/* Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in the * documentation and/or other materials provided with the distribution. * * Neither the name of NVIDIA CORPORATION nor the names of its * contributors may be used to endorse or promote products derived * from this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY * EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR * PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR * CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, * EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, * PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY * OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. */ //////////////////////////////////////////////////////////////////////////////// // These are CUDA Helper functions for initialization and error checking #ifndef COMMON_HELPER_CUDA_H_ #define COMMON_HELPER_CUDA_H_ #pragma once #include #include #include #include #include #ifndef EXIT_WAIVED #define EXIT_WAIVED 2 #endif // Note, it is required that your SDK sample to include the proper header // files, please refer the CUDA examples for examples of the needed CUDA // headers, which may change depending on which CUDA functions are used. // CUDA Runtime error messages #ifdef __DRIVER_TYPES_H__ static const char *_cudaGetErrorEnum(cudaError_t error) { return cudaGetErrorName(error); } #endif #ifdef CUDA_DRIVER_API // CUDA Driver API errors static const char *_cudaGetErrorEnum(CUresult error) { static char unknown[] = ""; const char *ret = NULL; cuGetErrorName(error, &ret); return ret ? ret : unknown; } #endif #ifdef CUBLAS_API_H_ // cuBLAS API errors static const char *_cudaGetErrorEnum(cublasStatus_t error) { switch (error) { case CUBLAS_STATUS_SUCCESS: return "CUBLAS_STATUS_SUCCESS"; case CUBLAS_STATUS_NOT_INITIALIZED: return "CUBLAS_STATUS_NOT_INITIALIZED"; case CUBLAS_STATUS_ALLOC_FAILED: return "CUBLAS_STATUS_ALLOC_FAILED"; case CUBLAS_STATUS_INVALID_VALUE: return "CUBLAS_STATUS_INVALID_VALUE"; case CUBLAS_STATUS_ARCH_MISMATCH: return "CUBLAS_STATUS_ARCH_MISMATCH"; case CUBLAS_STATUS_MAPPING_ERROR: return "CUBLAS_STATUS_MAPPING_ERROR"; case CUBLAS_STATUS_EXECUTION_FAILED: return "CUBLAS_STATUS_EXECUTION_FAILED"; case CUBLAS_STATUS_INTERNAL_ERROR: return "CUBLAS_STATUS_INTERNAL_ERROR"; case CUBLAS_STATUS_NOT_SUPPORTED: return "CUBLAS_STATUS_NOT_SUPPORTED"; case CUBLAS_STATUS_LICENSE_ERROR: return "CUBLAS_STATUS_LICENSE_ERROR"; } return ""; } #endif #ifdef _CUFFT_H_ // cuFFT API errors static const char *_cudaGetErrorEnum(cufftResult error) { switch (error) { case CUFFT_SUCCESS: return "CUFFT_SUCCESS"; case CUFFT_INVALID_PLAN: return "CUFFT_INVALID_PLAN"; case CUFFT_ALLOC_FAILED: return "CUFFT_ALLOC_FAILED"; case CUFFT_INVALID_TYPE: return "CUFFT_INVALID_TYPE"; case CUFFT_INVALID_VALUE: return "CUFFT_INVALID_VALUE"; case CUFFT_INTERNAL_ERROR: return "CUFFT_INTERNAL_ERROR"; case CUFFT_EXEC_FAILED: return "CUFFT_EXEC_FAILED"; case CUFFT_SETUP_FAILED: return "CUFFT_SETUP_FAILED"; case