139 lines
3.4 KiB
C++
139 lines
3.4 KiB
C++
/* This sample demonstrates the way you can perform independed tasks
|
|
on the different GPUs */
|
|
|
|
// Disable some warnings which are caused with CUDA headers
|
|
#if defined(_MSC_VER)
|
|
#pragma warning(disable: 4201 4408 4100)
|
|
#endif
|
|
|
|
#include <iostream>
|
|
#include "opencv2/core/core.hpp"
|
|
#include "opencv2/gpu/gpu.hpp"
|
|
|
|
#if defined(__arm__)
|
|
int main()
|
|
{
|
|
std::cout << "Unsupported for ARM CUDA library." << std::endl;
|
|
return 0;
|
|
}
|
|
#else
|
|
|
|
#include <cuda.h>
|
|
#include <cuda_runtime.h>
|
|
|
|
using namespace std;
|
|
using namespace cv;
|
|
using namespace cv::gpu;
|
|
|
|
#define safeCall(expr) safeCall_(expr, #expr, __FILE__, __LINE__)
|
|
inline void safeCall_(int code, const char* expr, const char* file, int line)
|
|
{
|
|
if (code != CUDA_SUCCESS)
|
|
{
|
|
std::cout << "CUDA driver API error: code " << code << ", expr " << expr
|
|
<< ", file " << file << ", line " << line << endl;
|
|
exit(-1);
|
|
}
|
|
}
|
|
|
|
struct Worker: public ParallelLoopBody
|
|
{
|
|
Worker(int num_devices)
|
|
{
|
|
count = num_devices;
|
|
contexts = new CUcontext[num_devices];
|
|
for (int device_id = 0; device_id < num_devices; device_id++)
|
|
{
|
|
CUdevice device;
|
|
safeCall(cuDeviceGet(&device, device_id));
|
|
safeCall(cuCtxCreate(&contexts[device_id], 0, device));
|
|
}
|
|
}
|
|
|
|
virtual void operator() (const Range& range) const
|
|
{
|
|
for (int device_id = range.start; device_id != range.end; ++device_id)
|
|
{
|
|
// Set the proper context
|
|
safeCall(cuCtxPushCurrent(contexts[device_id]));
|
|
|
|
Mat src(1000, 1000, CV_32F);
|
|
Mat dst;
|
|
|
|
RNG rng(0);
|
|
rng.fill(src, RNG::UNIFORM, 0, 1);
|
|
|
|
// CPU works
|
|
transpose(src, dst);
|
|
|
|
// GPU works
|
|
GpuMat d_src(src);
|
|
GpuMat d_dst;
|
|
transpose(d_src, d_dst);
|
|
|
|
// Check results
|
|
bool passed = norm(dst - Mat(d_dst), NORM_INF) < 1e-3;
|
|
std::cout << "GPU #" << device_id << " (" << DeviceInfo().name() << "): "
|
|
<< (passed ? "passed" : "FAILED") << endl;
|
|
|
|
// Deallocate data here, otherwise deallocation will be performed
|
|
// after context is extracted from the stack
|
|
d_src.release();
|
|
d_dst.release();
|
|
|
|
CUcontext prev_context;
|
|
safeCall(cuCtxPopCurrent(&prev_context));
|
|
}
|
|
}
|
|
|
|
~Worker()
|
|
{
|
|
if ((contexts != NULL) && count != 0)
|
|
{
|
|
for (int device_id = 0; device_id < count; device_id++)
|
|
{
|
|
safeCall(cuCtxDestroy(contexts[device_id]));
|
|
}
|
|
|
|
delete[] contexts;
|
|
}
|
|
}
|
|
|
|
CUcontext* contexts;
|
|
int count;
|
|
};
|
|
|
|
int main()
|
|
{
|
|
int num_devices = getCudaEnabledDeviceCount();
|
|
if (num_devices < 2)
|
|
{
|
|
std::cout << "Two or more GPUs are required\n";
|
|
return -1;
|
|
}
|
|
|
|
for (int i = 0; i < num_devices; ++i)
|
|
{
|
|
cv::gpu::printShortCudaDeviceInfo(i);
|
|
|
|
DeviceInfo dev_info(i);
|
|
if (!dev_info.isCompatible())
|
|
{
|
|
std::cout << "GPU module isn't built for GPU #" << i << " ("
|
|
<< dev_info.name() << ", CC " << dev_info.majorVersion()
|
|
<< dev_info.minorVersion() << "\n";
|
|
return -1;
|
|
}
|
|
}
|
|
|
|
// Init CUDA Driver API
|
|
safeCall(cuInit(0));
|
|
|
|
// Execute calculation
|
|
parallel_for_(cv::Range(0, num_devices), Worker(num_devices));
|
|
|
|
return 0;
|
|
}
|
|
|
|
#endif
|