66d9cddc83
* New updates. * Minor profiler updates Co-authored-by: Aniket Shivam <ashivam@nvidia.com>
248 lines
9.6 KiB
C++
248 lines
9.6 KiB
C++
/***************************************************************************************************
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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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/*! \file
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\brief
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Default kernel-level RankK definitions combine threadblock-scoped matrix multiply-add with
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the appropriate threadblock-scoped epilogue.
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*/
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#pragma once
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#include "cutlass/blas3.h"
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#include "cutlass/layout/matrix.h"
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#include "cutlass/arch/wmma.h"
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#include "cutlass/epilogue/threadblock/epilogue.h"
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#include "cutlass/epilogue/thread/linear_combination.h"
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#include "cutlass/gemm/gemm.h"
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#include "cutlass/gemm/kernel/rank_k_universal.h"
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#include "cutlass/gemm/threadblock/default_mma_core_sm75.h"
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#include "cutlass/gemm/threadblock/default_mma_core_sm70.h"
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#include "cutlass/gemm/threadblock/default_mma_core_sm80.h"
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#include "cutlass/gemm/threadblock/default_mma.h"
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#include "cutlass/gemm/threadblock/default_mma_core_simt.h"
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#include "cutlass/gemm/threadblock/threadblock_swizzle.h"
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#include "cutlass/epilogue/threadblock/default_epilogue_tensor_op_blas3.h"
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#include "cutlass/epilogue/threadblock/default_epilogue_volta_tensor_op.h"
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#include "cutlass/epilogue/threadblock/default_epilogue_simt.h"
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#include "cutlass/transform/threadblock/predicated_tile_iterator.h"
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#if defined(CUTLASS_ARCH_WMMA_ENABLED)
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#include "cutlass/epilogue/threadblock/default_epilogue_wmma_tensor_op.h"
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#endif //CUTLASS_ARCH_WMMA_ENABLED
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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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////////////////////////////////////////////////////////////////////////////////
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template <
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/// Element type for A matrix operand
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typename ElementA_,
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/// Layout type for A matrix operand
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typename LayoutA_,
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/// Access granularity of A matrix in units of elements
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int kAlignmentA,
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/// Element type for C and D matrix operands
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typename ElementC_,
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/// Layout type for C and D matrix operands
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typename LayoutC_,
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/// Fill Mode for C (kLower or kUpper)
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FillMode FillModeC_,
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/// Element type for internal accumulation
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typename ElementAccumulator,
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/// Operator class tag
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typename OperatorClass,
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/// Tag indicating architecture to tune for
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typename ArchTag,
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/// Threadblock-level tile size (concept: GemmShape)
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typename ThreadblockShape,
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/// Warp-level tile size (concept: GemmShape)
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typename WarpShape,
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/// Warp-level tile size (concept: GemmShape)
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typename InstructionShape,
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/// Epilogue output operator
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typename EpilogueOutputOp,
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/// Threadblock-level swizzling operator
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typename ThreadblockSwizzle,
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/// Number of stages used in the pipelined mainloop
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int Stages,
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/// If true, kernel is configured to support serial reduction in the
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/// epilogue
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bool SplitKSerial,
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/// Operation performed by GEMM
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typename Operator,
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/// Blas3 computation mode
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BlasMode BlasMode_ = BlasMode::kSymmetric>
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struct DefaultRankK;
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////////////////////////////////////////////////////////////////////////////////
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/// Partial specialization for Hopper Architecture
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template <
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/// Element type for A matrix operand
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typename ElementA,
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/// Layout type for A matrix operand
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typename LayoutA,
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/// Access granularity of A matrix in units of elements
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int kAlignmentA,
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/// Element type for C and D matrix operands
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typename ElementC,
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/// Fill Mode for C (kLower or kUpper)
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FillMode FillModeC,
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/// Element type for internal accumulation
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typename ElementAccumulator,
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/// Threadblock-level tile size (concept: GemmShape)
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typename ThreadblockShape,
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/// Warp-level tile size (concept: GemmShape)
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typename WarpShape,
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/// Warp-level tile size (concept: GemmShape)
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typename InstructionShape,
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/// Epilogue output operator
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typename EpilogueOutputOp,
