void pcl::gpu::printShortCudaDeviceInfo(int device)
{
int count = getCudaEnabledDeviceCount();
bool valid = (device >= 0) && (device < count);
int beg = valid ? device : 0;
int end = valid ? device+1 : count;
int driverVersion = 0, runtimeVersion = 0;
cudaSafeCall( cudaDriverGetVersion(&driverVersion) );
cudaSafeCall( cudaRuntimeGetVersion(&runtimeVersion) );
for(int dev = beg; dev < end; ++dev)
{
cudaDeviceProp prop;
cudaSafeCall( cudaGetDeviceProperties(&prop, dev) );
const char *arch_str = prop.major < 2 ? " (pre-Fermi)" : "";
printf("[pcl::gpu::printShortCudaDeviceInfo] : Device %d: \"%s\" %.0fMb", dev, prop.name, (float)prop.totalGlobalMem/1048576.0f);
printf(", sm_%d%d%s, %d cores", prop.major, prop.minor, arch_str, convertSMVer2Cores(prop.major, prop.minor) * prop.multiProcessorCount);
printf(", Driver/Runtime ver.%d.%d/%d.%d\n", driverVersion/1000, driverVersion%100, runtimeVersion/1000, runtimeVersion%100);
}
fflush(stdout);
}
// CUDA Devices on the System
int cuda_num_devices()
{
int version;
cudaError_t err = cudaDriverGetVersion(&version);
if (err != cudaSuccess)
{
applog(LOG_ERR, "Unable to query CUDA driver version! Is an nVidia driver installed?");
exit(1);
}
int maj = version / 1000, min = version % 100; // same as in deviceQuery sample
if (maj < 5 || (maj == 5 && min < 5))
{
applog(LOG_ERR, "Driver does not support CUDA %d.%d API! Update your nVidia driver!", 5, 5);
exit(1);
}
int GPU_N;
err = cudaGetDeviceCount(&GPU_N);
if (err != cudaSuccess)
{
applog(LOG_ERR, "Unable to query number of CUDA devices! Is an nVidia driver installed?");
exit(1);
}
return GPU_N;
}
TEST(StreamQuery, InvalidStream) {
::testing::FLAGS_gtest_death_test_style = "threadsafe";
cudaError_t ret;
cudaStream_t stream;
/* The CUDA 5.0 driver no longer segfaults. */
int driver;
ret = cudaDriverGetVersion(&driver);
ASSERT_EQ(cudaSuccess, ret);
ret = cudaStreamCreate(&stream);
ASSERT_EQ(cudaSuccess, ret);
ret = cudaStreamDestroy(stream);
ASSERT_EQ(cudaSuccess, ret);
if (driver >= 5000) {
ret = cudaStreamQuery(stream);
EXPECT_EQ(cudaErrorUnknown, ret);
} else {
EXPECT_EXIT({
cudaStreamQuery(stream); },
::testing::KilledBySignal(SIGSEGV), "");
}
oskar_CudaInfo* oskar_cuda_info_create(int* status)
{
oskar_CudaInfo* info;
int i;
/* Allocate index. */
info = (oskar_CudaInfo*) calloc(1, sizeof(oskar_CudaInfo));
/* Get the runtime version and the driver version. */
cudaDriverGetVersion(&info->driver_version);
cudaRuntimeGetVersion(&info->runtime_version);
/* Query the number of devices in the system. */
*status = cudaGetDeviceCount(&info->num_devices);
if (*status != cudaSuccess || info->num_devices == 0)
{
fprintf(stderr, "Unable to determine number of CUDA devices: %s\n",
cudaGetErrorString((cudaError_t)(*status)));
return info;
}
/* Allocate array big enough. */
info->device = (oskar_CudaDeviceInfo*) calloc(info->num_devices,
sizeof(oskar_CudaDeviceInfo));
/* Populate device array. */
for (i = 0; i < info->num_devices; ++i)
{
oskar_cuda_device_info_scan(&(info->device[i]), i);
}
return info;
}
// CUDAが使えるかチェック
Waifu2x::eWaifu2xCudaError Waifu2x::can_use_CUDA()
{
static eWaifu2xCudaError CudaFlag = eWaifu2xCudaError_NotFind;
std::call_once(waifu2x_cuda_once_flag, [&]()
{
int driverVersion = 0;
if (cudaDriverGetVersion(&driverVersion) == cudaSuccess)
{
if (driverVersion > 0)
{
int runtimeVersion;
if (cudaRuntimeGetVersion(&runtimeVersion) == cudaSuccess)
{
if (runtimeVersion >= MinCudaDriverVersion && driverVersion >= runtimeVersion)
CudaFlag = eWaifu2xCudaError_OK;
else
CudaFlag = eWaifu2xCudaError_OldVersion;
}
else
CudaFlag = eWaifu2xCudaError_NotFind;
}
else
CudaFlag = eWaifu2xCudaError_NotFind;
}
else
CudaFlag = eWaifu2xCudaError_NotFind;
});
return CudaFlag;
}
Caffe::Properties::Properties() :
init_time_(std::time(nullptr)),
main_thread_id_(std::this_thread::get_id()),
caffe_version_(AS_STRING(CAFFE_VERSION)) {
#ifndef CPU_ONLY
int count = 0;
CUDA_CHECK(cudaGetDeviceCount(&count));
compute_capabilities_.resize(count);
cudaDeviceProp device_prop;
for (int gpu = 0; gpu < compute_capabilities_.size(); ++gpu) {
CUDA_CHECK(cudaGetDeviceProperties(&device_prop, gpu));
compute_capabilities_[gpu] = device_prop.major * 100 + device_prop.minor;
DLOG(INFO) << "GPU " << gpu << " '" << device_prop.name << "' has compute capability "
<< device_prop.major << "." << device_prop.minor;
}
#ifdef USE_CUDNN
cudnn_version_ =
AS_STRING(CUDNN_MAJOR) "." AS_STRING(CUDNN_MINOR) "." AS_STRING(CUDNN_PATCHLEVEL);
#else
cudnn_version_ = "USE_CUDNN is not defined";
#endif
int cublas_version = 0;
CUBLAS_CHECK(cublasGetVersion(Caffe::cublas_handle(), &cublas_version));
cublas_version_ = std::to_string(cublas_version);
int cuda_version = 0;
CUDA_CHECK(cudaRuntimeGetVersion(&cuda_version));
cuda_version_ = std::to_string(cuda_version);
int cuda_driver_version = 0;
CUDA_CHECK(cudaDriverGetVersion(&cuda_driver_version));
cuda_driver_version_ = std::to_string(cuda_driver_version);
#endif
}
int
main(int argc, char *argv[])
{
int ver, major;
cudaDriverGetVersion(&ver);
major = ver/1000;
return(major < 5);
}
void print_info()
{
printf("\n");
#if defined _WIN32
# if defined _WIN64
puts("OS: Windows 64");
# else
puts("OS: Windows 32");
# endif
#elif defined linux
# if defined _LP64
puts("OS: Linux 64");
# else
puts("OS: Linux 32");
# endif
#elif defined __APPLE__
# if defined _LP64
puts("OS: Apple 64");
# else
puts("OS: Apple 32");
# endif
#endif
int deviceCount = cv::gpu::getCudaEnabledDeviceCount();
int driver;
cudaDriverGetVersion(&driver);
printf("CUDA Driver version: %d\n", driver);
printf("CUDA Runtime version: %d\n", CUDART_VERSION);
printf("CUDA device count: %d\n\n", deviceCount);
for (int i = 0; i < deviceCount; ++i)
{
cv::gpu::DeviceInfo info(i);
printf("Device %d:\n", i);
printf(" Name: %s\n", info.name().c_str());
printf(" Compute capability version: %d.%d\n", info.majorVersion(), info.minorVersion());
printf(" Total memory: %d Mb\n", static_cast<int>(static_cast<int>(info.totalMemory() / 1024.0) / 1024.0));
printf(" Free memory: %d Mb\n", static_cast<int>(static_cast<int>(info.freeMemory() / 1024.0) / 1024.0));
if (info.isCompatible())
puts(" This device is compatible with current GPU module build\n");
else
puts(" This device is NOT compatible with current GPU module build\n");
}
puts("GPU module was compiled for the following GPU archs:");
printf(" BIN: %s\n", CUDA_ARCH_BIN);
printf(" PTX: %s\n\n", CUDA_ARCH_PTX);
}
bool printfNPPinfo(int argc, char *argv[], int cudaVerMajor, int cudaVerMinor)
{
const NppLibraryVersion *libVer = nppGetLibVersion();
printf("NPP Library Version %d.%d.%d\n", libVer->major, libVer->minor, libVer->build);
int driverVersion, runtimeVersion;
cudaDriverGetVersion(&driverVersion);
cudaRuntimeGetVersion(&runtimeVersion);
printf(" CUDA Driver Version: %d.%d\n", driverVersion/1000, (driverVersion%100)/10);
printf(" CUDA Runtime Version: %d.%d\n", runtimeVersion/1000, (runtimeVersion%100)/10);
bool bVal = checkCudaCapabilities(cudaVerMajor, cudaVerMinor);
return bVal;
}
void DialogSelectHardware::ChangeText(int indexDevice)
{
int driverVersion = 0, runtimeVersion = 0;
cudaSetDevice(indexDevice);
cudaGetDeviceProperties(deviceProp, indexDevice);
cudaDriverGetVersion(&driverVersion);
cudaRuntimeGetVersion(&runtimeVersion);
char msg[256];
SPRINTF(msg,"%.0f MBytes (%llu bytes)\n",
(float)deviceProp->totalGlobalMem/1048576.0f, (unsigned long long) deviceProp->totalGlobalMem);
ui->tableWidget->clear();
addItem(QString ("Device "+QString::number(indexDevice).append(" : ")+ deviceProp->name),0,0);
addItem((selectDevice == indexDevice) ? "Dispositivo Seleccionado " : " ",0,1);
addItem("CUDA Driver Version / Runtime Version",1,0);
addItem(QString ("%1.%2 / %3.%4").arg(driverVersion/1000).arg((driverVersion%100)/10).arg( runtimeVersion/1000).arg((runtimeVersion%100)/10),1,1);
addItem("CUDA Capability Major/Minor version number: ",2,0);
addItem(QString ("%1.%2").arg(deviceProp->major).arg(deviceProp->minor),2,1);
addItem("Total amount of global memory:",3,0);
addItem(msg,3,1);
addItem(QString ("(%1) Multiprocessors, (%2) CUDA Cores/MP:%3 CUDA Cores").arg( deviceProp->multiProcessorCount).arg( _ConvertSMVer2Cores(deviceProp->major, deviceProp->minor)).arg( _ConvertSMVer2Cores(deviceProp->major, deviceProp->minor) * deviceProp->multiProcessorCount),4,0);
addItem("Total amount of constant memory:",5,0);
addItem(QString ("%1 bytes").arg(deviceProp->totalConstMem),5,1);
addItem("Total amount of shared memory per block:",6,0);
addItem(QString ("%1 bytes").arg(deviceProp->sharedMemPerBlock),6,1);
addItem("Total number of registers available per block:",7,0);
addItem(QString ("%1").arg(deviceProp->regsPerBlock),7,1);
addItem("Warp size:",8,0);
addItem(QString ("%1").arg(deviceProp->warpSize),8,1);
addItem("Maximum number of threads per multiprocessor:",9,0);
addItem(QString ("%1").arg(deviceProp->maxThreadsPerMultiProcessor),9,1);
addItem("Maximum number of threads per block:",10,0);
addItem(QString ("%1").arg(deviceProp->maxThreadsPerBlock),10,1);
addItem("Max dimension size of a thread block (x,y,z):",11,0);
addItem(QString ("(%1, %2, %3)").arg(deviceProp->maxThreadsDim[0]).arg( deviceProp->maxThreadsDim[1]).arg( deviceProp->maxThreadsDim[2]),11,1);
addItem("Max dimension size of a grid size (x,y,z):",12,0);
