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opencv/modules/core/src/cuda_info.cpp

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's 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.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "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 Intel Corporation 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.
//
//M*/
#include "precomp.hpp"
using namespace cv;
using namespace cv::cuda;
int cv::cuda::getCudaEnabledDeviceCount()
{
#ifndef HAVE_CUDA
return 0;
#else
int count;
cudaError_t error = cudaGetDeviceCount(&count);
if (error == cudaErrorInsufficientDriver)
return -1;
if (error == cudaErrorNoDevice)
return 0;
cudaSafeCall( error );
return count;
#endif
}
void cv::cuda::setDevice(int device)
{
#ifndef HAVE_CUDA
CV_UNUSED(device);
throw_no_cuda();
#else
cudaSafeCall( cudaSetDevice(device) );
cudaSafeCall( cudaFree(0) );
#endif
}
int cv::cuda::getDevice()
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
int device;
cudaSafeCall( cudaGetDevice(&device) );
return device;
#endif
}
void cv::cuda::resetDevice()
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
cudaSafeCall( cudaDeviceReset() );
#endif
}
bool cv::cuda::deviceSupports(FeatureSet feature_set)
{
#ifndef HAVE_CUDA
CV_UNUSED(feature_set);
throw_no_cuda();
#else
static int versions[] =
{
-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1
};
static const int cache_size = static_cast<int>(sizeof(versions) / sizeof(versions[0]));
const int devId = getDevice();
int version;
if (devId < cache_size && versions[devId] >= 0)
{
version = versions[devId];
}
else
{
DeviceInfo dev(devId);
version = dev.majorVersion() * 10 + dev.minorVersion();
if (devId < cache_size)
versions[devId] = version;
}
return TargetArchs::builtWith(feature_set) && (version >= feature_set);
#endif
}
////////////////////////////////////////////////////////////////////////
// TargetArchs
#ifdef HAVE_CUDA
namespace
{
class CudaArch
{
public:
CudaArch();
bool builtWith(FeatureSet feature_set) const;
bool hasPtx(int major, int minor) const;
bool hasBin(int major, int minor) const;
bool hasEqualOrLessPtx(int major, int minor) const;
bool hasEqualOrGreaterPtx(int major, int minor) const;
bool hasEqualOrGreaterBin(int major, int minor) const;
private:
static void fromStr(const char* set_as_str, std::vector<int>& arr);
std::vector<int> bin;
std::vector<int> ptx;
std::vector<int> features;
};
const CudaArch cudaArch;
CudaArch::CudaArch()
{
fromStr(CUDA_ARCH_BIN, bin);
fromStr(CUDA_ARCH_PTX, ptx);
fromStr(CUDA_ARCH_FEATURES, features);
}
bool CudaArch::builtWith(FeatureSet feature_set) const
{
return !features.empty() && (features.back() >= feature_set);
}
bool CudaArch::hasPtx(int major, int minor) const
{
return std::find(ptx.begin(), ptx.end(), major * 10 + minor) != ptx.end();
}
bool CudaArch::hasBin(int major, int minor) const
{
return std::find(bin.begin(), bin.end(), major * 10 + minor) != bin.end();
}
bool CudaArch::hasEqualOrLessPtx(int major, int minor) const
{
return !ptx.empty() && (ptx.front() <= major * 10 + minor);
}
bool CudaArch::hasEqualOrGreaterPtx(int major, int minor) const
{
return !ptx.empty() && (ptx.back() >= major * 10 + minor);
}