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/// Threadblock-level swizzling operator
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typename ThreadblockSwizzle,
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/// Number of stages used in the pipelined mainloop
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int Stages,
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/// If true, kernel is configured to support serial reduction in the
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/// epilogue
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bool SplitKSerial,
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/// Operation performed by GEMM
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typename Operator>
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struct DefaultRankK<
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ElementA, LayoutA, kAlignmentA,
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ElementC,layout::RowMajor, FillModeC,
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ElementAccumulator, arch::OpClassTensorOp, arch::Sm90,
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ThreadblockShape, WarpShape, InstructionShape,
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EpilogueOutputOp, ThreadblockSwizzle, Stages, SplitKSerial,
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Operator> {
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/// Define the threadblock-scoped matrix multiply-accumulate (A x AT)
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using Mma = typename cutlass::gemm::threadblock::DefaultMma<
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ElementA, LayoutA,
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kAlignmentA,
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ElementA, typename layout::LayoutTranspose<LayoutA>::type,
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kAlignmentA,
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ElementAccumulator, layout::RowMajor, arch::OpClassTensorOp, arch::Sm90,
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ThreadblockShape, WarpShape, InstructionShape, Stages,
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Operator>::ThreadblockMma;
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static const int kPartitionsK = ThreadblockShape::kK / WarpShape::kK;
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/// Define the epilogue
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using Epilogue =
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typename cutlass::epilogue::threadblock::DefaultEpilogueTensorOpBlas3<
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ThreadblockShape, typename Mma::Operator, kPartitionsK, EpilogueOutputOp,
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EpilogueOutputOp::kCount, BlasMode::kSymmetric>::Epilogue;
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/// Define the kernel-level Rank2 operator.
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using RankKkernel = kernel::RankKUniversal<Mma, Epilogue, ThreadblockSwizzle, FillModeC>;
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};
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////////////////////////////////////////////////////////////////////////////////
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/// Partial specialization for Ampere Architecture
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template <
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/// Element type for A matrix operand
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typename ElementA,
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/// Layout type for A matrix operand
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typename LayoutA,
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/// Access granularity of A matrix in units of elements
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int kAlignmentA,
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/// Element type for C and D matrix operands
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typename ElementC,
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/// Fill Mode for C (kLower or kUpper)
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FillMode FillModeC,
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/// Element type for internal accumulation
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typename ElementAccumulator,
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/// Threadblock-level tile size (concept: GemmShape)
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typename ThreadblockShape,
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/// Warp-level tile size (concept: GemmShape)
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typename WarpShape,
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/// Warp-level tile size (concept: GemmShape)
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typename InstructionShape,
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/// Epilogue output operator
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typename EpilogueOutputOp,
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/// Threadblock-level swizzling operator
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typename ThreadblockSwizzle,
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/// Number of stages used in the pipelined mainloop
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int Stages,
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/// If true, kernel is configured to support serial reduction in the
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/// epilogue
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bool SplitKSerial,
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/// Operation performed by GEMM
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typename Operator>
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struct DefaultRankK<
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ElementA, LayoutA, kAlignmentA,
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ElementC,layout::RowMajor, FillModeC,
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ElementAccumulator, arch::OpClassTensorOp, arch::Sm80,
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ThreadblockShape, WarpShape, InstructionShape,
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EpilogueOutputOp, ThreadblockSwizzle, Stages, SplitKSerial,
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Operator> {
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/// Define the threadblock-scoped matrix multiply-accumulate (A x AT)
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using Mma = typename cutlass::gemm::threadblock::DefaultMma<
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ElementA, LayoutA,
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kAlignmentA,
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ElementA, typename layout::LayoutTranspose<LayoutA>::type,
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kAlignmentA,
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ElementAccumulator, layout::RowMajor, arch::OpClassTensorOp, arch::Sm80,
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ThreadblockShape, WarpShape, InstructionShape, Stages,
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Operator>::ThreadblockMma;
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static const int kPartitionsK = ThreadblockShape::kK / WarpShape::kK;
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/// Define the epilogue
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using Epilogue =
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typename cutlass::epilogue::threadblock::DefaultEpilogueTensorOpBlas3<
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ThreadblockShape, typename Mma::Operator, kPartitionsK, EpilogueOutputOp,
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EpilogueOutputOp::kCount, BlasMode::kSymmetric>::Epilogue;
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/// Define the kernel-level Rank2 operator.
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using RankKkernel = kernel::RankKUniversal<Mma, Epilogue, ThreadblockSwizzle, FillModeC>;
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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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