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/***************************************************************************************************
* 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 <cutlass/fragment.h>
#include <cutlass/gemm/thread_multiply_add.h>
namespace cutlass {
namespace gemm {
////////////////////////////////////////////////////////////////////////////////////////////////////
/// Template performing matrix multiply-add operation within a thread
template <typename AccumulatorsPerThread_, typename ThreadsPerWarp_>
struct ThreadMultiplyAdd<AccumulatorsPerThread_, ThreadsPerWarp_, half, half, half> {
/// 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<AccumulatorsPerThread, ThreadsPerWarp>::Shape AccumulatorsPerWarp;
/// The type for A.
typedef half ScalarA;
/// The fragment for A.
typedef Fragment<ScalarA, AccumulatorsPerThread::kW> FragmentA;
/// The type for B.
typedef half ScalarB;
/// The fragment for B.
typedef Fragment<ScalarB, AccumulatorsPerThread::kH> FragmentB;
/// The type for C and D.
typedef half ScalarC;
/// The accumulators.
typedef Fragment<half, AccumulatorsPerThread::kH * AccumulatorsPerThread::kW> 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
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