addItem(QString ("(%1, %2, %3)\n").arg(deviceProp->maxGridSize[0]).arg(deviceProp->maxGridSize[1]).arg(deviceProp->maxGridSize[2]),12,1);
addItem("Run time limit on kernels: ",13,0);
addItem(QString ("%1\n").arg(deviceProp->kernelExecTimeoutEnabled ? "Yes" : "No"),13,1);
addItem("Integrated GPU sharing Host Memory: ",14,0);
addItem( QString ("%1\n").arg(deviceProp->integrated ? "Yes" : "No"),14,1);
ui->tableWidget->resizeColumnsToContents();
ui->tableWidget->resizeRowsToContents();
}
void cuda_running_configuration::update_parameters()
{
cuda_safe_call(cudaDriverGetVersion(&driver_version));
cuda_safe_call(cudaRuntimeGetVersion(&runtime_version));
int device_count;
cuda_safe_call(cudaGetDeviceCount(&device_count));
if (device_count <= 0)
throw neural_network_exception("No CUDA capable devices are found");
if (device_id >= device_count)
throw neural_network_exception((boost::format("Device ID %1% specified while %2% devices are available") % device_id % device_count).str());
cudaDeviceProp device_prop;
cuda_safe_call(cudaGetDeviceProperties(&device_prop, device_id));
device_name = device_prop.name;
compute_capability_major = device_prop.major;
compute_capability_minor = device_prop.minor;
clock_rate = device_prop.clockRate;
memory_clock_rate = device_prop.memoryClockRate;
memory_bus_width = device_prop.memoryBusWidth;
global_memory_size = device_prop.totalGlobalMem;
ecc_enabled = (device_prop.ECCEnabled != 0);
l2_cache_size = device_prop.l2CacheSize;
multiprocessor_count = device_prop.multiProcessorCount;
smem_per_block = device_prop.sharedMemPerBlock;
max_threads_per_multiprocessor = device_prop.maxThreadsPerMultiProcessor;
max_threads_per_block = device_prop.maxThreadsPerBlock;
for(int i = 0; i < sizeof(max_threads_dim) / sizeof(max_threads_dim[0]); ++i)
max_threads_dim[i] = device_prop.maxThreadsDim[i];
for(int i = 0; i < sizeof(max_grid_size) / sizeof(max_grid_size[0]); ++i)
max_grid_size[i] = device_prop.maxGridSize[i];
max_texture_1d_linear = device_prop.maxTexture1DLinear;
texture_alignment = device_prop.textureAlignment;
pci_bus_id = device_prop.pciBusID;
pci_device_id = device_prop.pciDeviceID;
#ifdef _WIN32
tcc_mode = (device_prop.tccDriver != 0);
#endif
cuda_safe_call(cudaSetDevice(device_id));
cublas_safe_call(cublasCreate(&cublas_handle));
cusparse_safe_call(cusparseCreate(&cusparse_handle));
}
static void printCudaInfo()
{
printOsInfo();
#ifndef HAVE_CUDA
printf("[----------]\n[ GPU INFO ] \tOpenCV was built without CUDA support.\n[----------]\n"), fflush(stdout);
#else
int driver;
cudaDriverGetVersion(&driver);
printf("[----------]\n"), fflush(stdout);
printf("[ GPU INFO ] \tCUDA Driver version: %d.\n", driver), fflush(stdout);
printf("[ GPU INFO ] \tCUDA Runtime version: %d.\n", CUDART_VERSION), fflush(stdout);
printf("[----------]\n"), fflush(stdout);
printf("[----------]\n"), fflush(stdout);
printf("[ GPU INFO ] \tGPU module was compiled for the following GPU archs.\n"), fflush(stdout);
printf("[ BIN ] \t%s.\n", CUDA_ARCH_BIN), fflush(stdout);
printf("[ PTX ] \t%s.\n", CUDA_ARCH_PTX), fflush(stdout);
printf("[----------]\n"), fflush(stdout);
printf("[----------]\n"), fflush(stdout);
int deviceCount = cv::gpu::getCudaEnabledDeviceCount();
printf("[ GPU INFO ] \tCUDA device count:: %d.\n", deviceCount), fflush(stdout);
printf("[----------]\n"), fflush(stdout);
for (int i = 0; i < deviceCount; ++i)
{
cv::gpu::DeviceInfo info(i);
printf("[----------]\n"), fflush(stdout);
printf("[ DEVICE ] \t# %d %s.\n", i, info.name().c_str()), fflush(stdout);
printf("[ ] \tCompute capability: %d.%d\n", (int)info.majorVersion(), (int)info.minorVersion()), fflush(stdout);
printf("[ ] \tMulti Processor Count: %d\n", info.multiProcessorCount()), fflush(stdout);
printf("[ ] \tTotal memory: %d Mb\n", static_cast<int>(static_cast<int>(info.totalMemory() / 1024.0) / 1024.0)), fflush(stdout);
printf("[ ] \tFree memory: %d Mb\n", static_cast<int>(static_cast<int>(info.freeMemory() / 1024.0) / 1024.0)), fflush(stdout);
if (!info.isCompatible())
printf("[ GPU INFO ] \tThis device is NOT compatible with current GPU module build\n");
printf("[----------]\n"), fflush(stdout);
}
#endif
}
char CudaBase::CheckCUDevice()
{
int deviceCount = 0;
if (cudaGetDeviceCount(&deviceCount) != cudaSuccess) {
std::cout << "Cannot find CUDA device!";
return 0;
}
if(deviceCount>0) {
std::cout << "Found " << deviceCount << " device(s)\n";
int driverVersion = 0, runtimeVersion = 0;
cudaDeviceProp deviceProp;
cudaGetDeviceProperties(&deviceProp, 0);
cudaDriverGetVersion(&driverVersion);
cudaRuntimeGetVersion(&runtimeVersion);
std::cout << " Device name: " << deviceProp.name<<"\n";
std::cout << " Diver Version: " << driverVersion<<"\n";
std::cout << " Runtime Version: " << runtimeVersion<<"\n";
std::cout << " Capability Major/Minor version number: "<<deviceProp.major<<"."<<deviceProp.minor<<"\n";
std::cout << " Total amount of global memory: "<<(unsigned long long)deviceProp.totalGlobalMem<<" bytes\n";
std::cout << " Total amount of constant memory: "<<deviceProp.totalConstMem<<"bytes\n";
std::cout << " Total amount of shared memory per block: "<<deviceProp.sharedMemPerBlock<<" bytes\n";
std::cout << " Total number of registers available per block: "<<deviceProp.regsPerBlock<<"\n";
std::cout << " Warp size: "<<deviceProp.warpSize<<"\n";
std::stringstream sst;
sst<<" Maximum sizes of each dimension of a grid: "<<deviceProp.maxGridSize[0]<<" x "<<deviceProp.maxGridSize[1]<<" x "<<deviceProp.maxGridSize[2];
std::cout<<sst.str()<<"\n";
sst.str("");
sst<<" Maximum sizes of each dimension of a block: "<<deviceProp.maxThreadsDim[0]<<" x "<<deviceProp.maxThreadsDim[1]<<" x "<<deviceProp.maxThreadsDim[2];
std::cout<<sst.str()<<"\n";
std::cout << " Maximum number of threads per block: " << deviceProp.maxThreadsPerBlock<<"\n";
MaxThreadPerBlock = deviceProp.maxThreadsPerBlock;
MaxRegisterPerBlock = deviceProp.regsPerBlock;
MaxSharedMemoryPerBlock = deviceProp.sharedMemPerBlock;
WarpSize = deviceProp.warpSize;
RuntimeVersion = runtimeVersion;
return 1;
}
return 0;
}
void oskar_device_get_info_cuda(oskar_Device* device)
{
#ifdef OSKAR_HAVE_CUDA
struct cudaDeviceProp prop;
cudaDriverGetVersion(&device->cuda_driver_version);
cudaRuntimeGetVersion(&device->cuda_runtime_version);
cudaGetDeviceProperties(&prop, device->index);
device->name = (char*) realloc(device->name, 1 + strlen(prop.name));
device->vendor = (char*) realloc(device->vendor, 1 + strlen("NVIDIA"));
strcpy(device->name, prop.name);
strcpy(device->vendor, "NVIDIA");
device->is_nv = 1;
device->platform_type = 'C';
device->device_type = 'G';
device->compute_capability[0] = prop.major;
device->compute_capability[1] = prop.minor;
device->supports_double = 0;
if (prop.major >= 2 || prop.minor >= 3)
device->supports_double = 1;
device->supports_atomic32 = 1;
device->supports_atomic64 = 1;
device->global_mem_cache_size = (size_t) prop.l2CacheSize;
device->local_mem_size = prop.sharedMemPerBlock;
device->max_work_group_size = (size_t) prop.maxThreadsPerBlock;
device->max_local_size[0] = prop.maxThreadsDim[0];
device->max_local_size[1] = prop.maxThreadsDim[1];
device->max_local_size[2] = prop.maxThreadsDim[2];
device->max_compute_units = prop.multiProcessorCount;
device->max_clock_freq_kHz = prop.clockRate;
device->memory_clock_freq_kHz = prop.memoryClockRate;
device->memory_bus_width = prop.memoryBusWidth;
device->num_registers = (unsigned int) prop.regsPerBlock;
device->warp_size = prop.warpSize;
cudaMemGetInfo(&device->global_mem_free_size, &device->global_mem_size);
#endif
device->num_cores = device->max_compute_units * oskar_get_num_cuda_cores(
device->compute_capability[0], device->compute_capability[1]);
device->init = 1;
}
// CUDAが使えるかチェック
Waifu2x::eWaifu2xCudaError Waifu2x::can_use_CUDA()
{
static eWaifu2xCudaError CudaFlag = eWaifu2xCudaError_NotFind;
std::call_once(waifu2x_cuda_once_flag, [&]()
{
int driverVersion = 0;
if (cudaDriverGetVersion(&driverVersion) == cudaSuccess)
{
if (driverVersion > 0)
{
int runtimeVersion;
if (cudaRuntimeGetVersion(&runtimeVersion) == cudaSuccess)
{
if (runtimeVersion >= MinCudaDriverVersion && driverVersion >= runtimeVersion)
{
cudaDeviceProp prop;
cudaGetDeviceProperties(&prop, 0);
if (prop.major >= 2)
CudaFlag = eWaifu2xCudaError_OK;
else
CudaFlag = eWaifu2xCudaError_OldDevice;
}
else
CudaFlag = eWaifu2xCudaError_OldVersion;
}
else
CudaFlag = eWaifu2xCudaError_NotFind;
}
else
CudaFlag = eWaifu2xCudaError_NotFind;
}
else
CudaFlag = eWaifu2xCudaError_NotFind;
});
return CudaFlag;
}
TEST(StreamSynchronize, InvalidStream) {
::testing::FLAGS_gtest_death_test_style = "threadsafe";
cudaStream_t stream;
cudaError_t ret;
/* The CUDA 5.0 driver no longer segfaults. */
int driver;
ret = cudaDriverGetVersion(&driver);
if (driver >= 5000) {
ret = cudaStreamCreate(&stream);
ASSERT_EQ(cudaSuccess, ret);
ret = cudaStreamDestroy(stream);
ASSERT_EQ(cudaSuccess, ret);
ret = cudaStreamSynchronize(stream);
EXPECT_EQ(cudaErrorUnknown, ret);
} else {
/**
* Without this compound statement, EXPECT_EXIT fails.
* Without the EXPECT_EXIT wrapper, SIGSEGV happens.
*
* From appearances, it seems that gtest does not properly execute both
* cudaStreamCreate and cudaStreamDestroy on stream when entering the
* death test for this lone statement as to properly "initialize"
* stream.