CUFFT_INVALID_SIZE: return "CUFFT_INVALID_SIZE"; case CUFFT_UNALIGNED_DATA: return "CUFFT_UNALIGNED_DATA"; case CUFFT_INCOMPLETE_PARAMETER_LIST: return "CUFFT_INCOMPLETE_PARAMETER_LIST"; case CUFFT_INVALID_DEVICE: return "CUFFT_INVALID_DEVICE"; case CUFFT_PARSE_ERROR: return "CUFFT_PARSE_ERROR"; case CUFFT_NO_WORKSPACE: return "CUFFT_NO_WORKSPACE"; case CUFFT_NOT_IMPLEMENTED: return "CUFFT_NOT_IMPLEMENTED"; case CUFFT_LICENSE_ERROR: return "CUFFT_LICENSE_ERROR"; case CUFFT_NOT_SUPPORTED: return "CUFFT_NOT_SUPPORTED"; } return ""; } #endif #ifdef CUSPARSEAPI // cuSPARSE API errors static const char *_cudaGetErrorEnum(cusparseStatus_t error) { switch (error) { case CUSPARSE_STATUS_SUCCESS: return "CUSPARSE_STATUS_SUCCESS"; case CUSPARSE_STATUS_NOT_INITIALIZED: return "CUSPARSE_STATUS_NOT_INITIALIZED"; case CUSPARSE_STATUS_ALLOC_FAILED: return "CUSPARSE_STATUS_ALLOC_FAILED"; case CUSPARSE_STATUS_INVALID_VALUE: return "CUSPARSE_STATUS_INVALID_VALUE"; case CUSPARSE_STATUS_ARCH_MISMATCH: return "CUSPARSE_STATUS_ARCH_MISMATCH"; case CUSPARSE_STATUS_MAPPING_ERROR: return "CUSPARSE_STATUS_MAPPING_ERROR"; case CUSPARSE_STATUS_EXECUTION_FAILED: return "CUSPARSE_STATUS_EXECUTION_FAILED"; case CUSPARSE_STATUS_INTERNAL_ERROR: return "CUSPARSE_STATUS_INTERNAL_ERROR"; case CUSPARSE_STATUS_MATRIX_TYPE_NOT_SUPPORTED: return "CUSPARSE_STATUS_MATRIX_TYPE_NOT_SUPPORTED"; } return ""; } #endif #ifdef CUSOLVER_COMMON_H_ // cuSOLVER API errors static const char *_cudaGetErrorEnum(cusolverStatus_t error) { switch (error) { case CUSOLVER_STATUS_SUCCESS: return "CUSOLVER_STATUS_SUCCESS"; case CUSOLVER_STATUS_NOT_INITIALIZED: return "CUSOLVER_STATUS_NOT_INITIALIZED"; case CUSOLVER_STATUS_ALLOC_FAILED: return "CUSOLVER_STATUS_ALLOC_FAILED"; case CUSOLVER_STATUS_INVALID_VALUE: return "CUSOLVER_STATUS_INVALID_VALUE"; case CUSOLVER_STATUS_ARCH_MISMATCH: return "CUSOLVER_STATUS_ARCH_MISMATCH"; case CUSOLVER_STATUS_MAPPING_ERROR: return "CUSOLVER_STATUS_MAPPING_ERROR"; case CUSOLVER_STATUS_EXECUTION_FAILED: return "CUSOLVER_STATUS_EXECUTION_FAILED"; case CUSOLVER_STATUS_INTERNAL_ERROR: return "CUSOLVER_STATUS_INTERNAL_ERROR"; case CUSOLVER_STATUS_MATRIX_TYPE_NOT_SUPPORTED: return "CUSOLVER_STATUS_MATRIX_TYPE_NOT_SUPPORTED"; case CUSOLVER_STATUS_NOT_SUPPORTED: return "CUSOLVER_STATUS_NOT_SUPPORTED "; case CUSOLVER_STATUS_ZERO_PIVOT: return "CUSOLVER_STATUS_ZERO_PIVOT"; case CUSOLVER_STATUS_INVALID_LICENSE: return "CUSOLVER_STATUS_INVALID_LICENSE"; } return ""; } #endif #ifdef CURAND_H_ // cuRAND API errors static const char *_cudaGetErrorEnum(curandStatus_t error) { switch (error) { case CURAND_STATUS_SUCCESS: return "CURAND_STATUS_SUCCESS"; case CURAND_STATUS_VERSION_MISMATCH: return "CURAND_STATUS_VERSION_MISMATCH"; case CURAND_STATUS_NOT_INITIALIZED: return "CURAND_STATUS_NOT_INITIALIZED"; case CURAND_STATUS_ALLOCATION_FAILED: return "CURAND_STATUS_ALLOCATION_FAILED"; case CURAND_STATUS_TYPE_ERROR: return "CURAND_STATUS_TYPE_ERROR"; case CURAND_STATUS_OUT_OF_RANGE: return "CURAND_STATUS_OUT_OF_RANGE"; case