bool CudaArch::hasEqualOrGreaterBin(int major, int minor) const
{
return !bin.empty() && (bin.back() >= major * 10 + minor);
}
void CudaArch::fromStr(const char* set_as_str, std::vector<int>& arr)
{
arr.clear();
const size_t len = strlen(set_as_str);
size_t pos = 0;
while (pos < len)
{
if (isspace(set_as_str[pos]))
{
++pos;
}
else
{
int cur_value;
int chars_read;
int args_read = sscanf(set_as_str + pos, "%d%n", &cur_value, &chars_read);
CV_Assert( args_read == 1 );
arr.push_back(cur_value);
pos += chars_read;
}
}
std::sort(arr.begin(), arr.end());
}
}
#endif
bool cv::cuda::TargetArchs::builtWith(cv::cuda::FeatureSet feature_set)
{
#ifndef HAVE_CUDA
CV_UNUSED(feature_set);
throw_no_cuda();
#else
return cudaArch.builtWith(feature_set);
#endif
}
bool cv::cuda::TargetArchs::hasPtx(int major, int minor)
{
#ifndef HAVE_CUDA
CV_UNUSED(major);
CV_UNUSED(minor);
throw_no_cuda();
#else
return cudaArch.hasPtx(major, minor);
#endif
}
bool cv::cuda::TargetArchs::hasBin(int major, int minor)
{
#ifndef HAVE_CUDA
CV_UNUSED(major);
CV_UNUSED(minor);
throw_no_cuda();
#else
return cudaArch.hasBin(major, minor);
#endif
}
bool cv::cuda::TargetArchs::hasEqualOrLessPtx(int major, int minor)
{
#ifndef HAVE_CUDA
CV_UNUSED(major);
CV_UNUSED(minor);
throw_no_cuda();
#else
return cudaArch.hasEqualOrLessPtx(major, minor);
#endif
}
bool cv::cuda::TargetArchs::hasEqualOrGreaterPtx(int major, int minor)
{
#ifndef HAVE_CUDA
CV_UNUSED(major);
CV_UNUSED(minor);
throw_no_cuda();
#else
return cudaArch.hasEqualOrGreaterPtx(major, minor);
#endif
}
bool cv::cuda::TargetArchs::hasEqualOrGreaterBin(int major, int minor)
{
#ifndef HAVE_CUDA
CV_UNUSED(major);
CV_UNUSED(minor);
throw_no_cuda();
#else
return cudaArch.hasEqualOrGreaterBin(major, minor);
#endif
}
////////////////////////////////////////////////////////////////////////
// DeviceInfo
#ifdef HAVE_CUDA
namespace
{
class DeviceProps
{
public:
DeviceProps();
const cudaDeviceProp* get(int devID) const;
private:
std::vector<cudaDeviceProp> props_;
};
DeviceProps::DeviceProps()
{
int count = getCudaEnabledDeviceCount();
if (count > 0)
{
props_.resize(count);
for (int devID = 0; devID < count; ++devID)
{
cudaSafeCall( cudaGetDeviceProperties(&props_[devID], devID) );
}
}
}
const cudaDeviceProp* DeviceProps::get(int devID) const
{
CV_Assert( static_cast<size_t>(devID) < props_.size() );
return &props_[devID];
}
DeviceProps& deviceProps()
{
static DeviceProps props;
return props;
}
}
#endif
const char* cv::cuda::DeviceInfo::name() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->name;
#endif
}
size_t cv::cuda::DeviceInfo::totalGlobalMem() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->totalGlobalMem;
#endif
}
size_t cv::cuda::DeviceInfo::sharedMemPerBlock() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->sharedMemPerBlock;
#endif
}
int cv::cuda::DeviceInfo::regsPerBlock() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->regsPerBlock;
#endif
}
int cv::cuda::DeviceInfo::warpSize() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->warpSize;
#endif
}
size_t cv::cuda::DeviceInfo::memPitch() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->memPitch;
#endif
}
int cv::cuda::DeviceInfo::maxThreadsPerBlock() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->maxThreadsPerBlock;
