_t *); typedef CUresult (CUDA_API_CALL *CUDA_CUMEMSETD32) (CUdeviceptr, unsigned int, size_t); typedef CUresult (CUDA_API_CALL *CUDA_CUMEMSETD8) (CUdeviceptr, unsigned char, size_t); typedef CUresult (CUDA_API_CALL *CUDA_CUMODULEGETFUNCTION) (CUfunction *, CUmodule, const char *); typedef CUresult (CUDA_API_CALL *CUDA_CUMODULEGETGLOBAL) (CUdeviceptr *, size_t *, CUmodule, const char *); typedef CUresult (CUDA_API_CALL *CUDA_CUMODULELOAD) (CUmodule *, const char *); typedef CUresult (CUDA_API_CALL *CUDA_CUMODULELOADDATA) (CUmodule *, const void *); typedef CUresult (CUDA_API_CALL *CUDA_CUMODULELOADDATAEX) (CUmodule *, const void *, unsigned int, CUjit_option *, void **); typedef CUresult (CUDA_API_CALL *CUDA_CUMODULEUNLOAD) (CUmodule); typedef CUresult (CUDA_API_CALL *CUDA_CUPROFILERSTART) (); typedef CUresult (CUDA_API_CALL *CUDA_CUPROFILERSTOP) (); typedef CUresult (CUDA_API_CALL *CUDA_CUSTREAMCREATE) (CUstream *, unsigned int); typedef CUresult (CUDA_API_CALL *CUDA_CUSTREAMDESTROY) (CUstream); typedef CUresult (CUDA_API_CALL *CUDA_CUSTREAMSYNCHRONIZE) (CUstream); typedef CUresult (CUDA_API_CALL *CUDA_CUSTREAMWAITEVENT) (CUstream, CUevent, unsigned int); typedef struct hc_cuda_lib { hc_dynlib_t lib; CUDA_CUCTXCREATE cuCtxCreate; CUDA_CUCTXDESTROY cuCtxDestroy; CUDA_CUCTXGETCACHECONFIG cuCtxGetCacheConfig; CUDA_CUCTXGETCURRENT cuCtxGetCurrent; CUDA_CUCTXGETSHAREDMEMCONFIG cuCtxGetSharedMemConfig; CUDA_CUCTXPOPCURRENT cuCtxPopCurrent; CUDA_CUCTXPUSHCURRENT cuCtxPushCurrent; CUDA_CUCTXSETCURRENT cuCtxSetCurrent; CUDA_CUCTXSETSHAREDMEMCONFIG cuCtxSetSharedMemConfig; CUDA_CUCTXSYNCHRONIZE cuCtxSynchronize; CUDA_CUDEVICEGETATTRIBUTE cuDeviceGetAttribute; CUDA_CUDEVICEGETCOUNT cuDeviceGetCount; CUDA_CUDEVICEGET cuDeviceGet; CUDA_CUDEVICEGETNAME cuDeviceGetName; CUDA_CUDEVICETOTALMEM cuDeviceTotalMem; CUDA_CUDRIVERGETVERSION cuDriverGetVersion; CUDA_CUEVENTCREATE cuEventCreate; CUDA_CUEVENTDESTROY cuEventDestroy; CUDA_CUEVENTELAPSEDTIME cuEventElapsedTime; CUDA_CUEVENTQUERY cuEventQuery; CUDA_CUEVENTRECORD cuEventRecord; CUDA_CUEVENTSYNCHRONIZE cuEventSynchronize; CUDA_CUFUNCGETATTRIBUTE cuFuncGetAttribute; CUDA_CUFUNCSETATTRIBUTE cuFuncSetAttribute; CUDA_CUFUNCSETCACHECONFIG cuFuncSetCacheConfig; CUDA_CUFUNCSETSHAREDMEMCONFIG cuFuncSetSharedMemConfig; CUDA_CUGETERRORNAME cuGetErrorName; CUDA_CUGETERRORSTRING cuGetErrorString; CUDA_CUINIT cuInit; CUDA_CULAUNCHKERNEL cuLaunchKernel; CUDA_CUMEMALLOC cuMemAlloc; CUDA_CUMEMALLOCHOST cuMemAllocHost; CUDA_CUMEMCPYDTOD cuMemcpyDtoD; CUDA_CUMEMCPYDTOH cuMemcpyDtoH; CUDA_CUMEMCPYHTOD cuMemcpyHtoD; CUDA_CUMEMFREE cuMemFree; CUDA_CUMEMFREEHOST cuMemFreeHost; CUDA_CUMEMGETINFO cuMemGetInfo; CUDA_CUMEMSETD32 cuMemsetD32; CUDA_CUMEMSETD8 cuMemsetD8; CUDA_CUMODULEGETFUNCTION cuModuleGetFunction; CUDA_CUMODULEGETGLOBAL cuModuleGetGlobal; CUDA_CUMODULELOAD cuModuleLoad; CUDA_CUMODULELOADDATA cuModuleLoadData; CUDA_CUMODULELOADDATAEX cuModuleLoadDataEx; CUDA_CUMODULEUNLOAD cuModuleUnload; CUDA_CUPROFILERSTART cuProfilerStart; CUDA_CUPROFILERSTOP cuProfilerStop; CUDA_CUSTREAMCREATE cuStreamCreate; CUDA_CUSTREAMDESTROY cuStreamDestroy; CUDA_CUSTREAMSYNCHRONIZE cuStreamSynchronize; CUDA_CUSTREAMWAITEVENT cuStreamWaitEvent; } hc_cuda_lib_t; typedef hc_cuda_lib_t CUDA_PTR; #endif // _EXT_CUDA_H