CURAND_STATUS_LENGTH_NOT_MULTIPLE: return "CURAND_STATUS_LENGTH_NOT_MULTIPLE"; case CURAND_STATUS_DOUBLE_PRECISION_REQUIRED: return "CURAND_STATUS_DOUBLE_PRECISION_REQUIRED"; case CURAND_STATUS_LAUNCH_FAILURE: return "CURAND_STATUS_LAUNCH_FAILURE"; case CURAND_STATUS_PREEXISTING_FAILURE: return "CURAND_STATUS_PREEXISTING_FAILURE"; case CURAND_STATUS_INITIALIZATION_FAILED: return "CURAND_STATUS_INITIALIZATION_FAILED"; case CURAND_STATUS_ARCH_MISMATCH: return "CURAND_STATUS_ARCH_MISMATCH"; case CURAND_STATUS_INTERNAL_ERROR: return "CURAND_STATUS_INTERNAL_ERROR"; } return ""; } #endif #ifdef NVJPEGAPI // nvJPEG API errors static const char *_cudaGetErrorEnum(nvjpegStatus_t error) { switch (error) { case NVJPEG_STATUS_SUCCESS: return "NVJPEG_STATUS_SUCCESS"; case NVJPEG_STATUS_NOT_INITIALIZED: return "NVJPEG_STATUS_NOT_INITIALIZED"; case NVJPEG_STATUS_INVALID_PARAMETER: return "NVJPEG_STATUS_INVALID_PARAMETER"; case NVJPEG_STATUS_BAD_JPEG: return "NVJPEG_STATUS_BAD_JPEG"; case NVJPEG_STATUS_JPEG_NOT_SUPPORTED: return "NVJPEG_STATUS_JPEG_NOT_SUPPORTED"; case NVJPEG_STATUS_ALLOCATOR_FAILURE: return "NVJPEG_STATUS_ALLOCATOR_FAILURE"; case NVJPEG_STATUS_EXECUTION_FAILED: return "NVJPEG_STATUS_EXECUTION_FAILED"; case NVJPEG_STATUS_ARCH_MISMATCH: return "NVJPEG_STATUS_ARCH_MISMATCH"; case NVJPEG_STATUS_INTERNAL_ERROR: return "NVJPEG_STATUS_INTERNAL_ERROR"; } return ""; } #endif #ifdef NV_NPPIDEFS_H // NPP API errors static const char *_cudaGetErrorEnum(NppStatus error) { switch (error) { case NPP_NOT_SUPPORTED_MODE_ERROR: return "NPP_NOT_SUPPORTED_MODE_ERROR"; case NPP_ROUND_MODE_NOT_SUPPORTED_ERROR: return "NPP_ROUND_MODE_NOT_SUPPORTED_ERROR"; case NPP_RESIZE_NO_OPERATION_ERROR: return "NPP_RESIZE_NO_OPERATION_ERROR"; case NPP_NOT_SUFFICIENT_COMPUTE_CAPABILITY: return "NPP_NOT_SUFFICIENT_COMPUTE_CAPABILITY"; #if ((NPP_VERSION_MAJOR << 12) + (NPP_VERSION_MINOR << 4)) <= 0x5000 case NPP_BAD_ARG_ERROR: return "NPP_BAD_ARGUMENT_ERROR"; case NPP_COEFF_ERROR: return "NPP_COEFFICIENT_ERROR"; case NPP_RECT_ERROR: return "NPP_RECTANGLE_ERROR"; case NPP_QUAD_ERROR: return "NPP_QUADRANGLE_ERROR"; case NPP_MEM_ALLOC_ERR: return "NPP_MEMORY_ALLOCATION_ERROR"; case NPP_HISTO_NUMBER_OF_LEVELS_ERROR: return "NPP_HISTOGRAM_NUMBER_OF_LEVELS_ERROR"; case NPP_INVALID_INPUT: return "NPP_INVALID_INPUT"; case NPP_POINTER_ERROR: return "NPP_POINTER_ERROR"; case NPP_WARNING: return "NPP_WARNING"; case NPP_ODD_ROI_WARNING: return "NPP_ODD_ROI_WARNING"; #else // These are for CUDA 5.5 or higher case NPP_BAD_ARGUMENT_ERROR: return "NPP_BAD_ARGUMENT_ERROR"; case NPP_COEFFICIENT_ERROR: return "NPP_COEFFICIENT_ERROR"; case NPP_RECTANGLE_ERROR: return "NPP_RECTANGLE_ERROR"; case NPP_QUADRANGLE_ERROR: return "NPP_QUADRANGLE_ERROR"; case NPP_MEMORY_ALLOCATION_ERR: return "NPP_MEMORY_ALLOCATION_ERROR"; case NPP_HISTOGRAM_NUMBER_OF_LEVELS_ERROR: return "NPP_HISTOGRAM_NUMBER_OF_LEVELS_ERROR"; case NPP_INVALID_HOST_POINTER_ERROR: return "NPP_INVALID_HOST_POINTER_ERROR"; case NPP_INVALID_DEVICE_POINTER_ERROR: