f4334277
 Hu Chunming
提交3rdparty
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// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
#ifndef OPENCV_DNN_SRC_CUDA_EXECUTION_HPP
#define OPENCV_DNN_SRC_CUDA_EXECUTION_HPP
#include "../cuda4dnn/csl/error.hpp"
#include "../cuda4dnn/csl/stream.hpp"
#include <opencv2/core.hpp>
#include <cuda_runtime_api.h>
#include <cstddef>
namespace cv { namespace dnn { namespace cuda4dnn { namespace csl {
struct execution_policy {
execution_policy(dim3 grid_size, dim3 block_size)
: grid{ grid_size }, block{ block_size }, sharedMem{ 0 }, stream{ 0 } { }
execution_policy(dim3 grid_size, dim3 block_size, std::size_t shared_mem)
: grid{ grid_size }, block{ block_size }, sharedMem{ shared_mem }, stream{ nullptr } { }
execution_policy(dim3 grid_size, dim3 block_size, const Stream& strm)
: grid{ grid_size }, block{ block_size }, sharedMem{ 0 }, stream{ strm.get() } { }
execution_policy(dim3 grid_size, dim3 block_size, std::size_t shared_mem, const Stream& strm)
: grid{ grid_size }, block{ block_size }, sharedMem{ shared_mem }, stream{ strm.get() } { }
dim3 grid;
dim3 block;
std::size_t sharedMem;
cudaStream_t stream;
};
/* this overload shouldn't be necessary; we should always provide a bound on the number of threads */
/*
template <class Kernel> inline
execution_policy make_policy(Kernel kernel, std::size_t sharedMem = 0, const Stream& stream = 0) {
int grid_size, block_size;
CUDA4DNN_CHECK_CUDA(cudaOccupancyMaxPotentialBlockSize(&grid_size, &block_size, kernel, sharedMem));
return execution_policy(grid_size, block_size, sharedMem, stream);
}*/
template <class Kernel> inline
execution_policy make_policy(Kernel kernel, std::size_t max_threads, std::size_t sharedMem = 0, const Stream& stream = 0) {
CV_Assert(max_threads > 0);
int grid_size = 0, block_size = 0;
CUDA4DNN_CHECK_CUDA(cudaOccupancyMaxPotentialBlockSize(&grid_size, &block_size, kernel, sharedMem));
if (grid_size * block_size > max_threads) {
grid_size = (max_threads + block_size - 1) / block_size;
if (block_size > max_threads)
block_size = max_threads;
}
CV_Assert(grid_size >= 1 && block_size >= 1);
return execution_policy(grid_size, block_size, sharedMem, stream);
}
template <class Kernel, typename ...Args> inline
void launch_kernel(Kernel kernel, Args ...args) {
auto policy = make_policy(kernel);
kernel <<<policy.grid, policy.block>>> (args...);
}
template <class Kernel, typename ...Args> inline
void launch_kernel(Kernel kernel, dim3 grid, dim3 block, Args ...args) {
kernel <<<grid, block>>> (args...);
}
template <class Kernel, typename ...Args> inline
void launch_kernel(Kernel kernel, execution_policy policy, Args ...args) {
kernel <<<policy.grid, policy.block, policy.sharedMem, policy.stream>>> (args...);
}
}}}} /* namespace cv::dnn::cuda4dnn::csl */
#endif /* OPENCV_DNN_SRC_CUDA_EXECUTION_HPP */
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