#endif
}
Vec3i cv::cuda::DeviceInfo::maxThreadsDim() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return Vec3i(deviceProps().get(device_id_)->maxThreadsDim);
#endif
}
Vec3i cv::cuda::DeviceInfo::maxGridSize() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return Vec3i(deviceProps().get(device_id_)->maxGridSize);
#endif
}
int cv::cuda::DeviceInfo::clockRate() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->clockRate;
#endif
}
size_t cv::cuda::DeviceInfo::totalConstMem() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->totalConstMem;
#endif
}
int cv::cuda::DeviceInfo::majorVersion() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->major;
#endif
}
int cv::cuda::DeviceInfo::minorVersion() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->minor;
#endif
}
size_t cv::cuda::DeviceInfo::textureAlignment() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->textureAlignment;
#endif
}
size_t cv::cuda::DeviceInfo::texturePitchAlignment() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->texturePitchAlignment;
#endif
}
int cv::cuda::DeviceInfo::multiProcessorCount() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->multiProcessorCount;
#endif
}
bool cv::cuda::DeviceInfo::kernelExecTimeoutEnabled() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->kernelExecTimeoutEnabled != 0;
#endif
}
bool cv::cuda::DeviceInfo::integrated() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->integrated != 0;
#endif
}
bool cv::cuda::DeviceInfo::canMapHostMemory() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->canMapHostMemory != 0;
#endif
}
DeviceInfo::ComputeMode cv::cuda::DeviceInfo::computeMode() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
static const ComputeMode tbl[] =
{
ComputeModeDefault,
ComputeModeExclusive,
ComputeModeProhibited,
ComputeModeExclusiveProcess
};
return tbl[deviceProps().get(device_id_)->computeMode];
#endif
}
int cv::cuda::DeviceInfo::maxTexture1D() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->maxTexture1D;
#endif
}
int cv::cuda::DeviceInfo::maxTexture1DMipmap() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
#if CUDA_VERSION >= 5000
return deviceProps().get(device_id_)->maxTexture1DMipmap;
#else
CV_Error(Error::StsNotImplemented, "This function requires CUDA 5.0");
return 0;
#endif
#endif
}
int cv::cuda::DeviceInfo::maxTexture1DLinear() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->maxTexture1DLinear;
#endif
}
Vec2i cv::cuda::DeviceInfo::maxTexture2D() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return Vec2i(deviceProps().get(device_id_)->maxTexture2D);
#endif
}
Vec2i cv::cuda::DeviceInfo::maxTexture2DMipmap() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
#if CUDA_VERSION >= 5000
return Vec2i(deviceProps().get(device_id_)->maxTexture2DMipmap);
#else
CV_Error(Error::StsNotImplemented, "This function requires CUDA 5.0");
return Vec2i();
#endif
#endif
}
Vec3i cv::cuda::DeviceInfo::maxTexture2DLinear() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return Vec3i(deviceProps().get(device_id_)->maxTexture2DLinear);
#endif
}
Vec2i cv::cuda::DeviceInfo::maxTexture2DGather() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return Vec2i(deviceProps().get(device_id_)->maxTexture2DGather);
