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hashcat/include/ext_cuda.h

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/**
* Author......: See docs/credits.txt
* License.....: MIT
*/
#ifndef HC_EXT_CUDA_H
#define HC_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 struct CUlinkState_st *CUlinkState;
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;
/**
* Stream creation flags
*/
typedef enum CUstream_flags_enum
{
CU_STREAM_DEFAULT = 0x0, /**< Default stream flag */
CU_STREAM_NON_BLOCKING = 0x1 /**< Stream does not synchronize with stream 0 (the NULL stream) */
} CUstream_flags;
/**
* Event creation flags
*/
typedef enum CUevent_flags_enum
{
CU_EVENT_DEFAULT = 0x0, /**< Default event flag */
CU_EVENT_BLOCKING_SYNC = 0x1, /**< Event uses blocking synchronization */
CU_EVENT_DISABLE_TIMING = 0x2, /**< Event will not record timing data */
CU_EVENT_INTERPROCESS = 0x4 /**< Event is suitable for interprocess use. CU_EVENT_DISABLE_TIMING must be set */
} CUevent_flags;
typedef enum CUjitInputType_enum
{
/**
* Compiled device-class-specific device code\n
* Applicable options: none
*/
CU_JIT_INPUT_CUBIN = 0,
/**
* PTX source code\n
* Applicable options: PTX compiler options
*/
CU_JIT_INPUT_PTX,
/**
* Bundle of multiple cubins and/or PTX of some device code\n
* Applicable options: PTX compiler options, ::CU_JIT_FALLBACK_STRATEGY
*/
CU_JIT_INPUT_FATBINARY,
/**
* Host object with embedded device code\n
* Applicable options: PTX compiler options, ::CU_JIT_FALLBACK_STRATEGY
*/
CU_JIT_INPUT_OBJECT,
/**
* Archive of host objects with embedded device code\n
* Applicable options: PTX compiler options, ::CU_JIT_FALLBACK_STRATEGY
*/
CU_JIT_INPUT_LIBRARY,
CU_JIT_NUM_INPUT_TYPES
} CUjitInputType;
#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_CUMEMCPYDTODASYNC) (CUdeviceptr, CUdeviceptr, size_t, CUstream);
typedef CUresult (CUDA_API_CALL *CUDA_CUMEMCPYDTOHASYNC) (void *, CUdeviceptr, size_t, CUstream);
typedef CUresult (CUDA_API_CALL *CUDA_CUMEMCPYHTODASYNC) (CUdeviceptr, const void *, size_t, CUstream);
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_CUMEMSETD32ASYNC) (CUdeviceptr, unsigned int, size_t, CUstream);
typedef CUresult (CUDA_API_CALL *CUDA_CUMEMSETD8ASYNC) (CUdeviceptr, unsigned char, size_t, CUstream);
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 CUresult (CUDA_API_CALL *CUDA_CULINKCREATE) (unsigned int, CUjit_option *, void **, CUlinkState *);
typedef CUresult (CUDA_API_CALL *CUDA_CULINKADDDATA) (CUlinkState, CUjitInputType, void *, size_t, const char *, unsigned int, CUjit_option *, void **);
typedef CUresult (CUDA_API_CALL *CUDA_CULINKDESTROY) (CUlinkState);
typedef CUresult (CUDA_API_CALL *CUDA_CULINKCOMPLETE) (CUlinkState, void **, size_t *);
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_CUCTXSETCACHECONFIG cuCtxSetCacheConfig;
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_CUMEMCPYDTODASYNC cuMemcpyDtoDAsync;
CUDA_CUMEMCPYDTOHASYNC cuMemcpyDtoHAsync;
CUDA_CUMEMCPYHTODASYNC cuMemcpyHtoDAsync;
CUDA_CUMEMFREE cuMemFree;
CUDA_CUMEMFREEHOST cuMemFreeHost;
CUDA_CUMEMGETINFO cuMemGetInfo;
CUDA_CUMEMSETD32ASYNC cuMemsetD32Async;
CUDA_CUMEMSETD8ASYNC cuMemsetD8Async;
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;
CUDA_CULINKCREATE cuLinkCreate;
CUDA_CULINKADDDATA cuLinkAddData;
CUDA_CULINKDESTROY cuLinkDestroy;
CUDA_CULINKCOMPLETE cuLinkComplete;
} hc_cuda_lib_t;
typedef hc_cuda_lib_t CUDA_PTR;
int cuda_init (void *hashcat_ctx);
void cuda_close (void *hashcat_ctx);
int hc_cuCtxCreate (void *hashcat_ctx, CUcontext *pctx, unsigned int flags, CUdevice dev);
int hc_cuCtxDestroy (void *hashcat_ctx, CUcontext ctx);
int hc_cuCtxSetCurrent (void *hashcat_ctx, CUcontext ctx);
