877bdcace6
CUTLASS 1.3 Release - Efficient GEMM kernel targeting Volta Tensor Cores via mma.sync instruction added in CUDA 10.1.
73 lines
3.3 KiB
C++
73 lines
3.3 KiB
C++
/***************************************************************************************************
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* Copyright (c) 2017-2019, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without modification, are permitted
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* provided that the following conditions are met:
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* * Redistributions of source code must retain the above copyright notice, this list of
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* conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright notice, this list of
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* conditions and the following disclaimer in the documentation and/or other materials
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* provided with the distribution.
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* * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used
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* to endorse or promote products derived from this software without specific prior written
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* permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
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* IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
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* FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE
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* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
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* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
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* OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
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* STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*
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**************************************************************************************************/
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#pragma once
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#include <stdexcept>
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#include "cutlass/cutlass.h"
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#include "tools/util/reference/device/kernel/tensor_foreach.h"
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namespace cutlass {
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namespace reference {
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namespace device {
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///////////////////////////////////////////////////////////////////////////////////////////////////
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/// Launches a kernel for each element in a tensor's index space.
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template <typename Func, int Rank, typename Params>
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struct TensorForEach {
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/// Constructor performs the operation.
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TensorForEach(Coord<Rank> size, Params params = Params(), int grid_size = 0, int block_size = 0) {
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if (!grid_size || !block_size) {
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// if grid_size or block_size are zero, query occupancy using the CUDA Occupancy API
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cudaError_t result = cudaOccupancyMaxPotentialBlockSize(
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&grid_size,
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&block_size,
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reinterpret_cast<void const *>(kernel::TensorForEach<Func, Rank, Params>));
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if (result != cudaSuccess) {
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throw std::runtime_error("Failed to query occupancy.");
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}
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// Limit block size. This has the effect of increasing the number of items processed by a
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// single thread and reduces the impact of initialization overhead.
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block_size = (block_size < 128 ? block_size : 128);
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}
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dim3 grid(grid_size, 1, 1);
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dim3 block(block_size, 1, 1);
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kernel::TensorForEach<Func, Rank, Params><<< grid, block >>>(size, params);
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}
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};
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///////////////////////////////////////////////////////////////////////////////////////////////////
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} // namespace device
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} // namespace reference
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} // namesace cutlass
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