#endif
}
Vec3i cv::cuda::DeviceInfo::maxTexture3D() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return Vec3i(deviceProps().get(device_id_)->maxTexture3D);
#endif
}
int cv::cuda::DeviceInfo::maxTextureCubemap() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->maxTextureCubemap;
#endif
}
Vec2i cv::cuda::DeviceInfo::maxTexture1DLayered() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return Vec2i(deviceProps().get(device_id_)->maxTexture1DLayered);
#endif
}
Vec3i cv::cuda::DeviceInfo::maxTexture2DLayered() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return Vec3i(deviceProps().get(device_id_)->maxTexture2DLayered);
#endif
}
Vec2i cv::cuda::DeviceInfo::maxTextureCubemapLayered() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return Vec2i(deviceProps().get(device_id_)->maxTextureCubemapLayered);
#endif
}
int cv::cuda::DeviceInfo::maxSurface1D() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->maxSurface1D;
#endif
}
Vec2i cv::cuda::DeviceInfo::maxSurface2D() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return Vec2i(deviceProps().get(device_id_)->maxSurface2D);
#endif
}
Vec3i cv::cuda::DeviceInfo::maxSurface3D() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return Vec3i(deviceProps().get(device_id_)->maxSurface3D);
#endif
}
Vec2i cv::cuda::DeviceInfo::maxSurface1DLayered() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return Vec2i(deviceProps().get(device_id_)->maxSurface1DLayered);
#endif
}
Vec3i cv::cuda::DeviceInfo::maxSurface2DLayered() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return Vec3i(deviceProps().get(device_id_)->maxSurface2DLayered);
#endif
}
int cv::cuda::DeviceInfo::maxSurfaceCubemap() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->maxSurfaceCubemap;
#endif
}
Vec2i cv::cuda::DeviceInfo::maxSurfaceCubemapLayered() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return Vec2i(deviceProps().get(device_id_)->maxSurfaceCubemapLayered);
#endif
}
size_t cv::cuda::DeviceInfo::surfaceAlignment() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->surfaceAlignment;
#endif
}
bool cv::cuda::DeviceInfo::concurrentKernels() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->concurrentKernels != 0;
#endif
}
bool cv::cuda::DeviceInfo::ECCEnabled() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->ECCEnabled != 0;
#endif
}
int cv::cuda::DeviceInfo::pciBusID() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->pciBusID;
#endif
}
int cv::cuda::DeviceInfo::pciDeviceID() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->pciDeviceID;
#endif
}
int cv::cuda::DeviceInfo::pciDomainID() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->pciDomainID;
#endif
}
bool cv::cuda::DeviceInfo::tccDriver() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->tccDriver != 0;
#endif
}
int cv::cuda::DeviceInfo::asyncEngineCount() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->asyncEngineCount;
#endif
}
bool cv::cuda::DeviceInfo::unifiedAddressing() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->unifiedAddressing != 0;
#endif
}
int cv::cuda::DeviceInfo::memoryClockRate() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->memoryClockRate;
#endif
}
