Commit 725d83b0 authored by Alexey Spizhevoy's avatar Alexey Spizhevoy

added init() function into MultiGpuMgr, added samples

parent 5d4913a2
......@@ -131,15 +131,16 @@ namespace cv
/////////////////////////// Multi GPU Manager //////////////////////////////
// Provides functionality for working with many GPUs. Object of this
// class must be created before any OpenCV GPU call and no call must
// be done after its destruction.
// Provides functionality for working with many GPUs
class CV_EXPORTS MultiGpuMgr
{
public:
MultiGpuMgr();
~MultiGpuMgr();
// Must be called before any other GPU calls
void init();
// Makes the given GPU active
void gpuOn(int gpu_id);
......
......@@ -48,6 +48,7 @@ namespace cv { namespace gpu {
class MultiGpuMgr::Impl {};
MultiGpuMgr::MultiGpuMgr() { throw_nogpu(); }
void MultiGpuMgr::init() { throw_nogpu(); }
void MultiGpuMgr::gpuOn(int) { throw_nogpu(); }
void MultiGpuMgr::gpuOff() { throw_nogpu(); }
......@@ -79,6 +80,8 @@ public:
void gpuOn(int gpu_id)
{
if (gpu_id < 0 || gpu_id >= num_devices_)
CV_Error(CV_StsBadArg, "MultiGpuMgr::gpuOn: GPU ID is out of range");
cuSafeCall(cuCtxPushCurrent(contexts_[gpu_id]));
}
......@@ -105,6 +108,8 @@ MultiGpuMgr::Impl::Impl(): num_devices_(0)
num_devices_ = getCudaEnabledDeviceCount();
contexts_.resize(num_devices_);
cuSafeCall(cuInit(0));
CUdevice device;
CUcontext prev_context;
for (int i = 0; i < num_devices_; ++i)
......@@ -116,18 +121,28 @@ MultiGpuMgr::Impl::Impl(): num_devices_(0)
}
MultiGpuMgr::MultiGpuMgr(): impl_(new Impl()) {}
MultiGpuMgr::MultiGpuMgr() {}
MultiGpuMgr::~MultiGpuMgr() {}
void MultiGpuMgr::init()
{
impl_ = Ptr<Impl>(new Impl());
}
void MultiGpuMgr::gpuOn(int gpu_id)
{
if (impl_.empty())
CV_Error(CV_StsNullPtr, "MultiGpuMgr::gpuOn: must be initialized before any calls");
impl_->gpuOn(gpu_id);
}
void MultiGpuMgr::gpuOff()
{
if (impl_.empty())
CV_Error(CV_StsNullPtr, "MultiGpuMgr::gpuOff: must be initialized before any calls");
impl_->gpuOff();
}
......
......@@ -120,25 +120,25 @@ int main(int argc, char** argv)
// Init CUDA Driver API
safeCall(cuInit(0));
// Create context for the first GPU
// Create context for GPU #0
CUdevice device;
safeCall(cuDeviceGet(&device, 0));
safeCall(cuCtxCreate(&contexts[0], 0, device));
contextOff();
// Create context for the second GPU
// Create context for GPU #1
safeCall(cuDeviceGet(&device, 1));
safeCall(cuCtxCreate(&contexts[1], 0, device));
contextOff();
// Split source images for processing on the first GPU
// Split source images for processing on GPU #0
contextOn(0);
d_left[0].upload(left.rowRange(0, left.rows / 2));
d_right[0].upload(right.rowRange(0, right.rows / 2));
bm[0] = new StereoBM_GPU();
contextOff();
// Split source images for processing on the second GPU
// Split source images for processing on the GPU #1
contextOn(1);
d_left[1].upload(left.rowRange(left.rows / 2, left.rows));
d_right[1].upload(right.rowRange(right.rows / 2, right.rows));
......