return "NPP_INVALID_DEVICE_POINTER_ERROR"; #endif case NPP_LUT_NUMBER_OF_LEVELS_ERROR: return "NPP_LUT_NUMBER_OF_LEVELS_ERROR"; case NPP_TEXTURE_BIND_ERROR: return "NPP_TEXTURE_BIND_ERROR"; case NPP_WRONG_INTERSECTION_ROI_ERROR: return "NPP_WRONG_INTERSECTION_ROI_ERROR"; case NPP_NOT_EVEN_STEP_ERROR: return "NPP_NOT_EVEN_STEP_ERROR"; case NPP_INTERPOLATION_ERROR: return "NPP_INTERPOLATION_ERROR"; case NPP_RESIZE_FACTOR_ERROR: return "NPP_RESIZE_FACTOR_ERROR"; case NPP_HAAR_CLASSIFIER_PIXEL_MATCH_ERROR: return "NPP_HAAR_CLASSIFIER_PIXEL_MATCH_ERROR"; #if ((NPP_VERSION_MAJOR << 12) + (NPP_VERSION_MINOR << 4)) <= 0x5000 case NPP_MEMFREE_ERR: return "NPP_MEMFREE_ERR"; case NPP_MEMSET_ERR: return "NPP_MEMSET_ERR"; case NPP_MEMCPY_ERR: return "NPP_MEMCPY_ERROR"; case NPP_MIRROR_FLIP_ERR: return "NPP_MIRROR_FLIP_ERR"; #else case NPP_MEMFREE_ERROR: return "NPP_MEMFREE_ERROR"; case NPP_MEMSET_ERROR: return "NPP_MEMSET_ERROR"; case NPP_MEMCPY_ERROR: return "NPP_MEMCPY_ERROR"; case NPP_MIRROR_FLIP_ERROR: return "NPP_MIRROR_FLIP_ERROR"; #endif case NPP_ALIGNMENT_ERROR: return "NPP_ALIGNMENT_ERROR"; case NPP_STEP_ERROR: return "NPP_STEP_ERROR"; case NPP_SIZE_ERROR: return "NPP_SIZE_ERROR"; case NPP_NULL_POINTER_ERROR: return "NPP_NULL_POINTER_ERROR"; case NPP_CUDA_KERNEL_EXECUTION_ERROR: return "NPP_CUDA_KERNEL_EXECUTION_ERROR"; case NPP_NOT_IMPLEMENTED_ERROR: return "NPP_NOT_IMPLEMENTED_ERROR"; case NPP_ERROR: return "NPP_ERROR"; case NPP_SUCCESS: return "NPP_SUCCESS"; case NPP_WRONG_INTERSECTION_QUAD_WARNING: return "NPP_WRONG_INTERSECTION_QUAD_WARNING"; case NPP_MISALIGNED_DST_ROI_WARNING: return "NPP_MISALIGNED_DST_ROI_WARNING"; case NPP_AFFINE_QUAD_INCORRECT_WARNING: return "NPP_AFFINE_QUAD_INCORRECT_WARNING"; case NPP_DOUBLE_SIZE_WARNING: return "NPP_DOUBLE_SIZE_WARNING"; case NPP_WRONG_INTERSECTION_ROI_WARNING: return "NPP_WRONG_INTERSECTION_ROI_WARNING"; #if ((NPP_VERSION_MAJOR << 12) + (NPP_VERSION_MINOR << 4)) >= 0x6000 /* These are 6.0 or higher */ case NPP_LUT_PALETTE_BITSIZE_ERROR: return "NPP_LUT_PALETTE_BITSIZE_ERROR"; case NPP_ZC_MODE_NOT_SUPPORTED_ERROR: return "NPP_ZC_MODE_NOT_SUPPORTED_ERROR"; case NPP_QUALITY_INDEX_ERROR: return "NPP_QUALITY_INDEX_ERROR"; case NPP_CHANNEL_ORDER_ERROR: return "NPP_CHANNEL_ORDER_ERROR"; case NPP_ZERO_MASK_VALUE_ERROR: return "NPP_ZERO_MASK_VALUE_ERROR"; case NPP_NUMBER_OF_CHANNELS_ERROR: return "NPP_NUMBER_OF_CHANNELS_ERROR"; case NPP_COI_ERROR: return "NPP_COI_ERROR"; case NPP_DIVISOR_ERROR: return "NPP_DIVISOR_ERROR"; case NPP_CHANNEL_ERROR: return "NPP_CHANNEL_ERROR"; case NPP_STRIDE_ERROR: return "NPP_STRIDE_ERROR"; case NPP_ANCHOR_ERROR: return "NPP_ANCHOR_ERROR"; case NPP_MASK_SIZE_ERROR: return "NPP_MASK_SIZE_ERROR"; case NPP_MOMENT_00_ZERO_ERROR: return "NPP_MOMENT_00_ZERO_ERROR"; case NPP_THRESHOLD_NEGATIVE_LEVEL_ERROR: return "NPP_THRESHOLD_NEGATIVE_LEVEL_ERROR"; case NPP_THRESHOLD_ERROR: return "NPP_THRESHOLD_ERROR"; case NPP_CONTEXT_MATCH_ERROR: return "NPP_CONTEXT_MATCH_ERROR"; case