int cv::cuda::DeviceInfo::memoryBusWidth() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->memoryBusWidth;
#endif
}
int cv::cuda::DeviceInfo::l2CacheSize() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->l2CacheSize;
#endif
}
int cv::cuda::DeviceInfo::maxThreadsPerMultiProcessor() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
return deviceProps().get(device_id_)->maxThreadsPerMultiProcessor;
#endif
}
void cv::cuda::DeviceInfo::queryMemory(size_t& _totalMemory, size_t& _freeMemory) const
{
#ifndef HAVE_CUDA
CV_UNUSED(_totalMemory);
CV_UNUSED(_freeMemory);
throw_no_cuda();
#else
int prevDeviceID = getDevice();
if (prevDeviceID != device_id_)
setDevice(device_id_);
cudaSafeCall( cudaMemGetInfo(&_freeMemory, &_totalMemory) );
if (prevDeviceID != device_id_)
setDevice(prevDeviceID);
#endif
}
bool cv::cuda::DeviceInfo::isCompatible() const
{
#ifndef HAVE_CUDA
throw_no_cuda();
#else
// Check PTX compatibility
if (TargetArchs::hasEqualOrLessPtx(majorVersion(), minorVersion()))
return true;
// Check BIN compatibility
for (int i = minorVersion(); i >= 0; --i)
if (TargetArchs::hasBin(majorVersion(), i))
return true;
return false;
#endif
}
////////////////////////////////////////////////////////////////////////
// print info
#ifdef HAVE_CUDA
namespace
{
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 (hexadecimal notation), M = SM Major version, and m = SM minor version
int Cores;
} SMtoCores;
SMtoCores gpuArchCoresPerSM[] = { { 0x10, 8 }, { 0x11, 8 }, { 0x12, 8 }, { 0x13, 8 }, { 0x20, 32 }, { 0x21, 48 }, {0x30, 192}, {0x35, 192}, { -1, -1 } };
int index = 0;
while (gpuArchCoresPerSM[index].SM != -1)
{
if (gpuArchCoresPerSM[index].SM == ((major << 4) + minor) )
return gpuArchCoresPerSM[index].Cores;
index++;
}
return -1;
}
}
#endif
void cv::cuda::printCudaDeviceInfo(int device)
{
#ifndef HAVE_CUDA
CV_UNUSED(device);
throw_no_cuda();
#else
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) );
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);
int cores = convertSMVer2Cores(prop.major, prop.minor);
if (cores > 0)
printf(" (%2d) Multiprocessors x (%2d) CUDA Cores/MP: %d CUDA Cores\n", prop.multiProcessorCount, cores, cores * prop.multiProcessorCount);
printf(" GPU Clock Speed: %.2f GHz\n", prop.clockRate * 1e-6f);
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]);
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);
printf(" Concurrent copy and execution: %s with %d copy engine(s)\n", (prop.deviceOverlap ? "Yes" : "No"), prop.asyncEngineCount);
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");
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 );
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);
#endif
}
void cv::cuda::printShortCudaDeviceInfo(int device)
{
#ifndef HAVE_CUDA
CV_UNUSED(device);
throw_no_cuda();
#else
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 ? " (not Fermi)" : "";
printf("Device %d: \"%s\" %.0fMb", dev, prop.name, (float)prop.totalGlobalMem/1048576.0f);
printf(", sm_%d%d%s", prop.major, prop.minor, arch_str);
int cores = convertSMVer2Cores(prop.major, prop.minor);
if (cores > 0)
printf(", %d cores", cores * prop.multiProcessorCount);
printf(", Driver/Runtime ver.%d.%d/%d.%d\n", driverVersion/1000, driverVersion%100, runtimeVersion/1000, runtimeVersion%100);
