107 lines
4.8 KiB
C++
107 lines
4.8 KiB
C++
/***************************************************************************************************
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* Copyright (c) 2017-2018, 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 Specialization implementing multiply-add operation on half-precision floating point
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fragments.
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*/
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#pragma once
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#include "cutlass/fragment.h"
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#include "cutlass/gemm/thread_multiply_add.h"
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namespace cutlass {
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namespace gemm {
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////////////////////////////////////////////////////////////////////////////////////////////////////
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/// Template performing matrix multiply-add operation within a thread
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template <typename ThreadGemmShape_, typename ThreadsPerWarp_>
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struct ThreadMultiplyAdd<ThreadGemmShape_, ThreadsPerWarp_, half, half, half> {
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/// The shape of the instruction.
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typedef Shape<1, 1, 2, 1> InstructionShape;
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/// The number of accumulators per thread.
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typedef ThreadGemmShape_ ThreadGemmShape;
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/// Aliased for compatibility. Will be removed for CUTLASS v2.0.
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typedef ThreadGemmShape AccumulatorsPerThread;
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/// The number of threads per warp.
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typedef ThreadsPerWarp_ ThreadsPerWarp;
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/// The number of accumulators per warp.
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typedef typename ShapeMul<ThreadGemmShape, ThreadsPerWarp>::Shape AccumulatorsPerWarp;
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/// The type for A.
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typedef half ScalarA;
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/// The fragment for A.
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typedef Fragment<ScalarA, AccumulatorsPerThread::kW> FragmentA;
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/// The type for B.
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typedef half ScalarB;
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/// The fragment for B.
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typedef Fragment<ScalarB, AccumulatorsPerThread::kH> FragmentB;
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/// The type for C and D.
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typedef half ScalarC;
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/// The accumulators.
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typedef Fragment<half, AccumulatorsPerThread::kH * AccumulatorsPerThread::kW> Accumulators;
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/// Make sure there's an even number of elements in both dimensions.
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static_assert(AccumulatorsPerThread::kH % 2 == 0, "Invalid size");
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static_assert(AccumulatorsPerThread::kW % 2 == 0, "Invalid size");
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/// Ctor.
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CUTLASS_DEVICE ThreadMultiplyAdd() {}
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/// Multiply : d = a*b + c.
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CUTLASS_DEVICE void multiply_add(FragmentA const& a,
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FragmentB const& b,
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Accumulators const& c,
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Accumulators& d) {
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#if defined(__CUDACC__) && __CUDA_ARCH__ >= 530
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// The inputs.
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__half2 const* a_half2 = reinterpret_cast<__half2 const*>(&a[0]);
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__half2 const* b_half2 = reinterpret_cast<__half2 const*>(&b[0]);
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__half2 const* c_half2 = reinterpret_cast<__half2 const*>(&c[0]);
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// The output.
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__half2* d_half2 = reinterpret_cast<__half2*>(&d[0]);
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for (int j = 0; j < AccumulatorsPerThread::kH / 2; ++j) {
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for (int i = 0; i < AccumulatorsPerThread::kW / 2; ++i) {
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// The offsets in the output fragment.
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int const k0 = (2 * j + 0) * (AccumulatorsPerThread::kW / 2) + i;
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int const k1 = (2 * j + 1) * (AccumulatorsPerThread::kW / 2) + i;
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// Compute the product a[i] * b[j].low.
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d_half2[k0] = __hfma2(a_half2[i], __low2half2(b_half2[j]), c_half2[k0]);
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// Compute the product a[i] * b[j].high.
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d_half2[k1] = __hfma2(a_half2[i], __high2half2(b_half2[j]), c_half2[k1]);
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}
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}
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#endif
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}
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};
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////////////////////////////////////////////////////////////////////////////////////////////////////
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} // namespace gemm
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} // namespace cutlass
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