NPP_FFT_FLAG_ERROR: return "NPP_FFT_FLAG_ERROR"; case NPP_FFT_ORDER_ERROR: return "NPP_FFT_ORDER_ERROR"; case NPP_SCALE_RANGE_ERROR: return "NPP_SCALE_RANGE_ERROR"; case NPP_DATA_TYPE_ERROR: return "NPP_DATA_TYPE_ERROR"; case NPP_OUT_OFF_RANGE_ERROR: return "NPP_OUT_OFF_RANGE_ERROR"; case NPP_DIVIDE_BY_ZERO_ERROR: return "NPP_DIVIDE_BY_ZERO_ERROR"; case NPP_RANGE_ERROR: return "NPP_RANGE_ERROR"; case NPP_NO_MEMORY_ERROR: return "NPP_NO_MEMORY_ERROR"; case NPP_ERROR_RESERVED: return "NPP_ERROR_RESERVED"; case NPP_NO_OPERATION_WARNING: return "NPP_NO_OPERATION_WARNING"; case NPP_DIVIDE_BY_ZERO_WARNING: return "NPP_DIVIDE_BY_ZERO_WARNING"; #endif #if ((NPP_VERSION_MAJOR << 12) + (NPP_VERSION_MINOR << 4)) >= 0x7000 /* These are 7.0 or higher */ case NPP_OVERFLOW_ERROR: return "NPP_OVERFLOW_ERROR"; case NPP_CORRUPTED_DATA_ERROR: return "NPP_CORRUPTED_DATA_ERROR"; #endif } return ""; } #endif #ifdef __DRIVER_TYPES_H__ #ifndef DEVICE_RESET #define DEVICE_RESET cudaDeviceReset(); #endif #else #ifndef DEVICE_RESET #define DEVICE_RESET #endif #endif template void check(T result, char const *const func, const char *const file, int const line) { if (result) { fprintf(stderr, "CUDA error at %s:%d code=%d(%s) \"%s\" \n", file, line, static_cast(result), _cudaGetErrorEnum(result), func); DEVICE_RESET // Make sure we call CUDA Device Reset before exiting exit(EXIT_FAILURE); } } #ifdef __DRIVER_TYPES_H__ // This will output the proper CUDA error strings in the event // that a CUDA host call returns an error #define checkCudaErrors(val) check((val), #val, __FILE__, __LINE__) // This will output the proper error string when calling cudaGetLastError #define getLastCudaError(msg) __getLastCudaError(msg, __FILE__, __LINE__) inline void __getLastCudaError(const char *errorMessage, const char *file, const int line) { cudaError_t err = cudaGetLastError(); if (cudaSuccess != err) { fprintf(stderr, "%s(%i) : getLastCudaError() CUDA error :" " %s : (%d) %s.\n", file, line, errorMessage, static_cast(err), cudaGetErrorString(err)); DEVICE_RESET exit(EXIT_FAILURE); } } // This will only print the proper error string when calling cudaGetLastError // but not exit program incase error detected. #define printLastCudaError(msg) __printLastCudaError(msg, __FILE__, __LINE__) inline void __printLastCudaError(const char *errorMessage, const char *file, const int line) { cudaError_t err = cudaGetLastError(); if (cudaSuccess != err) { fprintf(stderr, "%s(%i) : getLastCudaError() CUDA error :" " %s : (%d) %s.\n", file, line, errorMessage, static_cast(err), cudaGetErrorString(err)); } } #endif #ifndef MAX #define MAX(a, b) (a > b ? a : b) #endif // Float To Int conversion inline int ftoi(float value) { return (value >= 0 ? static_cast(value + 0.5) : static_cast(value - 0.5)); } // Beginning of GPU Architecture definitions inline int _ConvertSMVer2Cores(int major, int minor) { // Defines for GPU Architecture types (using the SM version to determine // the # of cores per SM typedef struct { int SM; // 0xMm (hexidecimal notation), M = SM Major version, // and m = SM minor version int Cores; } sSMtoCores; sSMtoCores nGpuArchCoresPerSM[] = { {0x30, 192}, {0x32, 192}, {0x35, 192}, {0x37, 192}, {0x50, 128}, {0x52, 128}, {0x53, 128}, {0x60, 64}, {0x61, 128}, {0x62, 128}, {0x70, 64}, {0x72, 64}, {0x75, 64}, {-1, -1}}; int index = 0; while (nGpuArchCoresPerSM[index].SM != -1) { if (nGpuArchCoresPerSM[index].SM == ((major << 4) + minor)) { return nGpuArchCoresPerSM[index].Cores; } index++; } // If we don't find the values, we default use the previous one // to run properly printf( "MapSMtoCores for SM %d.%d is undefined." " Default to use %d Cores/SM\n", major, minor, nGpuArchCoresPerSM[index - 1].Cores); return nGpuArchCoresPerSM[index - 1].Cores; } // end of GPU Architecture definitions #ifdef __CUDA_RUNTIME_H__ // General GPU Device CUDA Initialization inline int gpuDeviceInit(int devID) { int device_count; checkCudaErrors(cudaGetDeviceCount(&device_count)); if (device_count == 0) { fprintf(stderr, "gpuDeviceInit() CUDA error: " "no devices supporting CUDA.\n"); exit(EXIT_FAILURE); } if (devID < 0) { devID = 0; } if (devID > device_count - 1) { fprintf(stderr, "\n"); fprintf(stderr, ">> %d CUDA capable GPU device(s) detected. <<\n", device_count); fprintf(stderr, ">> gpuDeviceInit (-device=%d) is not a valid" " GPU device. <<\n", devID); fprintf(stderr, "\n"); return -devID; } cudaDeviceProp deviceProp; checkCudaErrors(cudaGetDeviceProperties(&deviceProp, devID)); if (deviceProp.computeMode == cudaComputeModeProhibited) { fprintf(stderr, "Error: device is running in , no threads can use cudaSetDevice().\n"); return -1; } if (deviceProp.major < 1) { fprintf(stderr, "gpuDeviceInit(): GPU device does not support CUDA.\n"); exit(EXIT_FAILURE); } checkCudaErrors(cudaSetDevice(devID)); printf("gpuDeviceInit() CUDA Device [%d]: \"%s\n", devID, deviceProp.name); return devID; } // This function returns the best GPU (with maximum GFLOPS) inline int gpuGetMaxGflopsDeviceId() { int current_device = 0, sm_per_multiproc = 0; int max_perf_device = 0; int device_count = 0; int devices_prohibited = 0; uint64_t max_compute_perf = 0; cudaDeviceProp deviceProp; checkCudaErrors(cudaGetDeviceCount(&device_count)); if (device_count == 0) { fprintf(stderr, "gpuGetMaxGflopsDeviceId() CUDA error:" " no devices supporting CUDA.\n"); exit(EXIT_FAILURE); } // Find the best CUDA capable GPU device current_device = 0; while (current_device < device_count) { cudaGetDeviceProperties(&deviceProp, current_device); // If this GPU is not running on Compute Mode prohibited, // then we can add it to the list if (deviceProp.computeMode != cudaComputeModeProhibited) { if (deviceProp.major == 9999 && deviceProp.minor == 9999) { sm_per_multiproc = 1; } else { sm_per_multiproc = _ConvertSMVer2Cores(deviceProp.major, deviceProp.minor); } uint64_t compute_perf = (uint64_t)deviceProp.multiProcessorCount * sm_per_multiproc * deviceProp.clockRate; if (compute_perf > max_compute_perf) { max_compute_perf = compute_perf; max_perf_device = current_device; } } else { devices_prohibited++; } ++current_device; } if (devices_prohibited == device_count) { fprintf(stderr, "gpuGetMaxGflopsDeviceId() CUDA error:" " all devices have compute mode prohibited.