}
fflush(stdout);
#endif
}
////////////////////////////////////////////////////////////////////////
// Error handling
#ifdef HAVE_CUDA
namespace
{
#define error_entry(entry) { entry, #entry }
struct ErrorEntry
{
int code;
const char* str;
};
struct ErrorEntryComparer
{
int code;
ErrorEntryComparer(int code_) : code(code_) {}
bool operator()(const ErrorEntry& e) const { return e.code == code; }
};
const ErrorEntry npp_errors [] =
{
#if defined (_MSC_VER)
error_entry( NPP_NOT_SUFFICIENT_COMPUTE_CAPABILITY ),
#endif
#if NPP_VERSION < 5500
error_entry( NPP_BAD_ARG_ERROR ),
error_entry( NPP_COEFF_ERROR ),
error_entry( NPP_RECT_ERROR ),
error_entry( NPP_QUAD_ERROR ),
error_entry( NPP_MEMFREE_ERR ),
error_entry( NPP_MEMSET_ERR ),
error_entry( NPP_MEM_ALLOC_ERR ),
error_entry( NPP_HISTO_NUMBER_OF_LEVELS_ERROR ),
error_entry( NPP_MIRROR_FLIP_ERR ),
error_entry( NPP_INVALID_INPUT ),
error_entry( NPP_POINTER_ERROR ),
error_entry( NPP_WARNING ),
error_entry( NPP_ODD_ROI_WARNING ),
#else
error_entry( NPP_INVALID_HOST_POINTER_ERROR ),
error_entry( NPP_INVALID_DEVICE_POINTER_ERROR ),
error_entry( NPP_LUT_PALETTE_BITSIZE_ERROR ),
error_entry( NPP_ZC_MODE_NOT_SUPPORTED_ERROR ),
error_entry( NPP_MEMFREE_ERROR ),
error_entry( NPP_MEMSET_ERROR ),
error_entry( NPP_QUALITY_INDEX_ERROR ),
error_entry( NPP_HISTOGRAM_NUMBER_OF_LEVELS_ERROR ),
error_entry( NPP_CHANNEL_ORDER_ERROR ),
error_entry( NPP_ZERO_MASK_VALUE_ERROR ),
error_entry( NPP_QUADRANGLE_ERROR ),
error_entry( NPP_RECTANGLE_ERROR ),
error_entry( NPP_COEFFICIENT_ERROR ),
error_entry( NPP_NUMBER_OF_CHANNELS_ERROR ),
error_entry( NPP_COI_ERROR ),
error_entry( NPP_DIVISOR_ERROR ),
error_entry( NPP_CHANNEL_ERROR ),
error_entry( NPP_STRIDE_ERROR ),
error_entry( NPP_ANCHOR_ERROR ),
error_entry( NPP_MASK_SIZE_ERROR ),
error_entry( NPP_MIRROR_FLIP_ERROR ),
error_entry( NPP_MOMENT_00_ZERO_ERROR ),
error_entry( NPP_THRESHOLD_NEGATIVE_LEVEL_ERROR ),
error_entry( NPP_THRESHOLD_ERROR ),
error_entry( NPP_CONTEXT_MATCH_ERROR ),
error_entry( NPP_FFT_FLAG_ERROR ),
error_entry( NPP_FFT_ORDER_ERROR ),
error_entry( NPP_SCALE_RANGE_ERROR ),
error_entry( NPP_DATA_TYPE_ERROR ),
error_entry( NPP_OUT_OFF_RANGE_ERROR ),
error_entry( NPP_DIVIDE_BY_ZERO_ERROR ),
error_entry( NPP_MEMORY_ALLOCATION_ERR ),
error_entry( NPP_RANGE_ERROR ),
error_entry( NPP_BAD_ARGUMENT_ERROR ),
error_entry( NPP_NO_MEMORY_ERROR ),
error_entry( NPP_ERROR_RESERVED ),
error_entry( NPP_NO_OPERATION_WARNING ),
error_entry( NPP_DIVIDE_BY_ZERO_WARNING ),
error_entry( NPP_WRONG_INTERSECTION_ROI_WARNING ),
#endif
error_entry( NPP_NOT_SUPPORTED_MODE_ERROR ),
error_entry( NPP_ROUND_MODE_NOT_SUPPORTED_ERROR ),
error_entry( NPP_RESIZE_NO_OPERATION_ERROR ),
error_entry( NPP_LUT_NUMBER_OF_LEVELS_ERROR ),
error_entry( NPP_TEXTURE_BIND_ERROR ),
error_entry( NPP_WRONG_INTERSECTION_ROI_ERROR ),
error_entry( NPP_NOT_EVEN_STEP_ERROR ),
error_entry( NPP_INTERPOLATION_ERROR ),
error_entry( NPP_RESIZE_FACTOR_ERROR ),
error_entry( NPP_HAAR_CLASSIFIER_PIXEL_MATCH_ERROR ),
error_entry( NPP_MEMCPY_ERROR ),
error_entry( NPP_ALIGNMENT_ERROR ),
error_entry( NPP_STEP_ERROR ),
error_entry( NPP_SIZE_ERROR ),
error_entry( NPP_NULL_POINTER_ERROR ),
error_entry( NPP_CUDA_KERNEL_EXECUTION_ERROR ),
error_entry( NPP_NOT_IMPLEMENTED_ERROR ),