/* 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 <cvconfig.h>
#include <opencv2/core/core.hpp>
#include <opencv2/gpu/gpu.hpp>
#if !defined(HAVE_CUDA) || !defined(HAVE_TBB)
int main()
{
#if !defined(HAVE_CUDA)
cout << "CUDA support is required (CMake key 'WITH_CUDA' must be true).\n";
#endif
#if !defined(HAVE_TBB)
cout << "TBB support is required (CMake key 'WITH_TBB' must be true).\n";
#endif
return 0;
}
#else
#include "opencv2/core/internal.hpp" // For TBB wrappers
using namespace std;
using namespace cv;
using namespace cv::gpu;
struct Worker { void operator()(int device_id) const; };
MultiGpuMgr multi_gpu_mgr;
int main()
{
int num_devices = getCudaEnabledDeviceCount();
if (num_devices < 2)
{
cout << "Two or more GPUs are required\n";
return -1;
}
for (int i = 0; i < num_devices; ++i)
{
DeviceInfo dev_info(i);
if (!dev_info.isCompatible())
{
cout << "GPU module isn't built for GPU #" << i << " ("
<< dev_info.name() << ", CC " << dev_info.majorVersion()
<< dev_info.minorVersion() << "\n";
return -1;
}
}
multi_gpu_mgr.init();
// Execute calculation in two threads using two GPUs
int devices[] = {0, 2};
parallel_do(devices, devices + 2, Worker());
return 0;
}
void Worker::operator()(int device_id) const
{
multi_gpu_mgr.gpuOn(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;
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();
multi_gpu_mgr.gpuOff();
}
#endif
/* This sample demonstrates working on one piece of data using two GPUs.
It splits input into two parts and processes them separately on 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 <cvconfig.h>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/gpu/gpu.hpp>
#if !defined(HAVE_CUDA) || !defined(HAVE_TBB)
int main()
{
#if !defined(HAVE_CUDA)
cout << "CUDA support is required (CMake key 'WITH_CUDA' must be true).\n";
#endif
#if !defined(HAVE_TBB)
cout << "TBB support is required (CMake key 'WITH_TBB' must be true).\n";
#endif
return 0;
}
#else
#include "opencv2/core/internal.hpp" // For TBB wrappers
using namespace std;
using namespace cv;
using namespace cv::gpu;
struct Worker { void operator()(int device_id) const; };
MultiGpuMgr multi_gpu_mgr;
// GPUs data
GpuMat d_left[2];
GpuMat d_right[2];
StereoBM_GPU* bm[2];
GpuMat d_result[2];
// CPU result
Mat result;
int main(int argc, char** argv)
{
if (argc < 3)
{
cout << "Usage: stereo_multi_gpu <left_image> <right_image>\n";
return -1;
}
int num_devices = getCudaEnabledDeviceCount();
if (num_devices < 2)
{
cout << "Two or more GPUs are required\n";
return -1;
}
for (int i = 0; i < num_devices; ++i)
{
DeviceInfo dev_info(i);
if (!dev_info.isCompatible())
{
cout << "GPU module isn't built for GPU #" << i << " ("
<< dev_info.name() << ", CC " << dev_info.majorVersion()
<< dev_info.minorVersion() << "\n";
return -1;
}
}
// Load input data
Mat left = imread(argv[1], CV_LOAD_IMAGE_GRAYSCALE);
Mat right = imread(argv[2], CV_LOAD_IMAGE_GRAYSCALE);
if (left.empty())
{
cout << "Cannot open '" << argv[1] << "'\n";
return -1;
}
if (right.empty())
{
cout << "Cannot open '" << argv[2] << "'\n";
return -1;
}
multi_gpu_mgr.init();
// Split source images for processing on the GPU #0
multi_gpu_mgr.gpuOn(0);
d_left[0].upload(left.rowRange(0, left.rows / 2));
d_right[0].upload(right.rowRange(0, right.rows / 2));
bm[0] = new StereoBM_GPU();
multi_gpu_mgr.gpuOff();
// Split source images for processing on the GPU #1
multi_gpu_mgr.gpuOn(1);
d_left[1].upload(left.rowRange(left.rows / 2, left.rows));
d_right[1].upload(right.rowRange(right.rows / 2, right.rows));
bm[1] = new StereoBM_GPU();
multi_gpu_mgr.gpuOff();
// Execute calculation in two threads using two GPUs
int devices[] = {0, 1};
parallel_do(devices, devices + 2, Worker());
// Release the first GPU resources
multi_gpu_mgr.gpuOn(0);
imshow("GPU #0 result", Mat(d_result[0]));
d_left[0].release();
d_right[0].release();
d_result[0].release();
delete bm[0];
multi_gpu_mgr.gpuOff();
// Release the second GPU resources
multi_gpu_mgr.gpuOn(1);
imshow("GPU #1 result", Mat(d_result[1]));
d_left[1].release();
d_right[1].release();
d_result[1].release();
delete bm[1];
multi_gpu_mgr.gpuOff();
waitKey();
return 0;
}
void Worker::operator()(int device_id) const
{
multi_gpu_mgr.gpuOn(device_id);
bm[device_id]->operator()(d_left[device_id], d_right[device_id],
d_result[device_id]);
cout << "GPU #" << device_id << " (" << DeviceInfo().name()
<< "): finished\n";
multi_gpu_mgr.gpuOff();
}
#endif
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