\n"); exit(EXIT_FAILURE); } return max_perf_device; } // Initialization code to find the best CUDA Device inline int findCudaDevice(int argc, const char **argv) { cudaDeviceProp deviceProp; int devID = 0; // If the command-line has a device number specified, use it if (checkCmdLineFlag(argc, argv, "device")) { devID = getCmdLineArgumentInt(argc, argv, "device="); if (devID < 0) { printf("Invalid command line parameter\n "); exit(EXIT_FAILURE); } else { devID = gpuDeviceInit(devID); if (devID < 0) { printf("exiting...\n"); exit(EXIT_FAILURE); } } } else { // Otherwise pick the device with highest Gflops/s devID = gpuGetMaxGflopsDeviceId(); checkCudaErrors(cudaSetDevice(devID)); checkCudaErrors(cudaGetDeviceProperties(&deviceProp, devID)); printf("GPU Device %d: \"%s\" with compute capability %d.%d\n\n", devID, deviceProp.name, deviceProp.major, deviceProp.minor); } return devID; } inline int findIntegratedGPU() { int current_device = 0; int device_count = 0; int devices_prohibited = 0; cudaDeviceProp deviceProp; checkCudaErrors(cudaGetDeviceCount(&device_count)); if (device_count == 0) { fprintf(stderr, "CUDA error: no devices supporting CUDA.\n"); exit(EXIT_FAILURE); } // Find the integrated GPU which is compute capable while (current_device < device_count) { cudaGetDeviceProperties(&deviceProp, current_device); // If GPU is integrated and is not running on Compute Mode prohibited, // then cuda can map to GLES resource if (deviceProp.integrated && (deviceProp.computeMode != cudaComputeModeProhibited)) { checkCudaErrors(cudaSetDevice(current_device)); checkCudaErrors(cudaGetDeviceProperties(&deviceProp, current_device)); printf("GPU Device %d: \"%s\" with compute capability %d.%d\n\n", current_device, deviceProp.name, deviceProp.major, deviceProp.minor); return current_device; } else { devices_prohibited++; } current_device++; } if (devices_prohibited == device_count) { fprintf(stderr, "CUDA error:" " No GLES-CUDA Interop capable GPU found.\n"); exit(EXIT_FAILURE); } return -1; } // General check for CUDA GPU SM Capabilities inline bool checkCudaCapabilities(int major_version, int minor_version) { cudaDeviceProp deviceProp; deviceProp.major = 0; deviceProp.minor = 0; int dev; checkCudaErrors(cudaGetDevice(&dev)); checkCudaErrors(cudaGetDeviceProperties(&deviceProp, dev)); if ((deviceProp.major > major_version) || (deviceProp.major == major_version && deviceProp.minor >= minor_version)) { printf(" Device %d: <%16s >, Compute SM %d.%d detected\n", dev, deviceProp.name, deviceProp.major, deviceProp.minor); return true; } else { printf( " No GPU device was found that can support " "CUDA compute capability %d.%d.\n", major_version, minor_version); return false; } } #endif // end of CUDA Helper Functions #endif // COMMON_HELPER_CUDA_H_