*/
EXPECT_EXIT(
{
cudaStreamCreate(&stream);
cudaStreamDestroy(stream);
cudaStreamSynchronize(stream);
},
::testing::KilledBySignal(SIGSEGV), "");
}
int cudaDeviceInfo(void)
{
int deviceCount = 0;
if (cudaGetDeviceCount(&deviceCount) != cudaSuccess)
{
Scierror(999, "\ncudaGetDeviceCount FAILED CUDA Driver and Runtime version may be mismatched.\n\n");
return 1;
}
sciprint("Starting...\n\n");
sciprint(" CUDA Device Query (Runtime API) version (CUDART static linking)\n\n");
// This function call returns 0 if there are no CUDA capable devices.
if (deviceCount == 0)
{
sciprint("There is no device supporting CUDA\n");
}
int dev = 0;
int driverVersion = 0, runtimeVersion = 0;
for (dev = 0; dev < deviceCount; ++dev)
{
cudaDeviceProp deviceProp;
cudaGetDeviceProperties(&deviceProp, dev);
if (dev == 0)
{
// This function call returns 9999 for both major & minor fields, if no CUDA capable devices are present
if (deviceProp.major == 9999 && deviceProp.minor == 9999)
{
sciprint("There is no device supporting CUDA.\n");
}
else if (deviceCount == 1)
{
sciprint("There is 1 device supporting CUDA\n");
}
else
{
sciprint("There are %d devices supporting CUDA\n", deviceCount);
}
}
sciprint("\nDevice %d: \"%s\"\n", dev, deviceProp.name);
#if CUDART_VERSION >= 2020
// Console log
cudaDriverGetVersion(&driverVersion);
sciprint(" CUDA Driver Version: %d.%d\n", driverVersion / 1000, driverVersion % 100);
cudaRuntimeGetVersion(&runtimeVersion);
sciprint(" CUDA Runtime Version: %d.%d\n", runtimeVersion / 1000, runtimeVersion % 100);
#endif
sciprint(" CUDA Capability Major revision number: %d\n", deviceProp.major);
sciprint(" CUDA Capability Minor revision number: %d\n", deviceProp.minor);
sciprint(" Total amount of global memory: %u bytes\n", deviceProp.totalGlobalMem);
#if CUDART_VERSION >= 2000
sciprint(" Number of multiprocessors: %d\n", deviceProp.multiProcessorCount);
// sciprint(" Number of cores: %d\n", nGpuArchCoresPerSM[deviceProp.major] * deviceProp.multiProcessorCount);
#endif
sciprint(" Total amount of constant memory: %u bytes\n", deviceProp.totalConstMem);
sciprint(" Total amount of shared memory per block: %u bytes\n", deviceProp.sharedMemPerBlock);
sciprint(" Total number of registers available per block: %d\n", deviceProp.regsPerBlock);
sciprint(" Warp size: %d\n", deviceProp.warpSize);
sciprint(" Maximum number of threads per block: %d\n", deviceProp.maxThreadsPerBlock);
sciprint(" Maximum sizes of each dimension of a block: %d x %d x %d\n",
deviceProp.maxThreadsDim[0],
deviceProp.maxThreadsDim[1],
deviceProp.maxThreadsDim[2]);
sciprint(" Maximum sizes of each dimension of a grid: %d x %d x %d\n",
deviceProp.maxGridSize[0],
deviceProp.maxGridSize[1],
deviceProp.maxGridSize[2]);
sciprint(" Maximum memory pitch: %u bytes\n", deviceProp.memPitch);
sciprint(" Texture alignment: %u bytes\n", deviceProp.textureAlignment);
sciprint(" Clock rate: %.2f GHz\n", deviceProp.clockRate * 1e-6f);
#if CUDART_VERSION >= 2000
sciprint(" Concurrent copy and execution: %s\n", deviceProp.deviceOverlap ? "Yes" : "No");
#endif
#if CUDART_VERSION >= 2020
sciprint(" Run time limit on kernels: %s\n", deviceProp.kernelExecTimeoutEnabled ? "Yes" : "No");
sciprint(" Integrated: %s\n", deviceProp.integrated ? "Yes" : "No");
sciprint(" Support host page-locked memory mapping: %s\n", deviceProp.canMapHostMemory ? "Yes" : "No");
sciprint(" Compute mode: %s\n", deviceProp.computeMode == cudaComputeModeDefault ?
"Default (multiple host threads can use this device simultaneously)" :
deviceProp.computeMode == cudaComputeModeExclusive ?
"Exclusive (only one host thread at a time can use this device)" :
deviceProp.computeMode == cudaComputeModeProhibited ?
"Prohibited (no host thread can use this device)" :
"Unknown");
#endif
#if CUDART_VERSION >= 3000
sciprint(" Concurrent kernel execution: %s\n", deviceProp.concurrentKernels ? "Yes" : "No");
#endif
#if CUDART_VERSION >= 3010
sciprint(" Device has ECC support enabled: %s\n", deviceProp.ECCEnabled ? "Yes" : "No");
#endif
}
// finish
sciprint("\n\nPASSED\n");
return 0;
}
////////////////////////////////////////////////////////////////////////////////
// Program main
////////////////////////////////////////////////////////////////////////////////
int
main(int argc, char **argv)
{
pArgc = &argc;
pArgv = argv;
printf("%s Starting...\n\n", argv[0]);
printf(" CUDA Device Query (Runtime API) version (CUDART static linking)\n\n");
int deviceCount = 0;
cudaError_t error_id = cudaGetDeviceCount(&deviceCount);
if (error_id != cudaSuccess)
{
printf("cudaGetDeviceCount returned %d\n-> %s\n", (int)error_id, cudaGetErrorString(error_id));
exit(EXIT_FAILURE);
}
// This function call returns 0 if there are no CUDA capable devices.
if (deviceCount == 0)
{
printf("There are no available device(s) that support CUDA\n");
}
else
{
printf("Detected %d CUDA Capable device(s)\n", deviceCount);
}
int dev, driverVersion = 0, runtimeVersion = 0;
for (dev = 0; dev < deviceCount; ++dev)
{
cudaSetDevice(dev);
cudaDeviceProp deviceProp;
cudaGetDeviceProperties(&deviceProp, dev);
printf("\nDevice %d: \"%s\"\n", dev, deviceProp.name);
// Console log
cudaDriverGetVersion(&driverVersion);
cudaRuntimeGetVersion(&runtimeVersion);
printf(" CUDA Driver Version / Runtime Version %d.%d / %d.%d\n", driverVersion/1000, (driverVersion%100)/10, runtimeVersion/1000, (runtimeVersion%100)/10);
printf(" CUDA Capability Major/Minor version number: %d.%d\n", deviceProp.major, deviceProp.minor);
char msg[256];
sprintf(msg, " Total amount of global memory: %.0f MBytes (%llu bytes)\n",
(float)deviceProp.totalGlobalMem/1048576.0f, (unsigned long long) deviceProp.totalGlobalMem);
printf("%s", msg);
printf(" (%2d) Multiprocessors x (%3d) CUDA Cores/MP: %d CUDA Cores\n",
deviceProp.multiProcessorCount,
_ConvertSMVer2Cores(deviceProp.major, deviceProp.minor),
_ConvertSMVer2Cores(deviceProp.major, deviceProp.minor) * deviceProp.multiProcessorCount);
printf(" GPU Clock rate: %.0f MHz (%0.2f GHz)\n", deviceProp.clockRate * 1e-3f, deviceProp.clockRate * 1e-6f);
#if CUDART_VERSION >= 5000
// This is supported in CUDA 5.0 (runtime API device properties)
printf(" Memory Clock rate: %.0f Mhz\n", deviceProp.memoryClockRate * 1e-3f);
printf(" Memory Bus Width: %d-bit\n", deviceProp.memoryBusWidth);
if (deviceProp.l2CacheSize)
{
printf(" L2 Cache Size: %d bytes\n", deviceProp.l2CacheSize);
}
#else
// This only available in CUDA 4.0-4.2 (but these were only exposed in the CUDA Driver API)
int memoryClock;
getCudaAttribute<int>(&memoryClock, CU_DEVICE_ATTRIBUTE_MEMORY_CLOCK_RATE, dev);
printf(" Memory Clock rate: %.0f Mhz\n", memoryClock * 1e-3f);
int memBusWidth;
getCudaAttribute<int>(&memBusWidth, CU_DEVICE_ATTRIBUTE_GLOBAL_MEMORY_BUS_WIDTH, dev);
printf(" Memory Bus Width: %d-bit\n", memBusWidth);
int L2CacheSize;
getCudaAttribute<int>(&L2CacheSize, CU_DEVICE_ATTRIBUTE_L2_CACHE_SIZE, dev);
if (L2CacheSize)
{
printf(" L2 Cache Size: %d bytes\n", L2CacheSize);
}
#endif
printf(" Max Texture Dimension Size (x,y,z) 1D=(%d), 2D=(%d,%d), 3D=(%d,%d,%d)\n",
deviceProp.maxTexture1D , deviceProp.maxTexture2D[0], deviceProp.maxTexture2D[1],
deviceProp.maxTexture3D[0], deviceProp.maxTexture3D[1], deviceProp.maxTexture3D[2]);
printf(" Max Layered Texture Size (dim) x layers 1D=(%d) x %d, 2D=(%d,%d) x %d\n",
deviceProp.maxTexture1DLayered[0], deviceProp.maxTexture1DLayered[1],
deviceProp.maxTexture2DLayered[0], deviceProp.maxTexture2DLayered[1], deviceProp.maxTexture2DLayered[2]);
printf(" Total amount of constant memory: %lu bytes\n", deviceProp.totalConstMem);
printf(" Total amount of shared memory per block: %lu bytes\n", deviceProp.sharedMemPerBlock);
printf(" Total number of registers available per block: %d\n", deviceProp.regsPerBlock);
printf(" Warp size: %d\n", deviceProp.warpSize);
printf(" Maximum number of threads per multiprocessor: %d\n", deviceProp.maxThreadsPerMultiProcessor);
printf(" Maximum number of threads per block: %d\n", deviceProp.maxThreadsPerBlock);
printf(" Maximum sizes of each dimension of a block: %d x %d x %d\n",
deviceProp.maxThreadsDim[0],
deviceProp.maxThreadsDim[1],
deviceProp.maxThreadsDim[2]);
printf(" Maximum sizes of each dimension of a grid: %d x %d x %d\n",
deviceProp.maxGridSize[0],
deviceProp.maxGridSize[1],
deviceProp.maxGridSize[2]);
printf(" Maximum memory pitch: %lu bytes\n", deviceProp.memPitch);
printf(" Texture alignment: %lu bytes\n", deviceProp.textureAlignment);
printf(" Concurrent copy and kernel execution: %s with %d copy engine(s)\n", (deviceProp.deviceOverlap ? "Yes" : "No"), deviceProp.asyncEngineCount);
printf(" Run time limit on kernels: %s\n", deviceProp.kernelExecTimeoutEnabled ? "Yes" : "No");
printf(" Integrated GPU sharing Host Memory: %s\n", deviceProp.integrated ? "Yes" : "No");
printf(" Support host page-locked memory mapping: %s\n", deviceProp.canMapHostMemory ? "Yes" : "No");
printf(" Alignment requirement for Surfaces: %s\n", deviceProp.surfaceAlignment ? "Yes" : "No");
printf(" Device has ECC support: %s\n", deviceProp.ECCEnabled ? "Enabled" : "Disabled");
#ifdef WIN32
printf(" CUDA Device Driver Mode (TCC or WDDM): %s\n", deviceProp.tccDriver ? "TCC (Tesla Compute Cluster Driver)" : "WDDM (Windows Display Driver Model)");
#endif
printf(" Device supports Unified Addressing (UVA): %s\n", deviceProp.unifiedAddressing ? "Yes" : "No");
printf(" Device PCI Bus ID / PCI location ID: %d / %d\n", deviceProp.pciBusID, deviceProp.pciDeviceID);
const char *sComputeMode[] =
{
