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