245 lines
8.7 KiB
C++
Executable File
245 lines
8.7 KiB
C++
Executable File
/***************************************************************************************************
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* Copyright (c) 2017 - 2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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* SPDX-License-Identifier: BSD-3-Clause
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions are met:
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*
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* 1. Redistributions of source code must retain the above copyright notice, this
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* list of conditions and the following disclaimer.
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*
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* 2. Redistributions in binary form must reproduce the above copyright notice,
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* this list of conditions and the following disclaimer in the documentation
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* and/or other materials provided with the distribution.
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*
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* 3. Neither the name of the copyright holder nor the names of its
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* contributors may be used to endorse or promote products derived from
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* this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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* AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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* DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
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* FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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* SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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* CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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* OR TORT (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/cutlass.h"
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#include "cutlass/aligned_buffer.h"
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#include "cutlass/array.h"
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#include "cutlass/numeric_types.h"
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#include "cutlass/matrix_shape.h"
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#include "cutlass/gemm/gemm.h"
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/////////////////////////////////////////////////////////////////////////////////////////////////
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namespace cutlass {
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namespace gemm {
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namespace kernel {
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namespace detail
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{
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template<typename ElementAlphaBeta, bool BetaIsZero>
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struct GemvBatchedStridedEpilogueScaling
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{
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ElementAlphaBeta const & alpha;
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ElementAlphaBeta const & beta;
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CUTLASS_DEVICE
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GemvBatchedStridedEpilogueScaling(ElementAlphaBeta& alpha_, ElementAlphaBeta& beta_) :
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alpha(alpha_), beta(beta_)
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{ }
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template<typename FragmentCD, typename FragmentAccumulator>
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CUTLASS_DEVICE
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void operator()(FragmentAccumulator& accumulators,
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FragmentCD const& fragment_C,
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FragmentCD& fragment_D) const
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{
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using AccType = typename FragmentAccumulator::value_type;
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using CDType = typename FragmentCD::value_type;
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static_assert(FragmentCD::kElements == FragmentAccumulator::kElements,
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"Mistmatch in fragment sizes.");
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for (int i = 0; i < FragmentCD::kElements; ++i)
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{
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if (BetaIsZero)
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{
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fragment_D[i] = CDType(accumulators[i] * AccType(alpha));
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}
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else
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{
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fragment_D[i] = CDType(accumulators[i] * AccType(alpha)
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+ AccType(fragment_C[i]) * AccType(beta));
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}
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}
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}
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};
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}
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/////////////////////////////////////////////////////////////////////////////////////////////////
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template <typename GemvKernel, typename ElementAlphaBeta, bool BetaIsZero=false>
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CUTLASS_DEVICE void GemvBatchedStridedDevice(
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cutlass::gemm::BatchedGemmCoord problem_size,
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ElementAlphaBeta alpha,
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ElementAlphaBeta beta,
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typename GemvKernel::IteratorA::TensorRef ref_A,
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typename GemvKernel::IteratorA::TensorRef::LongIndex lda,
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typename GemvKernel::IteratorB::TensorRef ref_B,
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typename GemvKernel::IteratorB::TensorRef::LongIndex ldb,
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typename GemvKernel::IteratorCD::TensorRef ref_C,
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typename GemvKernel::IteratorCD::TensorRef::LongIndex ldc,
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typename GemvKernel::IteratorCD::TensorRef ref_D,
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typename GemvKernel::IteratorCD::TensorRef::LongIndex ldd)
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{
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using ThreadBlockGemv = typename GemvKernel::ThreadBlockGemv;
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using ThreadBlockSwizzle = typename GemvKernel::ThreadBlockSwizzle;
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using EpilogueScale = detail::GemvBatchedStridedEpilogueScaling<ElementAlphaBeta, BetaIsZero>;
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ThreadBlockSwizzle swizzler;
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// Compute initial location in logical coordinates
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BatchedGemmCoord tb_offset = swizzler.get_tile_offset();
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int const batch_idx = swizzler.get_batch_idx();
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// Offset to the batch
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ref_A.add_pointer_offset(batch_idx*lda);
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ref_B.add_pointer_offset(batch_idx*ldb);
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// Construct iterators to A and B operands
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typename GemvKernel::IteratorA::Params params_A(ref_A.layout());
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typename GemvKernel::IteratorA iterator_A(
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params_A,
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ref_A.data(),
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{ 1, problem_size.k() },
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0,
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{ 0, 0 });