"Default (multiple host threads can use ::cudaSetDevice() with device simultaneously)",
"Exclusive (only one host thread in one process is able to use ::cudaSetDevice() with this device)",
"Prohibited (no host thread can use ::cudaSetDevice() with this device)",
"Exclusive Process (many threads in one process is able to use ::cudaSetDevice() with this device)",
"Unknown",
NULL
};
printf(" Compute Mode:\n");
printf(" < %s >\n", sComputeMode[deviceProp.computeMode]);
}
// csv masterlog info
// *****************************
// exe and CUDA driver name
printf("\n");
std::string sProfileString = "deviceQuery, CUDA Driver = CUDART";
char cTemp[16];
// driver version
sProfileString += ", CUDA Driver Version = ";
#ifdef WIN32
sprintf_s(cTemp, 10, "%d.%d", driverVersion/1000, (driverVersion%100)/10);
#else
sprintf(cTemp, "%d.%d", driverVersion/1000, (driverVersion%100)/10);
#endif
sProfileString += cTemp;
// Runtime version
sProfileString += ", CUDA Runtime Version = ";
#ifdef WIN32
sprintf_s(cTemp, 10, "%d.%d", runtimeVersion/1000, (runtimeVersion%100)/10);
#else
sprintf(cTemp, "%d.%d", runtimeVersion/1000, (runtimeVersion%100)/10);
#endif
sProfileString += cTemp;
// Device count
sProfileString += ", NumDevs = ";
#ifdef WIN32
sprintf_s(cTemp, 10, "%d", deviceCount);
#else
sprintf(cTemp, "%d", deviceCount);
#endif
sProfileString += cTemp;
// Print Out all device Names
for (dev = 0; dev < deviceCount; ++dev)
{
#ifdef _WIN32
sprintf_s(cTemp, 13, ", Device%d = ", dev);
#else
sprintf(cTemp, ", Device%d = ", dev);
#endif
cudaDeviceProp deviceProp;
cudaGetDeviceProperties(&deviceProp, dev);
sProfileString += cTemp;
sProfileString += deviceProp.name;
}
sProfileString += "\n";
printf("%s", sProfileString.c_str());
// finish
exit(EXIT_SUCCESS);
}
/** Documented at declaration */
int
gpujpeg_init_device(int device_id, int flags)
{
int dev_count;
cudaGetDeviceCount(&dev_count);
if ( dev_count == 0 ) {
fprintf(stderr, "[GPUJPEG] [Error] No CUDA enabled device\n");
return -1;
}
if ( device_id < 0 || device_id >= dev_count ) {
fprintf(stderr, "[GPUJPEG] [Error] Selected device %d is out of bound. Devices on your system are in range %d - %d\n",
device_id, 0, dev_count - 1);
return -1;
}
struct cudaDeviceProp devProp;
if ( cudaSuccess != cudaGetDeviceProperties(&devProp, device_id) ) {
fprintf(stderr,
"[GPUJPEG] [Error] Can't get CUDA device properties!\n"
"[GPUJPEG] [Error] Do you have proper driver for CUDA installed?\n"
);
return -1;
}
if ( devProp.major < 1 ) {
fprintf(stderr, "[GPUJPEG] [Error] Device %d does not support CUDA\n", device_id);
return -1;
}
if ( flags & GPUJPEG_OPENGL_INTEROPERABILITY ) {
cudaGLSetGLDevice(device_id);
gpujpeg_cuda_check_error("Enabling OpenGL interoperability");
}
if ( flags & GPUJPEG_VERBOSE ) {
int cuda_driver_version = 0;
cudaDriverGetVersion(&cuda_driver_version);
printf("CUDA driver version: %d.%d\n", cuda_driver_version / 1000, (cuda_driver_version % 100) / 10);
int cuda_runtime_version = 0;
cudaRuntimeGetVersion(&cuda_runtime_version);
printf("CUDA runtime version: %d.%d\n", cuda_runtime_version / 1000, (cuda_runtime_version % 100) / 10);
printf("Using Device #%d: %s (c.c. %d.%d)\n", device_id, devProp.name, devProp.major, devProp.minor);
}
cudaSetDevice(device_id);
gpujpeg_cuda_check_error("Set CUDA device");
// Test by simple copying that the device is ready
uint8_t data[] = {8};
uint8_t* d_data = NULL;
cudaMalloc((void**)&d_data, 1);
cudaMemcpy(d_data, data, 1, cudaMemcpyHostToDevice);
cudaFree(d_data);
cudaError_t error = cudaGetLastError();
if ( cudaSuccess != error ) {
fprintf(stderr, "[GPUJPEG] [Error] Failed to initialize CUDA device.\n");
if ( flags & GPUJPEG_OPENGL_INTEROPERABILITY )
fprintf(stderr, "[GPUJPEG] [Info] OpenGL interoperability is used, is OpenGL context available?\n");
return -1;
}
return 0;
}
QHardwareWidget::QHardwareWidget(QWidget* pParent) :
QGroupBox(pParent),
m_MainLayout(),
m_Devices(),
m_OptimalDevice()
{
setTitle("Hardware Selection");
setStatusTip("Hardware Selection");
setToolTip("Hardware Selection");
m_MainLayout.setColumnMinimumWidth(0, 75);
setLayout(&m_MainLayout);
int DriverVersion = 0, RuntimeVersion = 0;
cudaDriverGetVersion(&DriverVersion);
cudaRuntimeGetVersion(&RuntimeVersion);
QString DriverVersionString = QString::number(DriverVersion / 1000) + "." + QString::number(DriverVersion % 100);
QString RuntimeVersionString = QString::number(RuntimeVersion / 1000) + "." + QString::number(RuntimeVersion % 100);
gStatus.SetStatisticChanged("Graphics Card", "CUDA Driver Version", DriverVersionString);
gStatus.SetStatisticChanged("Graphics Card", "CUDA Runtime Version", RuntimeVersionString);
QString VersionInfo;
VersionInfo += "CUDA Driver Version: " + DriverVersionString;
VersionInfo += ", CUDA Runtime Version: " + RuntimeVersionString;
m_MainLayout.addWidget(new QLabel(VersionInfo), 0, 0, 1, 2);
m_MainLayout.addWidget(&m_Devices, 1, 0, 1, 2);
m_Model.EnumerateDevices();
m_Devices.horizontalHeader()->setResizeMode(QHeaderView::ResizeToContents);
m_Devices.horizontalHeader()->setStretchLastSection(true);
m_Devices.horizontalHeader()->setDefaultSectionSize(1);
m_Devices.horizontalHeader()->setDefaultAlignment(Qt::AlignLeft);
m_Devices.horizontalHeader()->setHighlightSections(false);
m_Devices.verticalHeader()->setVisible(false);
m_Devices.verticalHeader()->setDefaultSectionSize(20);
m_Devices.setSelectionMode(QAbstractItemView::SingleSelection);
m_Devices.setSelectionBehavior(QAbstractItemView::SelectRows);
m_Devices.setFixedHeight(75);
m_Devices.setModel(&m_Model);
m_OptimalDevice.setText("Optimal Device");
m_OptimalDevice.setToolTip("Optimal Device");
m_OptimalDevice.setStatusTip("Choose the most optimal device for rendering");
m_OptimalDevice.setFixedWidth(90);
m_OptimalDevice.setVisible(m_Model.rowCount(QModelIndex()) > 1);
m_MainLayout.addWidget(&m_OptimalDevice);
QObject::connect(&m_OptimalDevice, SIGNAL(clicked()), this, SLOT(OnOptimalDevice()));
QObject::connect(&m_Devices, SIGNAL(clicked(const QModelIndex&)), this, SLOT(OnSelection(const QModelIndex&)));
OnOptimalDevice();
}
/////////////////////////////////////////////////////////////////////////////
// Device info dump (this code is taken from the SDK's deviceQuery example)
/////////////////////////////////////////////////////////////////////////////
static int dump()
{
int deviceCount = 0;
// This function call returns 0 if there are no CUDA capable devices.
cudaGetDeviceCount(&deviceCount);
if (deviceCount == 0)
{
printf("There is no device supporting CUDA\n");
return (1);
}
int dev = 0;
for (dev = 0; dev < deviceCount; ++dev)
{
cudaDeviceProp deviceProp;
cudaGetDeviceProperties(&deviceProp, dev);
if (dev == 0)
{
// This function call returns 9999 for both major & minor fields,
// if no CUDA capable devices are present
if (deviceProp.major == 9999 && deviceProp.minor == 9999)
{
printf("There is no device supporting CUDA.\n");
return (1);
}
else if (deviceCount == 1)
printf("There is 1 device supporting CUDA:\n");
else
printf("There are %d devices supporting CUDA:\n", deviceCount);
}
printf("\nDevice %d: \"%s\"\n", dev, deviceProp.name);
int driverVersion = 0, runtimeVersion = 0;
cudaDriverGetVersion(&driverVersion);
printf(" CUDA Driver Version: %d.%d\n",
driverVersion/1000, driverVersion%100);
cudaRuntimeGetVersion(&runtimeVersion);
printf(" CUDA Runtime Version: %d.%d\n",
runtimeVersion/1000, runtimeVersion%100);
printf(" CUDA Capability Major revision number: %d\n",
deviceProp.major);
printf(" CUDA Capability Minor revision number: %d\n",
deviceProp.minor);
printf(" Total amount of global memory: %u bytes\n",
(unsigned int)deviceProp.totalGlobalMem);
printf(" Number of multiprocessors: %d\n",
deviceProp.multiProcessorCount);
printf(" Number of cores: %d\n",
nGpuArchCoresPerSM[deviceProp.major] *
deviceProp.multiProcessorCount);
printf(" Total amount of constant memory: %u bytes\n",
(unsigned int)deviceProp.totalConstMem);
printf(" Total amount of shared memory per block: %u bytes\n",
(unsigned int)deviceProp.sharedMemPerBlock);
printf(" Total number of registers available per block: %d\n",
deviceProp.regsPerBlock);
printf(" Warp size: %d\n",
deviceProp.warpSize);
printf(" Maximum number of threads per block: %d\n",
deviceProp.maxThreadsPerBlock);
printf(" Maximum sizes of each dimension of a block: %d x %d x %d\n",
deviceProp.maxThreadsDim[0],
deviceProp.maxThreadsDim[1],
deviceProp.maxThreadsDim[2]);
printf(" Maximum sizes of each dimension of a grid: %d x %d x %d\n",
deviceProp.maxGridSize[0],
deviceProp.maxGridSize[1],
deviceProp.maxGridSize[2]);
printf(" Maximum memory pitch: %u bytes\n",
(unsigned int)deviceProp.memPitch);
printf(" Texture alignment: %u bytes\n",
(unsigned int)deviceProp.textureAlignment);
printf(" Clock rate: %.2f GHz\n",
deviceProp.clockRate * 1e-6f);
printf(" Concurrent copy and execution: %s\n",
deviceProp.deviceOverlap ? "Yes" : "No");
printf(" Run time limit on kernels: %s\n",
deviceProp.kernelExecTimeoutEnabled ? "Yes" : "No");
printf(" Integrated: %s\n",
deviceProp.integrated ? "Yes" : "No");
printf(" Support host page-locked memory mapping: %s\n",
deviceProp.canMapHostMemory ? "Yes" : "No");
printf(" Compute mode: %s\n",
deviceProp.computeMode == cudaComputeModeDefault ?
"Default (multiple host threads can use this device "
"simultaneously)" :
deviceProp.computeMode == cudaComputeModeExclusive ?
"Exclusive (only one host thread at a time can use this device)" :
deviceProp.computeMode == cudaComputeModeProhibited ?
