96dab34ad9
CUTLASS 2.1 contributes: - BLAS-style host-side API added to CUTLASS Library - Planar Complex GEMM kernels targeting Volta and Turing Tensor Cores - Minor enhancements and bug fixes
153 lines
5.6 KiB
C++
153 lines
5.6 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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/*! \file
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\brief Templates exposing architecture support for multiply-add operations
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*/
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#pragma once
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#include "cutlass/array.h"
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#include "cutlass/numeric_types.h"
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#include "cutlass/gemm/gemm.h"
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#include "cutlass/arch/arch.h"
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/////////////////////////////////////////////////////////////////////////////////////////////////
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namespace cutlass {
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namespace arch {
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/////////////////////////////////////////////////////////////////////////////////////////////////
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/// Tag indicating the operation implied by MMA.
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struct OpMultiplyAdd;
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/////////////////////////////////////////////////////////////////////////////////////////////////
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/// Tag indicating the result is saturated to MAX_FLOAT|MIN_FLOAT or MAX_INT|MIN_INT
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struct OpMultiplyAddSaturate;
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/////////////////////////////////////////////////////////////////////////////////////////////////
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/// Tag indicating the complex multiply-add operation
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struct OpMultiplyAddComplex;
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/////////////////////////////////////////////////////////////////////////////////////////////////
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/// Tag indicating the inner product is defined by (XOR, POPC)
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struct OpXorPopc;
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/////////////////////////////////////////////////////////////////////////////////////////////////
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/// Tag classifying math operators as thread-level operations.
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struct OpClassSimt;
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/////////////////////////////////////////////////////////////////////////////////////////////////
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/// Tag classifing operators as Tensor Core operations.
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struct OpClassTensorOp;
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/////////////////////////////////////////////////////////////////////////////////////////////////
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/// Tag classifing operators as WMMA Tensor Core operations
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struct OpClassWmmaTensorOp;
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/////////////////////////////////////////////////////////////////////////////////////////////////
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/// Matrix multiply-add operation
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template <
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/// Size of the matrix product (concept: GemmShape)
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typename Shape_,
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/// Number of threads participating
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int kThreads_,
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/// Data type of A elements
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typename ElementA,
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/// Layout of A matrix (concept: MatrixLayout)
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typename LayoutA,
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/// Data type of B elements
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typename ElementB,
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/// Layout of B matrix (concept: MatrixLayout)
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typename LayoutB,
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/// Element type of C matrix
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typename ElementC,
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/// Layout of C matrix (concept: MatrixLayout)
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typename LayoutC,
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/// Inner product operator
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typename Operator
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>
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struct Mma;
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/////////////////////////////////////////////////////////////////////////////////////////////////
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/// Matrix multiply-add operation - specialized for 1x1x1x1 matrix multiply operation
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template <
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/// Data type of A elements
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typename ElementA,
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/// Layout of A matrix (concept: MatrixLayout)
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typename LayoutA,
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/// Data type of B elements
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typename ElementB,
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/// Layout of B matrix (concept: MatrixLayout)
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typename LayoutB,
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/// Element type of C matrix
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typename ElementC,
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/// Layout of C matrix (concept: MatrixLayout)
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typename LayoutC,
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/// Inner product operator
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typename Operator
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>
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struct Mma<gemm::GemmShape<1, 1, 1>, 1, ElementA, LayoutA, ElementB, LayoutB, ElementC, LayoutC, Operator> {
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using Shape = gemm::GemmShape<1, 1, 1>;
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CUTLASS_HOST_DEVICE
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void operator()(
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Array<ElementC, 1> &d,
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Array<ElementA, 1> const &a,
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Array<ElementB, 1> const &b,
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Array<ElementC, 1> const &c
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) {
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d[0] = a[0] * b[0] + c[0];
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}
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};
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/////////////////////////////////////////////////////////////////////////////////////////////////
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} // namespace arch
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} // namespace cutlass
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/////////////////////////////////////////////////////////////////////////////////////////////////
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//
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// Specializations for each compute capability
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//
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#include "cutlass/arch/mma_sm50.h"
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#include "cutlass/arch/mma_sm60.h"
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#include "cutlass/arch/mma_sm61.h"
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#include "cutlass/arch/mma_sm70.h"
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#include "cutlass/arch/mma_sm75.h"
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/////////////////////////////////////////////////////////////////////////////////////////////////
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