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typename GemvKernel::IteratorB::Params params_B(ref_B.layout());
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typename GemvKernel::IteratorB iterator_B(
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params_B,
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ref_B.data(),
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{ problem_size.k(), problem_size.n() },
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threadIdx.x,
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{ 0, tb_offset.n()*ThreadBlockGemv::Shape::kN });
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//
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// Main loop
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//
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// Construct thread-scoped matrix multiply
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ThreadBlockGemv mma;
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typename ThreadBlockGemv::FragmentC accumulators;
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accumulators.clear();
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// Compute threadblock-scoped gemv
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mma(problem_size.mnk(), accumulators, iterator_A, iterator_B, accumulators);
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//
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// Epilogue
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//
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typename GemvKernel::FragmentCD fragment_CD;
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// Load C (skip if beta is zero)
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if (!BetaIsZero)
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{
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tb_offset = swizzler.get_tile_offset();
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ref_C.add_pointer_offset(batch_idx*ldc);
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typename GemvKernel::IteratorCD::Params params_C(ref_C.layout());
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typename GemvKernel::IteratorCD iterator_C(
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params_C,
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ref_C.data(),
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{ 1, problem_size.n() },
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threadIdx.x,
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{ 0, tb_offset.n()*ThreadBlockGemv::Shape::kN });
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iterator_C.load(fragment_CD);
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}
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// Apply alpha/beta scaling
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EpilogueScale epilogue_scale(alpha, beta);
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epilogue_scale(accumulators, fragment_CD, fragment_CD);
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// Store D
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tb_offset = swizzler.get_tile_offset();
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ref_D.add_pointer_offset(batch_idx*ldd);
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typename GemvKernel::IteratorCD::Params params_D(ref_D.layout());
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typename GemvKernel::IteratorCD iterator_D(
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params_D,
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ref_D.data(),
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{ 1, problem_size.n() },
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threadIdx.x,
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{ 0, tb_offset.n()*ThreadBlockGemv::Shape::kN });
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iterator_D.store(fragment_CD);
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}
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template <typename GemvKernel, typename ElementAlphaBeta, bool BetaIsZero>
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__global__ void GemvBatchedStrided(
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cutlass::gemm::BatchedGemmCoord problem_size,
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ElementAlphaBeta alpha,
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ElementAlphaBeta beta,
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typename GemvKernel::IteratorA::TensorRef ref_A,
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typename GemvKernel::IteratorA::TensorRef::LongIndex lda,
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typename GemvKernel::IteratorB::TensorRef ref_B,
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typename GemvKernel::IteratorB::TensorRef::LongIndex ldb,
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typename GemvKernel::IteratorCD::TensorRef ref_C,
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typename GemvKernel::IteratorCD::TensorRef::LongIndex ldc,
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typename GemvKernel::IteratorCD::TensorRef ref_D,
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typename GemvKernel::IteratorCD::TensorRef::LongIndex ldd)
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{
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GemvBatchedStridedDevice<GemvKernel, ElementAlphaBeta, BetaIsZero>(
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problem_size, alpha, beta, ref_A, lda, ref_B, ldb, ref_C, ldc, ref_D, ldd
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);
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}
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template <typename GemvKernel, typename ElementAlphaBeta>
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__global__ void GemvBatchedStrided(
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cutlass::gemm::BatchedGemmCoord problem_size,
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ElementAlphaBeta alpha,
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typename GemvKernel::IteratorA::TensorRef ref_A,
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typename GemvKernel::IteratorA::TensorRef::LongIndex lda,
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typename GemvKernel::IteratorB::TensorRef ref_B,
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typename GemvKernel::IteratorB::TensorRef::LongIndex ldb,
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typename GemvKernel::IteratorCD::TensorRef ref_D,
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typename GemvKernel::IteratorCD::TensorRef::LongIndex ldd)
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{
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GemvBatchedStridedDevice<GemvKernel, ElementAlphaBeta, true>(
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problem_size, alpha, ElementAlphaBeta(0), ref_A, lda, ref_B, ldb, ref_D, ldd, ref_D, ldd
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);
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}
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template <typename GemvKernel>
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__global__ void GemvBatchedStrided(
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cutlass::gemm::BatchedGemmCoord problem_size,
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typename GemvKernel::IteratorA::TensorRef ref_A,
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typename GemvKernel::IteratorA::TensorRef::LongIndex lda,
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typename GemvKernel::IteratorB::TensorRef ref_B,
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typename GemvKernel::IteratorB::TensorRef::LongIndex ldb,
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typename GemvKernel::IteratorCD::TensorRef ref_D,
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typename GemvKernel::IteratorCD::TensorRef::LongIndex ldd)
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{
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using ElementAlphaBeta = typename GemvKernel::IteratorCD::Element;
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GemvBatchedStridedDevice<GemvKernel, ElementAlphaBeta, true>(
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problem_size, ElementAlphaBeta(1), ElementAlphaBeta(0), ref_A, lda, ref_B, ldb, ref_D, ldd, ref_D, ldd
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);
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}
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/////////////////////////////////////////////////////////////////////////////////////////////////
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} // namespace kernel
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} // namespace gemm
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} // namespace cutlass
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