"Prohibited (no host thread can use this device)" :
"Unknown");
}
return (0);
}
cudaError_t WINAPI wine_cudaDriverGetVersion( int *driverVersion ) {
WINE_TRACE("\n");
return cudaDriverGetVersion( driverVersion );
}
int SimCudaHelper::PrintDevices(int deviceSelected)
{
int deviceCount = 0;
if (cudaGetDeviceCount(&deviceCount) != cudaSuccess)
{
printf("cudaGetDeviceCount FAILED CUDA Driver and Runtime version may be mismatched.\n");
printf("\nFAILED\n");
}
// This function call returns 0 if there are no CUDA capable devices.
if (deviceCount == 0)
printf("There is no device supporting CUDA\n");
int dev;
int driverVersion = 0, runtimeVersion = 0;
for (dev = 0; dev < deviceCount; ++dev)
{
cudaDeviceProp deviceProp;
cudaGetDeviceProperties(&deviceProp, dev);
if (dev == 0)
{
// This function call returns 9999 for both major & minor fields, if no CUDA capable devices are present
if (deviceProp.major == 9999 && deviceProp.minor == 9999)
printf("There is no device supporting CUDA.\n");
else if (deviceCount == 1)
printf("There is 1 device supporting CUDA\n");
else
printf("There are %d devices supporting CUDA\n", deviceCount);
}
printf("\nDevice %d: \"%s\"\n", dev, deviceProp.name);
#if CUDART_VERSION >= 2020
// Console log
cudaDriverGetVersion(&driverVersion);
printf(" CUDA Driver Version: %d.%d\n", driverVersion / 1000, driverVersion % 100);
cudaRuntimeGetVersion(&runtimeVersion);
printf(" CUDA Runtime Version: %d.%d\n", runtimeVersion / 1000, runtimeVersion % 100);
#endif
printf(" CUDA Capability Major revision number: %d\n", deviceProp.major);
printf(" CUDA Capability Minor revision number: %d\n", deviceProp.minor);
printf(" Total amount of global memory: %zu bytes\n", deviceProp.totalGlobalMem);
#if CUDART_VERSION >= 2000
printf(" Number of multiprocessors: %d\n", deviceProp.multiProcessorCount);
//printf(" Number of cores: %d\n", nGpuArchCoresPerSM[deviceProp.major] * deviceProp.multiProcessorCount);
#endif
printf(" Total amount of constant memory: %zu bytes\n", deviceProp.totalConstMem);
printf(" Total amount of shared memory per block: %zu bytes\n", deviceProp.sharedMemPerBlock);
printf(" Total number of registers available per block: %d\n", deviceProp.regsPerBlock);
printf(" Warp size: %d\n", deviceProp.warpSize);
printf(" Maximum number of threads per block: %d\n", deviceProp.maxThreadsPerBlock);
printf(" Maximum sizes of each dimension of a block: %d x %d x %d\n",
deviceProp.maxThreadsDim[0],
deviceProp.maxThreadsDim[1],
deviceProp.maxThreadsDim[2]);
printf(" Maximum sizes of each dimension of a grid: %d x %d x %d\n",
deviceProp.maxGridSize[0],
deviceProp.maxGridSize[1],
deviceProp.maxGridSize[2]);
printf(" Maximum memory pitch: %zu bytes\n", deviceProp.memPitch);
printf(" Texture alignment: %zu bytes\n", deviceProp.textureAlignment);
printf(" Clock rate: %.2f GHz\n", deviceProp.clockRate * 1e-6f);
#if CUDART_VERSION >= 2000
printf(" Concurrent copy and execution: %s\n", deviceProp.deviceOverlap ? "Yes" : "No");
#endif
#if CUDART_VERSION >= 2020
printf(" Run time limit on kernels: %s\n", deviceProp.kernelExecTimeoutEnabled ? "Yes" : "No");
printf(" Integrated: %s\n", deviceProp.integrated ? "Yes" : "No");
printf(" Support host page-locked memory mapping: %s\n", deviceProp.canMapHostMemory ? "Yes" : "No");
printf(" Compute mode: %s\n", deviceProp.computeMode == cudaComputeModeDefault ? "Default (multiple host threads can use this device simultaneously)" : deviceProp.computeMode == cudaComputeModeExclusive ? "Exclusive (only one host thread at a time can use this device)" : deviceProp.computeMode == cudaComputeModeProhibited ? "Prohibited (no host thread can use this device)" : "Unknown");
#endif
}
// csv masterlog info
// *****************************
// exe and CUDA driver name
printf("\n");
std::string sProfileString = "deviceQuery, CUDA Driver = CUDART";
char cTemp[10];
// driver version
sProfileString += ", CUDA Driver Version = ";
#ifdef WIN32
sprintf_s(cTemp, 10, "%d.%d", driverVersion / 1000, driverVersion % 100);
#else
sprintf(cTemp, "%d.%d", driverVersion / 1000, driverVersion % 100);
#endif
sProfileString += cTemp;
// Runtime version
sProfileString += ", CUDA Runtime Version = ";
#ifdef WIN32
sprintf_s(cTemp, 10, "%d.%d", runtimeVersion / 1000, runtimeVersion % 100);
#else
sprintf(cTemp, "%d.%d", runtimeVersion / 1000, runtimeVersion % 100);
#endif
sProfileString += cTemp;
// Device count
sProfileString += ", NumDevs = ";
#ifdef WIN32
sprintf_s(cTemp, 10, "%d", deviceCount);
#else
sprintf(cTemp, "%d", deviceCount);
#endif
sProfileString += cTemp;
// First 2 device names, if any
for (dev = 0; dev < ((deviceCount > 2) ? 2 : deviceCount); ++dev)
{
cudaDeviceProp deviceProp;
cudaGetDeviceProperties(&deviceProp, dev);
sProfileString += ", Device = ";
sProfileString += deviceProp.name;
}
sProfileString += "\n";
// shrLogEx(LOGBOTH | MASTER, 0, sProfileString.c_str());
// finish
//printf("\n\nPASSED\n");
//Log* pLog = Ogre::LogManager::getSingleton().getDefaultLog();
cudaError_t err = cudaSuccess;
return err;
}
////////////////////////////////////////////////////////////////////////////////
// Program main
////////////////////////////////////////////////////////////////////////////////
int
main(int argc, char **argv)
{
pArgc = &argc;
pArgv = argv;
printf("%s Starting...\n\n", argv[0]);
printf(" CUDA Device Query (Runtime API) version (CUDART static linking)\n\n");
int deviceCount = 0;
cudaError_t error_id = cudaGetDeviceCount(&deviceCount);
if (error_id != cudaSuccess)
{
printf("cudaGetDeviceCount returned %d\n-> %s\n", (int)error_id, cudaGetErrorString(error_id));
printf("Result = FAIL\n");
exit(EXIT_FAILURE);
}
// This function call returns 0 if there are no CUDA capable devices.
if (deviceCount == 0)
{
printf("There are no available device(s) that support CUDA\n");
}
else
{
printf("Detected %d CUDA Capable device(s)\n", deviceCount);
}
int dev, driverVersion = 0, runtimeVersion = 0;
for (dev = 0; dev < deviceCount; ++dev)
{
cudaSetDevice(dev);
cudaDeviceProp deviceProp;
cudaGetDeviceProperties(&deviceProp, dev);
printf("\nDevice %d: \"%s\"\n", dev, deviceProp.name);
// Console log
cudaDriverGetVersion(&driverVersion);
cudaRuntimeGetVersion(&runtimeVersion);
printf(" CUDA Driver Version / Runtime Version %d.%d / %d.%d\n", driverVersion/1000, (driverVersion%100)/10, runtimeVersion/1000, (runtimeVersion%100)/10);
printf(" CUDA Capability Major/Minor version number: %d.%d\n", deviceProp.major, deviceProp.minor);
char msg[256];
SPRINTF(msg, " Total amount of global memory: %.0f MBytes (%llu bytes)\n",
(float)deviceProp.totalGlobalMem/1048576.0f, (unsigned long long) deviceProp.totalGlobalMem);
printf("%s", msg);
printf(" (%2d) Multiprocessors, (%3d) CUDA Cores/MP: %d CUDA Cores\n",
deviceProp.multiProcessorCount,
_ConvertSMVer2Cores(deviceProp.major, deviceProp.minor),
_ConvertSMVer2Cores(deviceProp.major, deviceProp.minor) * deviceProp.multiProcessorCount);
printf(" GPU Max Clock rate: %.0f MHz (%0.2f GHz)\n", deviceProp.clockRate * 1e-3f, deviceProp.clockRate * 1e-6f);
#if CUDART_VERSION >= 5000
// This is supported in CUDA 5.0 (runtime API device properties)
printf(" Memory Clock rate: %.0f Mhz\n", deviceProp.memoryClockRate * 1e-3f);
printf(" Memory Bus Width: %d-bit\n", deviceProp.memoryBusWidth);
if (deviceProp.l2CacheSize)
{
printf(" L2 Cache Size: %d bytes\n", deviceProp.l2CacheSize);
}
#else
// This only available in CUDA 4.0-4.2 (but these were only exposed in the CUDA Driver API)
int memoryClock;
getCudaAttribute<int>(&memoryClock, CU_DEVICE_ATTRIBUTE_MEMORY_CLOCK_RATE, dev);
printf(" Memory Clock rate: %.0f Mhz\n", memoryClock * 1e-3f);
int memBusWidth;
getCudaAttribute<int>(&memBusWidth, CU_DEVICE_ATTRIBUTE_GLOBAL_MEMORY_BUS_WIDTH, dev);
printf(" Memory Bus Width: %d-bit\n", memBusWidth);
int L2CacheSize;
getCudaAttribute<int>(&L2CacheSize, CU_DEVICE_ATTRIBUTE_L2_CACHE_SIZE, dev);
if (L2CacheSize)
{
printf(" L2 Cache Size: %d bytes\n", L2CacheSize);
}
#endif
printf(" Maximum Texture Dimension Size (x,y,z) 1D=(%d), 2D=(%d, %d), 3D=(%d, %d, %d)\n",
deviceProp.maxTexture1D , deviceProp.maxTexture2D[0], deviceProp.maxTexture2D[1],
deviceProp.maxTexture3D[0], deviceProp.maxTexture3D[1], deviceProp.maxTexture3D[2]);
printf(" Maximum Layered 1D Texture Size, (num) layers 1D=(%d), %d layers\n",
deviceProp.maxTexture1DLayered[0], deviceProp.maxTexture1DLayered[1]);
printf(" Maximum Layered 2D Texture Size, (num) layers 2D=(%d, %d), %d layers\n",
deviceProp.maxTexture2DLayered[0], deviceProp.maxTexture2DLayered[1], deviceProp.maxTexture2DLayered[2]);
printf(" Total amount of constant memory: %lu bytes\n", deviceProp.totalConstMem);
printf(" Total amount of shared memory per block: %lu bytes\n", deviceProp.sharedMemPerBlock);
printf(" Total number of registers available per block: %d\n", deviceProp.regsPerBlock);
printf(" Warp size: %d\n", deviceProp.warpSize);
printf(" Maximum number of threads per multiprocessor: %d\n", deviceProp.maxThreadsPerMultiProcessor);
printf(" Maximum number of threads per block: %d\n", deviceProp.maxThreadsPerBlock);
printf(" Max dimension size of a thread block (x,y,z): (%d, %d, %d)\n",
deviceProp.maxThreadsDim[0],
deviceProp.maxThreadsDim[1],
deviceProp.maxThreadsDim[2]);
printf(" Max dimension size of a grid size (x,y,z): (%d, %d, %d)\n",
deviceProp.maxGridSize[0],
deviceProp.maxGridSize[1],
deviceProp.maxGridSize[2]);
printf(" Maximum memory pitch: %lu bytes\n", deviceProp.memPitch);
printf(" Texture alignment: %lu bytes\n", deviceProp.textureAlignment);
printf(" Concurrent copy and kernel execution: %s with %d copy engine(s)\n", (deviceProp.deviceOverlap ? "Yes" : "No"), deviceProp.asyncEngineCount);
printf(" Run time limit on kernels: %s\n", deviceProp.kernelExecTimeoutEnabled ? "Yes" : "No");
printf(" Integrated GPU sharing Host Memory: %s\n", deviceProp.integrated ? "Yes" : "No");
printf(" Support host page-locked memory mapping: %s\n", deviceProp.canMapHostMemory ? "Yes" : "No");
printf(" Alignment requirement for Surfaces: %s\n", deviceProp.surfaceAlignment ? "Yes" : "No");
printf(" Device has ECC support: %s\n", deviceProp.ECCEnabled ? "Enabled" : "Disabled");
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
printf(" CUDA Device Driver Mode (TCC or WDDM): %s\n", deviceProp.tccDriver ? "TCC (Tesla Compute Cluster Driver)" : "WDDM (Windows Display Driver Model)");
#endif
printf(" Device supports Unified Addressing (UVA): %s\n", deviceProp.unifiedAddressing ? "Yes" : "No");
printf(" Device PCI Domain ID / Bus ID / location ID: %d / %d / %d\n", deviceProp.pciDomainID, deviceProp.pciBusID, deviceProp.pciDeviceID);
const char *sComputeMode[] =
{
"Default (multiple host threads can use ::cudaSetDevice() with device simultaneously)",
"Exclusive (only one host thread in one process is able to use ::cudaSetDevice() with this device)",
"Prohibited (no host thread can use ::cudaSetDevice() with this device)",
"Exclusive Process (many threads in one process is able to use ::cudaSetDevice() with this device)",
"Unknown",
NULL
};
printf(" Compute Mode:\n");
printf(" < %s >\n", sComputeMode[deviceProp.computeMode]);
}
// If there are 2 or more GPUs, query to determine whether RDMA is supported
if (deviceCount >= 2)
{
cudaDeviceProp prop[64];
int gpuid[64]; // we want to find the first two GPUs that can support P2P
int gpu_p2p_count = 0;
for (int i=0; i < deviceCount; i++)
{
checkCudaErrors(cudaGetDeviceProperties(&prop[i], i));
// Only boards based on Fermi or later can support P2P
if ((prop[i].major >= 2)
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
// on Windows (64-bit), the Tesla Compute Cluster driver for windows must be enabled to support this
&& prop[i].tccDriver
#endif
)
{
// This is an array of P2P capable GPUs
gpuid[gpu_p2p_count++] = i;
}
}
// Show all the combinations of support P2P GPUs
int can_access_peer;
if (gpu_p2p_count >= 2)
{
for (int i = 0; i < gpu_p2p_count; i++)
{
for (int j = 0; j < gpu_p2p_count; j++)
{
if (gpuid[i] == gpuid[j])
{
continue;
}
checkCudaErrors(cudaDeviceCanAccessPeer(&can_access_peer, gpuid[i], gpuid[j]));
printf("> Peer access from %s (GPU%d) -> %s (GPU%d) : %s\n", prop[gpuid[i]].name, gpuid[i],
prop[gpuid[j]].name, gpuid[j] ,
can_access_peer ? "Yes" : "No");
}
}
}
}
// csv masterlog info
// *****************************
// exe and CUDA driver name
printf("\n");
std::string sProfileString = "deviceQuery, CUDA Driver = CUDART";
char cTemp[16];
// driver version
sProfileString += ", CUDA Driver Version = ";
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
sprintf_s(cTemp, 10, "%d.%d", driverVersion/1000, (driverVersion%100)/10);
#else
sprintf(cTemp, "%d.%d", driverVersion/1000, (driverVersion%100)/10);
#endif
sProfileString += cTemp;
// Runtime version
sProfileString += ", CUDA Runtime Version = ";
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
sprintf_s(cTemp, 10, "%d.%d", runtimeVersion/1000, (runtimeVersion%100)/10);
#else
sprintf(cTemp, "%d.%d", runtimeVersion/1000, (runtimeVersion%100)/10);
#endif
sProfileString += cTemp;
// Device count
sProfileString += ", NumDevs = ";
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
sprintf_s(cTemp, 10, "%d", deviceCount);
#else
sprintf(cTemp, "%d", deviceCount);
#endif
sProfileString += cTemp;
// Print Out all device Names
for (dev = 0; dev < deviceCount; ++dev)
{
#if defined(WIN32) || defined(_WIN32) || defined(WIN64) || defined(_WIN64)
sprintf_s(cTemp, 13, ", Device%d = ", dev);
#else
sprintf(cTemp, ", Device%d = ", dev);
#endif
cudaDeviceProp deviceProp;
cudaGetDeviceProperties(&deviceProp, dev);
sProfileString += cTemp;
sProfileString += deviceProp.name;
}
sProfileString += "\n";
printf("%s", sProfileString.c_str());
printf("Result = PASS\n");
// finish
exit(EXIT_SUCCESS);
}
void CUT_DEVICE_QUERY()
{
log_printf(INFO,"CUDA Device Query (Runtime API) version (CUDART static linking)\n");
int deviceCount;
cudaGetDeviceCount(&deviceCount);
// This function call returns 0 if there are no CUDA capable devices.