error_entry( NPP_ERROR ),
error_entry( NPP_NO_ERROR ),
error_entry( NPP_SUCCESS ),
error_entry( NPP_WRONG_INTERSECTION_QUAD_WARNING ),
error_entry( NPP_MISALIGNED_DST_ROI_WARNING ),
error_entry( NPP_AFFINE_QUAD_INCORRECT_WARNING ),
error_entry( NPP_DOUBLE_SIZE_WARNING )
};
const size_t npp_error_num = sizeof(npp_errors) / sizeof(npp_errors[0]);
const ErrorEntry cu_errors [] =
{
error_entry( CUDA_SUCCESS ),
error_entry( CUDA_ERROR_INVALID_VALUE ),
error_entry( CUDA_ERROR_OUT_OF_MEMORY ),
error_entry( CUDA_ERROR_NOT_INITIALIZED ),
error_entry( CUDA_ERROR_DEINITIALIZED ),
error_entry( CUDA_ERROR_PROFILER_DISABLED ),
error_entry( CUDA_ERROR_PROFILER_NOT_INITIALIZED ),
error_entry( CUDA_ERROR_PROFILER_ALREADY_STARTED ),
error_entry( CUDA_ERROR_PROFILER_ALREADY_STOPPED ),
error_entry( CUDA_ERROR_NO_DEVICE ),
error_entry( CUDA_ERROR_INVALID_DEVICE ),
error_entry( CUDA_ERROR_INVALID_IMAGE ),
error_entry( CUDA_ERROR_INVALID_CONTEXT ),
error_entry( CUDA_ERROR_CONTEXT_ALREADY_CURRENT ),
error_entry( CUDA_ERROR_MAP_FAILED ),
error_entry( CUDA_ERROR_UNMAP_FAILED ),
error_entry( CUDA_ERROR_ARRAY_IS_MAPPED ),
error_entry( CUDA_ERROR_ALREADY_MAPPED ),
error_entry( CUDA_ERROR_NO_BINARY_FOR_GPU ),
error_entry( CUDA_ERROR_ALREADY_ACQUIRED ),
error_entry( CUDA_ERROR_NOT_MAPPED ),
error_entry( CUDA_ERROR_NOT_MAPPED_AS_ARRAY ),
error_entry( CUDA_ERROR_NOT_MAPPED_AS_POINTER ),
error_entry( CUDA_ERROR_ECC_UNCORRECTABLE ),
error_entry( CUDA_ERROR_UNSUPPORTED_LIMIT ),
error_entry( CUDA_ERROR_CONTEXT_ALREADY_IN_USE ),
error_entry( CUDA_ERROR_INVALID_SOURCE ),
error_entry( CUDA_ERROR_FILE_NOT_FOUND ),
error_entry( CUDA_ERROR_SHARED_OBJECT_SYMBOL_NOT_FOUND ),
error_entry( CUDA_ERROR_SHARED_OBJECT_INIT_FAILED ),
error_entry( CUDA_ERROR_OPERATING_SYSTEM ),
error_entry( CUDA_ERROR_INVALID_HANDLE ),
error_entry( CUDA_ERROR_NOT_FOUND ),
error_entry( CUDA_ERROR_NOT_READY ),
error_entry( CUDA_ERROR_LAUNCH_FAILED ),
error_entry( CUDA_ERROR_LAUNCH_OUT_OF_RESOURCES ),
error_entry( CUDA_ERROR_LAUNCH_TIMEOUT ),
error_entry( CUDA_ERROR_LAUNCH_INCOMPATIBLE_TEXTURING ),
error_entry( CUDA_ERROR_PEER_ACCESS_ALREADY_ENABLED ),
error_entry( CUDA_ERROR_PEER_ACCESS_NOT_ENABLED ),
error_entry( CUDA_ERROR_PRIMARY_CONTEXT_ACTIVE ),
error_entry( CUDA_ERROR_CONTEXT_IS_DESTROYED ),
error_entry( CUDA_ERROR_ASSERT ),
error_entry( CUDA_ERROR_TOO_MANY_PEERS ),
error_entry( CUDA_ERROR_HOST_MEMORY_ALREADY_REGISTERED ),
error_entry( CUDA_ERROR_HOST_MEMORY_NOT_REGISTERED ),
error_entry( CUDA_ERROR_UNKNOWN )
};
const size_t cu_errors_num = sizeof(cu_errors) / sizeof(cu_errors[0]);
cv::String getErrorString(int code, const ErrorEntry* errors, size_t n)
{
size_t idx = std::find_if(errors, errors + n, ErrorEntryComparer(code)) - errors;
const char* msg = (idx != n) ? errors[idx].str : "Unknown error code";
cv::String str = cv::format("%s [Code = %d]", msg, code);
return str;
}
}
#endif
String cv::cuda::getNppErrorMessage(int code)
{
#ifndef HAVE_CUDA
CV_UNUSED(code);
return String();
#else
return getErrorString(code, npp_errors, npp_error_num);
#endif
}
String cv::cuda::getCudaDriverApiErrorMessage(int code)
{
#ifndef HAVE_CUDA
CV_UNUSED(code);
return String();
#else
return getErrorString(code, cu_errors, cu_errors_num);
#endif
}