877bdcace6
CUTLASS 1.3 Release - Efficient GEMM kernel targeting Volta Tensor Cores via mma.sync instruction added in CUDA 10.1.
113 lines
3.9 KiB
C++
113 lines
3.9 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 "cutlass/cutlass.h"
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#include "cutlass/coord.h"
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namespace cutlass {
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namespace reference {
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namespace device {
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namespace kernel {
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///////////////////////////////////////////////////////////////////////////////////////////////////
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/// Defines several helpers
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namespace detail {
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/// Helper to perform for-each operation
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template <typename Func, int Rank, int RankRemaining>
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struct TensorForEachHelper {
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/// Constructor for general rank
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__inline__ __device__
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TensorForEachHelper(Func &func, Coord<Rank> const &size, Coord<Rank> &coord, int64_t index) {
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int64_t product = 1;
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CUTLASS_PRAGMA_UNROLL
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for (int i = Rank - RankRemaining; i < Rank; ++i) {
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product *= size[i];
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}
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coord[Rank - 1 - RankRemaining] = index / product;
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int64_t remaining = index % product;
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TensorForEachHelper<Func, Rank, RankRemaining-1>(func, size, coord, remaining);
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}
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};
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/// Helper to perform for-each operation
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template <typename Func, int Rank>
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struct TensorForEachHelper<Func, Rank, 0> {
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/// Constructor for fastest chaning rank
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__inline__ __device__
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TensorForEachHelper(Func &func, Coord<Rank> const &size, Coord<Rank> &coord, int64_t index) {
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coord[Rank - 1] = index;
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if (coord < size) {
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func(coord);
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}
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}
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};
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} // namespace detail
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///////////////////////////////////////////////////////////////////////////////////////////////////
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/// Helper to perform for-each operation
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template <typename Func, int Rank, typename Params>
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__global__ void TensorForEach(Coord<Rank> size, Params params = Params()) {
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Func func(params);
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int64_t index = threadIdx.x + blockIdx.x * blockDim.x;
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int64_t max_index = 1;
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CUTLASS_PRAGMA_UNROLL
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for (int i = 0; i < Rank; ++i) {
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max_index *= size[i];
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}
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CUTLASS_PRAGMA_NO_UNROLL
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while (index < max_index) {
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Coord<Rank> coord;
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detail::TensorForEachHelper<Func, Rank, Rank - 1>(func, size, coord, index);
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index += blockDim.x * gridDim.x;
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}
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}
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///////////////////////////////////////////////////////////////////////////////////////////////////
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} // namespace kernel
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} // namespace device
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} // namespace reference
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} // namespace cutlass
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