if (deviceCount == 0)
log_printf(INFO,"There is no device supporting CUDA\n");
int dev;
for (dev = 0; dev < deviceCount; ++dev) {
cudaDeviceProp deviceProp;
cudaGetDeviceProperties(&deviceProp, dev);
if (dev == 0) {
// This function call returns 9999 for both major & minor fields, if no CUDA capable devices are present
if (deviceProp.major == 9999 && deviceProp.minor == 9999)
log_printf(INFO,"There is no device supporting CUDA.\n");
else if (deviceCount == 1)
log_printf(INFO,"There is 1 device supporting CUDA\n");
else
log_printf(INFO,"There are %d devices supporting CUDA\n", deviceCount);
}
log_printf(INFO,"\n");
log_printf(INFO,"Device %d: \"%s\"\n", dev, deviceProp.name);
#if CUDART_VERSION >= 2020
int driverVersion = 0, runtimeVersion = 0;
cudaDriverGetVersion(&driverVersion);
log_printf(INFO," CUDA Driver Version: %d.%d\n", driverVersion/1000, driverVersion%100);
cudaRuntimeGetVersion(&runtimeVersion);
log_printf(INFO," CUDA Runtime Version: %d.%d\n", runtimeVersion/1000, runtimeVersion%100);
#endif
log_printf(INFO," CUDA Capability Major revision number: %d\n", deviceProp.major);
log_printf(INFO," CUDA Capability Minor revision number: %d\n", deviceProp.minor);
log_printf(INFO," Total amount of global memory: %u bytes\n", deviceProp.totalGlobalMem);
#if CUDART_VERSION >= 2000
log_printf(INFO," Number of multiprocessors: %d\n", deviceProp.multiProcessorCount);
log_printf(INFO," Number of cores: %d\n", 8 * deviceProp.multiProcessorCount);
#endif
log_printf(INFO," Total amount of constant memory: %u bytes\n", deviceProp.totalConstMem);
log_printf(INFO," Total amount of shared memory per block: %u bytes\n", deviceProp.sharedMemPerBlock);
log_printf(INFO," Total number of registers available per block: %d\n", deviceProp.regsPerBlock);
log_printf(INFO," Warp size: %d\n", deviceProp.warpSize);
log_printf(INFO," Maximum number of threads per block: %d\n", deviceProp.maxThreadsPerBlock);
log_printf(INFO," Maximum sizes of each dimension of a block: %d x %d x %d\n",
deviceProp.maxThreadsDim[0],
deviceProp.maxThreadsDim[1],
deviceProp.maxThreadsDim[2]);
log_printf(INFO," Maximum sizes of each dimension of a grid: %d x %d x %d\n",
deviceProp.maxGridSize[0],
deviceProp.maxGridSize[1],
deviceProp.maxGridSize[2]);
log_printf(INFO," Maximum memory pitch: %u bytes\n", deviceProp.memPitch);
log_printf(INFO," Texture alignment: %u bytes\n", deviceProp.textureAlignment);
log_printf(INFO," Clock rate: %.2f GHz\n", deviceProp.clockRate * 1e-6f);
#if CUDART_VERSION >= 2000
log_printf(INFO," Concurrent copy and execution: %s\n", deviceProp.deviceOverlap ? "Yes" : "No");
#endif
#if CUDART_VERSION >= 2020
log_printf(INFO," Run time limit on kernels: %s\n", deviceProp.kernelExecTimeoutEnabled ? "Yes" : "No");
log_printf(INFO," Integrated: %s\n", deviceProp.integrated ? "Yes" : "No");
log_printf(INFO," Support host page-locked memory mapping: %s\n", deviceProp.canMapHostMemory ? "Yes" : "No");
log_printf(INFO," Compute mode: %s\n", deviceProp.computeMode == cudaComputeModeDefault ?
"Default (multiple host threads can use this device simultaneously)" :
deviceProp.computeMode == cudaComputeModeExclusive ?
"Exclusive (only one host thread at a time can use this device)" :
deviceProp.computeMode == cudaComputeModeProhibited ?
"Prohibited (no host thread can use this device)" :
"Unknown");
#endif
}
}
void pcl::gpu::printCudaDeviceInfo(int device)
{
int count = getCudaEnabledDeviceCount();
bool valid = (device >= 0) && (device < count);
int beg = valid ? device : 0;
int end = valid ? device+1 : count;
printf("*** CUDA Device Query (Runtime API) version (CUDART static linking) *** \n\n");
printf("Device count: %d\n", count);
int driverVersion = 0, runtimeVersion = 0;
cudaSafeCall( cudaDriverGetVersion(&driverVersion) );
cudaSafeCall( cudaRuntimeGetVersion(&runtimeVersion) );
const char *computeMode[] = {
"Default (multiple host threads can use ::cudaSetDevice() with device simultaneously)",
"Exclusive (only one host thread in one process is able to use ::cudaSetDevice() with this device)",
"Prohibited (no host thread can use ::cudaSetDevice() with this device)",
"Exclusive Process (many threads in one process is able to use ::cudaSetDevice() with this device)",
"Unknown",
NULL
};
for(int dev = beg; dev < end; ++dev)
{
cudaDeviceProp prop;
cudaSafeCall( cudaGetDeviceProperties(&prop, dev) );
int sm_cores = convertSMVer2Cores(prop.major, prop.minor);
printf("\nDevice %d: \"%s\"\n", dev, prop.name);
printf(" CUDA Driver Version / Runtime Version %d.%d / %d.%d\n", driverVersion/1000, driverVersion%100, runtimeVersion/1000, runtimeVersion%100);
printf(" CUDA Capability Major/Minor version number: %d.%d\n", prop.major, prop.minor);
printf(" Total amount of global memory: %.0f MBytes (%llu bytes)\n", (float)prop.totalGlobalMem/1048576.0f, (unsigned long long) prop.totalGlobalMem);
printf(" (%2d) Multiprocessors x (%2d) CUDA Cores/MP: %d CUDA Cores\n", prop.multiProcessorCount, sm_cores, sm_cores * prop.multiProcessorCount);
printf(" GPU Clock Speed: %.2f GHz\n", prop.clockRate * 1e-6f);
#if (CUDART_VERSION >= 4000)
// This is not available in the CUDA Runtime API, so we make the necessary calls the driver API to support this for output
int memoryClock, memBusWidth, L2CacheSize;
getCudaAttribute<int>( &memoryClock, CU_DEVICE_ATTRIBUTE_MEMORY_CLOCK_RATE, dev );
getCudaAttribute<int>( &memBusWidth, CU_DEVICE_ATTRIBUTE_GLOBAL_MEMORY_BUS_WIDTH, dev );
getCudaAttribute<int>( &L2CacheSize, CU_DEVICE_ATTRIBUTE_L2_CACHE_SIZE, dev );
printf(" Memory Clock rate: %.2f Mhz\n", memoryClock * 1e-3f);
printf(" Memory Bus Width: %d-bit\n", memBusWidth);
if (L2CacheSize)
printf(" L2 Cache Size: %d bytes\n", L2CacheSize);
printf(" Max Texture Dimension Size (x,y,z) 1D=(%d), 2D=(%d,%d), 3D=(%d,%d,%d)\n",
prop.maxTexture1D, prop.maxTexture2D[0], prop.maxTexture2D[1],
prop.maxTexture3D[0], prop.maxTexture3D[1], prop.maxTexture3D[2]);
printf(" Max Layered Texture Size (dim) x layers 1D=(%d) x %d, 2D=(%d,%d) x %d\n",
prop.maxTexture1DLayered[0], prop.maxTexture1DLayered[1],
prop.maxTexture2DLayered[0], prop.maxTexture2DLayered[1], prop.maxTexture2DLayered[2]);
#endif
printf(" Total amount of constant memory: %u bytes\n", (int)prop.totalConstMem);
printf(" Total amount of shared memory per block: %u bytes\n", (int)prop.sharedMemPerBlock);
printf(" Total number of registers available per block: %d\n", prop.regsPerBlock);
printf(" Warp size: %d\n", prop.warpSize);
printf(" Maximum number of threads per block: %d\n", prop.maxThreadsPerBlock);
printf(" Maximum sizes of each dimension of a block: %d x %d x %d\n", prop.maxThreadsDim[0], prop.maxThreadsDim[1], prop.maxThreadsDim[2]);
printf(" Maximum sizes of each dimension of a grid: %d x %d x %d\n", prop.maxGridSize[0], prop.maxGridSize[1], prop.maxGridSize[2]);
printf(" Maximum memory pitch: %u bytes\n", (int)prop.memPitch);
printf(" Texture alignment: %u bytes\n", (int)prop.textureAlignment);
#if CUDART_VERSION >= 4000
printf(" Concurrent copy and execution: %s with %d copy engine(s)\n", (prop.deviceOverlap ? "Yes" : "No"), prop.asyncEngineCount);
#else
printf(" Concurrent copy and execution: %s\n", prop.deviceOverlap ? "Yes" : "No");
#endif
printf(" Run time limit on kernels: %s\n", prop.kernelExecTimeoutEnabled ? "Yes" : "No");
printf(" Integrated GPU sharing Host Memory: %s\n", prop.integrated ? "Yes" : "No");
printf(" Support host page-locked memory mapping: %s\n", prop.canMapHostMemory ? "Yes" : "No");
printf(" Concurrent kernel execution: %s\n", prop.concurrentKernels ? "Yes" : "No");
printf(" Alignment requirement for Surfaces: %s\n", prop.surfaceAlignment ? "Yes" : "No");
printf(" Device has ECC support enabled: %s\n", prop.ECCEnabled ? "Yes" : "No");
printf(" Device is using TCC driver mode: %s\n", prop.tccDriver ? "Yes" : "No");
#if CUDART_VERSION >= 4000
printf(" Device supports Unified Addressing (UVA): %s\n", prop.unifiedAddressing ? "Yes" : "No");
printf(" Device PCI Bus ID / PCI location ID: %d / %d\n", prop.pciBusID, prop.pciDeviceID );
#endif
printf(" Compute Mode:\n");
printf(" %s \n", computeMode[prop.computeMode]);
}
printf("\n");
printf("deviceQuery, CUDA Driver = CUDART");
printf(", CUDA Driver Version = %d.%d", driverVersion / 1000, driverVersion % 100);
printf(", CUDA Runtime Version = %d.%d", runtimeVersion/1000, runtimeVersion%100);
printf(", NumDevs = %d\n\n", count);
fflush(stdout);
}
// Check if there is a device supporting CUDA
void GetCUDADeviceFlags()
{
int deviceCount;
bool archi_13 = false;
cudaGetDeviceCount(&deviceCount);
// This function call returns 0 if there are no CUDA capable devices.
