/*************************************************************************************************** * Copyright (c) 2017-2018, NVIDIA CORPORATION. All rights reserved. * * Redistribution and use in source and binary forms, with or without modification, are permitted * provided that the following conditions are met: * * Redistributions of source code must retain the above copyright notice, this list of * conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above copyright notice, this list of * conditions and the following disclaimer in the documentation and/or other materials * provided with the distribution. * * Neither the name of the NVIDIA CORPORATION nor the names of its contributors may be used * to endorse or promote products derived from this software without specific prior written * permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR * IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND * FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL NVIDIA CORPORATION BE LIABLE * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; * OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, * STRICT LIABILITY, OR TOR (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. * **************************************************************************************************/ /*! \file \brief Specialization implementing multiply-add operation on half-precision floating point fragments. */ #pragma once #include #include namespace cutlass { namespace gemm { //////////////////////////////////////////////////////////////////////////////////////////////////// /// Template performing matrix multiply-add operation within a thread template struct ThreadMultiplyAdd { /// The shape of the instruction. typedef Shape<1, 1, 2, 1> InstructionShape; /// The number of accumulators per thread. typedef AccumulatorsPerThread_ AccumulatorsPerThread; /// The number of threads per warp. typedef ThreadsPerWarp_ ThreadsPerWarp; /// The number of accumulators per warp. typedef typename ShapeMul::Shape AccumulatorsPerWarp; /// The type for A. typedef half ScalarA; /// The fragment for A. typedef Fragment FragmentA; /// The type for B. typedef half ScalarB; /// The fragment for B. typedef Fragment FragmentB; /// The type for C and D. typedef half ScalarC; /// The accumulators. typedef Fragment Accumulators; /// Make sure there's an even number of elements in both dimensions. static_assert(AccumulatorsPerThread::kH % 2 == 0, "Invalid size"); static_assert(AccumulatorsPerThread::kW % 2 == 0, "Invalid size"); /// Ctor. CUTLASS_DEVICE ThreadMultiplyAdd() {} /// Multiply : d = a*b + c. CUTLASS_DEVICE void multiply_add(FragmentA const& a, FragmentB const& b, Accumulators const& c, Accumulators& d) { #if defined(__CUDACC__) && __CUDA_ARCH__ >= 530 // The inputs. __half2 const* a_half2 = reinterpret_cast<__half2 const*>(&a[0]); __half2 const* b_half2 = reinterpret_cast<__half2 const*>(&b[0]); __half2 const* c_half2 = reinterpret_cast<__half2 const*>(&c[0]); // The output. __half2* d_half2 = reinterpret_cast<__half2*>(&d[0]); for (int j = 0; j < AccumulatorsPerThread::kH / 2; ++j) { for (int i = 0; i < AccumulatorsPerThread::kW / 2; ++i) { // The offsets in the output fragment. int const k0 = (2 * j + 0) * (AccumulatorsPerThread::kW / 2) + i; int const k1 = (2 * j + 1) * (AccumulatorsPerThread::kW / 2) + i; // Compute the product a[i] * b[j].H0_H0. d_half2[k0] = __hfma2(a_half2[i], __low2half2(b_half2[j]), c_half2[k0]); // Compute the product a[i] * b[j].H1_H1. d_half2[k1] = __hfma2(a_half2[i], __high2half2(b_half2[j]), c_half2[k1]); } } #endif } }; //////////////////////////////////////////////////////////////////////////////////////////////////// } // namespace gemm } // namespace cutlass