877bdcace6
CUTLASS 1.3 Release - Efficient GEMM kernel targeting Volta Tensor Cores via mma.sync instruction added in CUDA 10.1.
159 lines
4.9 KiB
C++
159 lines
4.9 KiB
C++
/***************************************************************************************************
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* Copyright (c) 2018-2019, 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/core_io.h"
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#include "cutlass/tensor_view.h"
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namespace cutlass {
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///////////////////////////////////////////////////////////////////////////////////////////////////
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namespace detail {
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/// Helper to write the least significant rank of a TensorView
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template <
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typename Storage_,
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int Rank_,
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typename MapFunc_,
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int StorageRank_,
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typename Index_,
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typename LongIndex_
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>
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inline std::ostream & TensorView_WriteLeastSignificantRank(
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std::ostream& out,
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cutlass::TensorView<
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Storage_,
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Rank_,
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MapFunc_,
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StorageRank_,
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Index_,
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LongIndex_> const& tensor,
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cutlass::Coord<Rank_> const &start_coord,
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int rank,
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std::streamsize width) {
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for (int idx = 0; idx < tensor.size(rank); ++idx) {
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Coord<Rank_> coord(start_coord);
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coord[rank] = idx;
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if (idx) {
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out.width(0);
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out << ", ";
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}
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if (idx || coord) {
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out.width(width);
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}
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out << ScalarIO<Storage_>(tensor.at(coord));
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}
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return out;
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}
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/// Helper to write a rank of a TensorView
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template <
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typename Storage_,
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int Rank_,
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typename MapFunc_,
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int StorageRank_,
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typename Index_,
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typename LongIndex_
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>
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inline std::ostream & TensorView_WriteRank(
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std::ostream& out,
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cutlass::TensorView<
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Storage_,
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Rank_,
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MapFunc_,
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StorageRank_,
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Index_,
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LongIndex_> const& tensor,
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cutlass::Coord<Rank_> const &start_coord,
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int rank,
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std::streamsize width) {
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// If called on the least significant rank, write the result as a row
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if (rank + 1 == Rank_) {
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return TensorView_WriteLeastSignificantRank(out, tensor, start_coord, rank, width);
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}
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// Otherwise, write a sequence of rows and newlines
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for (int idx = 0; idx < tensor.size(rank); ++idx) {
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Coord<Rank_> coord(start_coord);
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coord[rank] = idx;
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if (rank + 2 == Rank_) {
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// Write least significant ranks asa matrix with rows delimited by ";\n"
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out << (idx ? ";\n" : "");
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TensorView_WriteLeastSignificantRank(out, tensor, coord, rank + 1, width);
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}
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else {
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// Higher ranks are separated by newlines
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out << (idx ? "\n" : "");
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TensorView_WriteRank(out, tensor, coord, rank + 1, width);
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}
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}
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return out;
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}
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} // namespace detail
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///////////////////////////////////////////////////////////////////////////////////////////////////
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/// Prints human-readable representation of a TensorView to an ostream
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template <
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typename Storage_,
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int Rank_,
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typename MapFunc_,
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int StorageRank_,
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typename Index_,
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typename LongIndex_
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>
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inline std::ostream& operator<<(
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std::ostream& out,
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TensorView<
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Storage_,
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Rank_,
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MapFunc_,
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StorageRank_,
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Index_,
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LongIndex_> const& tensor) {
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// Prints a TensorView according to the following conventions:
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// - least significant rank is printed as rows separated by ";\n"
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// - all greater ranks are delimited with newlines
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//
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// The result is effectively a whitespace-delimited series of 2D matrices.
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return detail::TensorView_WriteRank(out, tensor, Coord<Rank_>(), 0, out.width());
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}
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///////////////////////////////////////////////////////////////////////////////////////////////////
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} // namespace cutlass
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