if (deviceCount == 0)
printf("There is no device supporting CUDA\n");
int dev = 0;
for (dev = 0; dev < 1/*deviceCount/*HACK : we want the first one only for now*/; ++dev) {
printf("\nFirst device is selected by default.\n\n");
cudaDeviceProp deviceProp;
cudaGetDeviceProperties(&deviceProp, dev);
if (dev == 0) {
// This function call returns 9999 for both major & minor fields, if no CUDA capable devices are present
if (deviceProp.major == 9999 && deviceProp.minor == 9999)
printf("There is no device supporting CUDA.\n");
else if (deviceCount == 1)
printf("There is 1 device supporting CUDA\n");
else
printf("There are %d devices supporting CUDA\n", deviceCount);
if ((deviceProp.major * 10 + deviceProp.minor) >= 13 ) {
// OK on peut faire du double et rajouter des optimizations
archi_13 = true;
}
#if CUDART_VERSION >= 2000
if (archi_13){
fb.add_def("MAX_THREADS", deviceProp.multiProcessorCount*1024);
} else {
fb.add_def("MAX_THREADS", deviceProp.multiProcessorCount*768);
}
#endif
fb.add_def("WARP_SIZE", deviceProp.warpSize);
fb.add_flag("USE_CRS_SHARED");
fb.add_flag("USE_TEXTURE");
}
printf("\nDevice %d: \"%s\"\n", dev, deviceProp.name);
#if CUDART_VERSION >= 2020
int driverVersion = 0, runtimeVersion = 0;
cudaDriverGetVersion(&driverVersion);
printf(" CUDA Driver Version: %d.%d\n", driverVersion/1000, driverVersion%100);
cudaRuntimeGetVersion(&runtimeVersion);
printf(" CUDA Runtime Version: %d.%d\n", runtimeVersion/1000, runtimeVersion%100);
#endif
printf(" CUDA Capability Major revision number: %d\n", deviceProp.major);
printf(" CUDA Capability Minor revision number: %d\n", deviceProp.minor);
printf(" Total amount of global memory: %u bytes\n", deviceProp.totalGlobalMem);
#if CUDART_VERSION >= 2000
printf(" Number of multiprocessors: %d\n", deviceProp.multiProcessorCount);
printf(" Number of cores: %d\n", 8 * deviceProp.multiProcessorCount);
#endif
printf(" Total amount of constant memory: %u bytes\n", deviceProp.totalConstMem);
printf(" Total amount of shared memory per block: %u bytes\n", deviceProp.sharedMemPerBlock);
printf(" Total number of registers available per block: %d\n", deviceProp.regsPerBlock);
printf(" Warp size: %d\n", deviceProp.warpSize);
printf(" Warp size: %d\n", deviceProp.warpSize);
printf(" Maximum number of threads per block: %d\n", deviceProp.maxThreadsPerBlock);
printf(" Maximum sizes of each dimension of a block: %d x %d x %d\n",
deviceProp.maxThreadsDim[0],
deviceProp.maxThreadsDim[1],
deviceProp.maxThreadsDim[2]);
printf(" Maximum sizes of each dimension of a grid: %d x %d x %d\n",
deviceProp.maxGridSize[0],
deviceProp.maxGridSize[1],
deviceProp.maxGridSize[2]);
printf(" Maximum memory pitch: %u bytes\n", deviceProp.memPitch);
printf(" Texture alignment: %u bytes\n", deviceProp.textureAlignment);
printf(" Clock rate: %.2f GHz\n", deviceProp.clockRate * 1e-6f);
#if CUDART_VERSION >= 2000
printf(" Concurrent copy and execution: %s\n", deviceProp.deviceOverlap ? "Yes" : "No");
#endif
#if CUDART_VERSION >= 2020
printf(" Run time limit on kernels: %s\n", deviceProp.kernelExecTimeoutEnabled ? "Yes" : "No");
printf(" Integrated: %s\n", deviceProp.integrated ? "Yes" : "No");
printf(" Support host page-locked memory mapping: %s\n", deviceProp.canMapHostMemory ? "Yes" : "No");
printf(" Compute mode: %s\n", deviceProp.computeMode == cudaComputeModeDefault ?
"Default (multiple host threads can use this device simultaneously)" :
deviceProp.computeMode == cudaComputeModeExclusive ?
"Exclusive (only one host thread at a time can use this device)" :
deviceProp.computeMode == cudaComputeModeProhibited ?
"Prohibited (no host thread can use this device)" :
"Unknown");
#endif
}
}
void CudaDeviceDialog::updateInfo(int index) {
m_infoText = "<html><body>";
int deviceCount = 0;
cudaGetDeviceCount(&deviceCount);
cudaDeviceProp p;
cudaGetDeviceProperties(&p, index);
if (p.major == 9999 && p.minor == 9999)
m_infoText += "<p>There is no device supporting CUDA</p>";
else if (deviceCount == 1)
m_infoText += "<p>There is 1 device supporting CUDA</p>";
else
m_infoText += QString("<p>There are %1 devices supporting CUDA</p>").arg(deviceCount);
m_infoText += QString("<p>CUDA Driver/Runtime</p>");
m_infoText += "<table>";
int driverVersion = 0, runtimeVersion = 0;
cudaDriverGetVersion(&driverVersion);
cudaRuntimeGetVersion(&runtimeVersion);
QString error = "<span style='color:red;'>***ERROR*** >= 4.0 required</span>";
addItem(1, "CUDA Driver Version:",
QString("%1.%2 %3").arg(driverVersion/1000).arg(driverVersion%100)
.arg((driverVersion >= 4000)? "" : error));
addItem(1, "CUDA Runtime Version:",
QString("%1.%2 %3").arg(runtimeVersion/1000).arg(runtimeVersion%100)
.arg((driverVersion >= 4000)? "" : error));
m_infoText += "</table>";
if (index < deviceCount) {
m_infoText += QString("<p>Device %1: "%2"</p>").arg(index).arg(p.name);
m_infoText += "<table>";
addItem(1, "CUDA Capability Major/Minor version number:",
QString("%1.%2").arg(p.major).arg(p.minor));
addItem(1, "Total amount of global memory:", QString("%1 MB").arg(p.totalGlobalMem / 1024 / 1024));
addItem(1, QString("%1 Multiprocessors x %2 CUDA Cores/MP:").arg(p.multiProcessorCount).arg(ConvertSMVer2Cores(p.major, p.minor)),
QString("%1 CUDA Cores").arg(ConvertSMVer2Cores(p.major, p.minor) * p.multiProcessorCount));
addItem(1, "Total amount of constant memory:", QString("%1 bytes").arg(p.totalConstMem));
addItem(1, "Total amount of shared memory per block:", QString("%1 bytes").arg(p.sharedMemPerBlock));
addItem(1, "Total number of registers available per block:", QString("%1").arg(p.regsPerBlock));
addItem(1, "Warp size:", QString("%1").arg(p.warpSize));
addItem(1, "Maximum number of threads per block:", QString("%1").arg(p.maxThreadsPerBlock));
addItem(1, "Maximum sizes of each dimension of a block:", QString("%1 x %2 x %3")
.arg(p.maxThreadsDim[0])
.arg(p.maxThreadsDim[1])
.arg(p.maxThreadsDim[2]));
addItem(1, "Maximum sizes of each dimension of a grid:", QString("%1 x %2 x %3")
.arg(p.maxGridSize[0])
.arg(p.maxGridSize[1])
.arg(p.maxGridSize[2]));
addItem(1, "Maximum memory pitch:", QString("%1 bytes").arg(p.memPitch));
addItem(1, "Texture alignment:", QString("%1 bytes").arg(p.textureAlignment));
addItem(1, "Clock rate:", QString("%1 GHz").arg(p.clockRate * 1e-6f));
addItem(1, "Concurrent copy and execution:", p.deviceOverlap ? "yes" : "no");
addItem(1, "# of Asynchronous Copy Engines:", QString("%1").arg(p.asyncEngineCount));
addItem(1, "Run time limit on kernels:", p.kernelExecTimeoutEnabled ? "yes" : "no");
addItem(1, "Integrated:", p.integrated ? "yes" : "no");
addItem(1, "Support host page-locked memory mapping:", p.canMapHostMemory ? "yes" : "no");
addItem(1, "Compute mode:", p.computeMode == cudaComputeModeDefault ?
"Default (multiple host threads can use this device simultaneously)" :
p.computeMode == cudaComputeModeExclusive ?
"Exclusive (only one host thread at a time can use this device)" :
p.computeMode == cudaComputeModeProhibited ?
"Prohibited (no host thread can use this device)" :
"Unknown");
addItem(1, "Concurrent kernel execution:", p.concurrentKernels ? "yes" : "no");
addItem(1, "Device has ECC support enabled:", p.ECCEnabled ? "yes" : "no");
addItem(1, "Device is using TCC driver mode:", p.tccDriver ? "yes" : "no");
m_infoText += "</table>";
}
m_infoText += "</body></html>";
m->info->setHtml(m_infoText);
m->buttonBox->button(QDialogButtonBox::Ok)->setEnabled((driverVersion >= 4000) && (runtimeVersion >= 4000));
}
////////////////////////////////////////////////////////////////////////////////
// Program main
////////////////////////////////////////////////////////////////////////////////
int
main( int argc, char** argv)
{
pArgc = &argc;
pArgv = argv;
/* shrQAStart(argc, argv);
shrSetLogFileName ("deviceQuery.txt");
*/
shrLog("%s Starting...\n\n", argv[0]);
shrLog(" CUDA Device Query (Runtime API) version (CUDART static linking)\n\n");
int deviceCount = 0;
cudaError_t error_id = cudaGetDeviceCount(&deviceCount);
if (error_id != cudaSuccess) {
shrLog( "cudaGetDeviceCount returned %d\n-> %s\n", (int)error_id, cudaGetErrorString(error_id) );
return -1;
}
// This function call returns 0 if there are no CUDA capable devices.