int hc_cuCtxSetCacheConfig (void *hashcat_ctx, CUfunc_cache config);
int hc_cuCtxSynchronize (void *hashcat_ctx);
int hc_cuDeviceGetAttribute (void *hashcat_ctx, int *pi, CUdevice_attribute attrib, CUdevice dev);
int hc_cuDeviceGetCount (void *hashcat_ctx, int *count);
int hc_cuDeviceGet (void *hashcat_ctx, CUdevice *device, int ordinal);
int hc_cuDeviceGetName (void *hashcat_ctx, char *name, int len, CUdevice dev);
int hc_cuDeviceTotalMem (void *hashcat_ctx, size_t *bytes, CUdevice dev);
int hc_cuDriverGetVersion (void *hashcat_ctx, int *driverVersion);
int hc_cuEventCreate (void *hashcat_ctx, CUevent *phEvent, unsigned int Flags);
int hc_cuEventDestroy (void *hashcat_ctx, CUevent hEvent);
int hc_cuEventElapsedTime (void *hashcat_ctx, float *pMilliseconds, CUevent hStart, CUevent hEnd);
int hc_cuEventQuery (void *hashcat_ctx, CUevent hEvent);
int hc_cuEventRecord (void *hashcat_ctx, CUevent hEvent, CUstream hStream);
int hc_cuEventSynchronize (void *hashcat_ctx, CUevent hEvent);
int hc_cuFuncGetAttribute (void *hashcat_ctx, int *pi, CUfunction_attribute attrib, CUfunction hfunc);
int hc_cuFuncSetAttribute (void *hashcat_ctx, CUfunction hfunc, CUfunction_attribute attrib, int value);
int hc_cuInit (void *hashcat_ctx, unsigned int Flags);
int hc_cuLaunchKernel (void *hashcat_ctx, CUfunction f, unsigned int gridDimX, unsigned int gridDimY, unsigned int gridDimZ, unsigned int blockDimX, unsigned int blockDimY, unsigned int blockDimZ, unsigned int sharedMemBytes, CUstream hStream, void **kernelParams, void **extra);
int hc_cuMemAlloc (void *hashcat_ctx, CUdeviceptr *dptr, size_t bytesize);
int hc_cuMemcpyDtoDAsync (void *hashcat_ctx, CUdeviceptr dstDevice, CUdeviceptr srcDevice, size_t ByteCount, CUstream hStream);
int hc_cuMemcpyDtoHAsync (void *hashcat_ctx, void *dstHost, CUdeviceptr srcDevice, size_t ByteCount, CUstream hStream);
int hc_cuMemcpyHtoDAsync (void *hashcat_ctx, CUdeviceptr dstDevice, const void *srcHost, size_t ByteCount, CUstream hStream);
int hc_cuMemFree (void *hashcat_ctx, CUdeviceptr dptr);
int hc_cuMemGetInfo (void *hashcat_ctx, size_t *free, size_t *total);
int hc_cuMemsetD32Async (void *hashcat_ctx, CUdeviceptr dstDevice, unsigned int ui, size_t N, CUstream hStream);
int hc_cuMemsetD8Async (void *hashcat_ctx, CUdeviceptr dstDevice, unsigned char uc, size_t N, CUstream hStream);
int hc_cuModuleGetFunction (void *hashcat_ctx, CUfunction *hfunc, CUmodule hmod, const char *name);
int hc_cuModuleGetGlobal (void *hashcat_ctx, CUdeviceptr *dptr, size_t *bytes, CUmodule hmod, const char *name);
int hc_cuModuleLoadDataEx (void *hashcat_ctx, CUmodule *module, const void *image, unsigned int numOptions, CUjit_option *options, void **optionValues);
int hc_cuModuleUnload (void *hashcat_ctx, CUmodule hmod);
int hc_cuStreamCreate (void *hashcat_ctx, CUstream *phStream, unsigned int Flags);
int hc_cuStreamDestroy (void *hashcat_ctx, CUstream hStream);
int hc_cuStreamSynchronize (void *hashcat_ctx, CUstream hStream);
int hc_cuCtxPushCurrent (void *hashcat_ctx, CUcontext ctx);
int hc_cuCtxPopCurrent (void *hashcat_ctx, CUcontext *pctx);
int hc_cuLinkCreate (void *hashcat_ctx, unsigned int numOptions, CUjit_option *options, void **optionValues, CUlinkState *stateOut);
int hc_cuLinkAddData (void *hashcat_ctx, CUlinkState state, CUjitInputType type, void *data, size_t size, const char *name, unsigned int numOptions, CUjit_option *options, void **optionValues);
int hc_cuLinkDestroy (void *hashcat_ctx, CUlinkState state);
int hc_cuLinkComplete (void *hashcat_ctx, CUlinkState state, void **cubinOut, size_t *sizeOut);
#endif // HC_EXT_CUDA_H
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