if (deviceCount == 0)
shrLog("There is no device supporting CUDA\n");
else
shrLog("Found %d CUDA Capable device(s)\n", deviceCount);
int dev, driverVersion = 0, runtimeVersion = 0;
for (dev = 0; dev < deviceCount; ++dev) {
cudaDeviceProp deviceProp;
cudaGetDeviceProperties(&deviceProp, dev);
shrLog("\nDevice %d: \"%s\"\n", dev, deviceProp.name);
#if CUDART_VERSION >= 2020
// Console log
cudaDriverGetVersion(&driverVersion);
cudaRuntimeGetVersion(&runtimeVersion);
shrLog(" CUDA Driver Version / Runtime Version %d.%d / %d.%d\n", driverVersion/1000, (driverVersion%100)/10, runtimeVersion/1000, (runtimeVersion%100)/10);
#endif
shrLog(" CUDA Capability Major/Minor version number: %d.%d\n", deviceProp.major, deviceProp.minor);
char msg[256];
sprintf(msg, " Total amount of global memory: %.0f MBytes (%llu bytes)\n",
(float)deviceProp.totalGlobalMem/1048576.0f, (unsigned long long) deviceProp.totalGlobalMem);
shrLog(msg);
#if CUDART_VERSION >= 2000
shrLog(" (%2d) Multiprocessors x (%2d) CUDA Cores/MP: %d CUDA Cores\n",
deviceProp.multiProcessorCount,
ConvertSMVer2Cores(deviceProp.major, deviceProp.minor),
ConvertSMVer2Cores(deviceProp.major, deviceProp.minor) * deviceProp.multiProcessorCount);
#endif
shrLog(" GPU Clock Speed: %.2f GHz\n", deviceProp.clockRate * 1e-6f);
#if CUDART_VERSION >= 4000
// This is not available in the CUDA Runtime API, so we make the necessary calls the driver API to support this for output
int memoryClock;
getCudaAttribute<int>( &memoryClock, CU_DEVICE_ATTRIBUTE_MEMORY_CLOCK_RATE, dev );
shrLog(" Memory Clock rate: %.2f Mhz\n", memoryClock * 1e-3f);
int memBusWidth;
getCudaAttribute<int>( &memBusWidth, CU_DEVICE_ATTRIBUTE_GLOBAL_MEMORY_BUS_WIDTH, dev );
shrLog(" Memory Bus Width: %d-bit\n", memBusWidth);
int L2CacheSize;
getCudaAttribute<int>( &L2CacheSize, CU_DEVICE_ATTRIBUTE_L2_CACHE_SIZE, dev );
if (L2CacheSize) {
shrLog(" L2 Cache Size: %d bytes\n", L2CacheSize);
}
shrLog(" Max Texture Dimension Size (x,y,z) 1D=(%d), 2D=(%d,%d), 3D=(%d,%d,%d)\n",
deviceProp.maxTexture1D, deviceProp.maxTexture2D[0], deviceProp.maxTexture2D[1],
deviceProp.maxTexture3D[0], deviceProp.maxTexture3D[1], deviceProp.maxTexture3D[2]);
shrLog(" Max Layered Texture Size (dim) x layers 1D=(%d) x %d, 2D=(%d,%d) x %d\n",
deviceProp.maxTexture1DLayered[0], deviceProp.maxTexture1DLayered[1],
deviceProp.maxTexture2DLayered[0], deviceProp.maxTexture2DLayered[1], deviceProp.maxTexture2DLayered[2]);
#endif
shrLog(" Total amount of constant memory: %u bytes\n", deviceProp.totalConstMem);
shrLog(" Total amount of shared memory per block: %u bytes\n", deviceProp.sharedMemPerBlock);
shrLog(" Total number of registers available per block: %d\n", deviceProp.regsPerBlock);
shrLog(" Warp size: %d\n", deviceProp.warpSize);
shrLog(" Maximum number of threads per block: %d\n", deviceProp.maxThreadsPerBlock);
shrLog(" Maximum sizes of each dimension of a block: %d x %d x %d\n",
deviceProp.maxThreadsDim[0],
deviceProp.maxThreadsDim[1],
deviceProp.maxThreadsDim[2]);
shrLog(" Maximum sizes of each dimension of a grid: %d x %d x %d\n",
deviceProp.maxGridSize[0],
deviceProp.maxGridSize[1],
deviceProp.maxGridSize[2]);
shrLog(" Maximum memory pitch: %u bytes\n", deviceProp.memPitch);
shrLog(" Texture alignment: %u bytes\n", deviceProp.textureAlignment);
#if CUDART_VERSION >= 4000
shrLog(" Concurrent copy and execution: %s with %d copy engine(s)\n", (deviceProp.deviceOverlap ? "Yes" : "No"), deviceProp.asyncEngineCount);
#else
shrLog(" Concurrent copy and execution: %s\n", deviceProp.deviceOverlap ? "Yes" : "No");
#endif
#if CUDART_VERSION >= 2020
shrLog(" Run time limit on kernels: %s\n", deviceProp.kernelExecTimeoutEnabled ? "Yes" : "No");
shrLog(" Integrated GPU sharing Host Memory: %s\n", deviceProp.integrated ? "Yes" : "No");
shrLog(" Support host page-locked memory mapping: %s\n", deviceProp.canMapHostMemory ? "Yes" : "No");
#endif
#if CUDART_VERSION >= 3000
shrLog(" Concurrent kernel execution: %s\n", deviceProp.concurrentKernels ? "Yes" : "No");
shrLog(" Alignment requirement for Surfaces: %s\n", deviceProp.surfaceAlignment ? "Yes" : "No");
#endif
#if CUDART_VERSION >= 3010
shrLog(" Device has ECC support enabled: %s\n", deviceProp.ECCEnabled ? "Yes" : "No");
#endif
#if CUDART_VERSION >= 3020
shrLog(" Device is using TCC driver mode: %s\n", deviceProp.tccDriver ? "Yes" : "No");
#endif
#if CUDART_VERSION >= 4000
shrLog(" Device supports Unified Addressing (UVA): %s\n", deviceProp.unifiedAddressing ? "Yes" : "No");
shrLog(" Device PCI Bus ID / PCI location ID: %d / %d\n", deviceProp.pciBusID, deviceProp.pciDeviceID );
#endif
#if CUDART_VERSION >= 2020
const char *sComputeMode[] = {
"Default (multiple host threads can use ::cudaSetDevice() with device simultaneously)",
"Exclusive (only one host thread in one process is able to use ::cudaSetDevice() with this device)",
"Prohibited (no host thread can use ::cudaSetDevice() with this device)",
"Exclusive Process (many threads in one process is able to use ::cudaSetDevice() with this device)",
"Unknown",
NULL
};
shrLog(" Compute Mode:\n");
shrLog(" < %s >\n", sComputeMode[deviceProp.computeMode]);
#endif
}
// csv masterlog info
// *****************************
// exe and CUDA driver name
shrLog("\n");
std::string sProfileString = "deviceQuery, CUDA Driver = CUDART";
char cTemp[10];
// driver version
sProfileString += ", CUDA Driver Version = ";
#ifdef WIN32
sprintf_s(cTemp, 10, "%d.%d", driverVersion/1000, (driverVersion%100)/10);
#else
sprintf(cTemp, "%d.%d", driverVersion/1000, (driverVersion%100)/10);
#endif
sProfileString += cTemp;
// Runtime version
sProfileString += ", CUDA Runtime Version = ";
#ifdef WIN32
sprintf_s(cTemp, 10, "%d.%d", runtimeVersion/1000, (runtimeVersion%100)/10);
#else
sprintf(cTemp, "%d.%d", runtimeVersion/1000, (runtimeVersion%100)/10);
#endif
sProfileString += cTemp;
// Device count
sProfileString += ", NumDevs = ";
#ifdef WIN32
sprintf_s(cTemp, 10, "%d", deviceCount);
#else
sprintf(cTemp, "%d", deviceCount);
#endif
sProfileString += cTemp;
// First 2 device names, if any
for (dev = 0; dev < ((deviceCount > 2) ? 2 : deviceCount); ++dev)
{
cudaDeviceProp deviceProp;
cudaGetDeviceProperties(&deviceProp, dev);
sProfileString += ", Device = ";
sProfileString += deviceProp.name;
}
sProfileString += "\n";
//shrLogEx(LOGBOTH | MASTER, 0, sProfileString.c_str());
std::cout << sProfileString.c_str() << std::endl;
std::cout << "Press <ENTER>" << std::endl;
//
getchar();
runtimeTest();
getchar();
// finish
return 0;
}
void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[]) {
//if (nrhs != 1)
// mexErrMsgTxt("Wrong number of arguments");
//int dev = (int) mxGetScalar(prhs[0]);
int deviceCount;
cudaGetDeviceCount(&deviceCount);
// This function call returns 0 if there are no CUDA capable devices.
if (deviceCount == 0)
mexErrMsgTxt("There is no device supporting CUDA\n");
int dev;
int devStart = 0;
int devStop = deviceCount;
if (nrhs==1) {
devStart = (int) mxGetScalar(prhs[0]);
devStop = devStart+1;
if (devStart >= deviceCount)
mexErrMsgTxt("Please specify a valid GPU device.\n");
}
for (dev = devStart; dev < devStop; ++dev) {
cudaDeviceProp deviceProp;
cudaGetDeviceProperties(&deviceProp, dev);
if (dev == devStart) {
// This function call returns 9999 for both major & minor fields, if no CUDA capable devices are present
if (deviceProp.major == 9999 && deviceProp.minor == 9999)
mexErrMsgTxt("There is no device supporting CUDA.\n");
else if (deviceCount == 1)
printf("There is 1 device supporting CUDA\n");
else
printf("There are %d devices supporting CUDA\n", deviceCount);
#if CUDART_VERSION >= 2020
int driverVersion = 0, runtimeVersion = 0;
cudaDriverGetVersion(&driverVersion);
printf("CUDA Driver Version: %d.%d\n", driverVersion/1000, driverVersion%100);
cudaRuntimeGetVersion(&runtimeVersion);
printf("CUDA Runtime Version: %d.%d\n", runtimeVersion/1000, runtimeVersion%100);
#endif
}
printf("\nDevice %d: \"%s\"\n", dev, deviceProp.name);
printf(" CUDA Capability Major revision number: %d\n",
deviceProp.major);
printf(" CUDA Capability Minor revision number: %d\n",
deviceProp.minor);
printf(" Total amount of global memory: %u bytes\n",
deviceProp.totalGlobalMem);
//#if CUDART_VERSION >= 2000
// printf(" Number of multiprocessors: %d\n",
// deviceProp.multiProcessorCount);
// printf(" Number of cores: %d\n", 8
// * deviceProp.multiProcessorCount);
//#endif
printf(" Total amount of constant memory: %u bytes\n",
deviceProp.totalConstMem);
printf(" Total amount of shared memory per block: %u bytes\n",
deviceProp.sharedMemPerBlock);
printf(" Total number of registers available per block: %d\n",
deviceProp.regsPerBlock);
printf(" Warp size: %d\n",
deviceProp.warpSize);
printf(" Maximum number of threads per block: %d\n",
deviceProp.maxThreadsPerBlock);
printf(" Maximum sizes of each dimension of a block: %d x %d x %d\n",
deviceProp.maxThreadsDim[0], deviceProp.maxThreadsDim[1],
deviceProp.maxThreadsDim[2]);
printf(" Maximum sizes of each dimension of a grid: %d x %d x %d\n",
deviceProp.maxGridSize[0], deviceProp.maxGridSize[1],
deviceProp.maxGridSize[2]);
printf(" Maximum memory pitch: %u bytes\n",
deviceProp.memPitch);
printf(" Texture alignment: %u bytes\n",
deviceProp.textureAlignment);
printf(" Clock rate: %.2f GHz\n",
deviceProp.clockRate * 1e-6f);
#if CUDART_VERSION >= 2000
printf(" Concurrent copy and execution: %s\n",
deviceProp.deviceOverlap ? "Yes" : "No");
#endif
#if CUDART_VERSION >= 2020
printf(" Run time limit on kernels: %s\n", deviceProp.kernelExecTimeoutEnabled ? "Yes" : "No");
printf(" Integrated: %s\n", deviceProp.integrated ? "Yes" : "No");
printf(" Support host page-locked memory mapping: %s\n", deviceProp.canMapHostMemory ? "Yes" : "No");
printf(" Compute mode: %s\n", deviceProp.computeMode == cudaComputeModeDefault ?
"Default (multiple host threads can use this device simultaneously)" :
deviceProp.computeMode == cudaComputeModeExclusive ?
"Exclusive (only one host thread at a time can use this device)" :
deviceProp.computeMode == cudaComputeModeProhibited ?
"Prohibited (no host thread can use this device)" :
"Unknown");
#endif
}
}
