66d9cddc83
* New updates. * Minor profiler updates Co-authored-by: Aniket Shivam <ashivam@nvidia.com>
356 lines
12 KiB
C++
356 lines
12 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 grouped Rank2K.
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*/
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#pragma once
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#include "cutlass/cutlass.h"
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#include "cutlass/complex.h"
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#include "cutlass/layout/matrix.h"
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#include "cutlass/numeric_types.h"
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#include "cutlass/gemm/kernel/rank_2k_transpose_operands.h"
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#include "cutlass/gemm/kernel/default_rank_2k.h"
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#include "cutlass/gemm/kernel/default_rank_2k_complex.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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/////////////////////////////////////////////////////////////////////////////////////////////////
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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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/// Complex elementwise transformation on A operand
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ComplexTransform TransformA,
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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 B matrix operand
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typename ElementB,
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/// Layout type for B matrix operand
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typename LayoutB,
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/// Complex elementwise transformation on B operand
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ComplexTransform TransformB,
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/// Access granularity of B matrix in units of elements
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int kAlignmentB,
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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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/// 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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/// Whether the schedule of problems to visit has been precomputed
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GroupScheduleMode GroupScheduleMode_ = GroupScheduleMode::kDeviceOnly,
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///
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typename Enable = void
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>
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struct DefaultRank2KGrouped;
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/////////////////////////////////////////////////////////////////////////////////////////////////
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//
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// Real-valued grouped Rank2K
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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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/// Complex elementwise transformation on A operand
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ComplexTransform TransformA,
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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 B matrix operand
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typename ElementB,
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/// Layout type for B matrix operand
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typename LayoutB,
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/// Complex elementwise transformation on B operand
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ComplexTransform TransformB,
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/// Access granularity of B matrix in units of elements
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int kAlignmentB,
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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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/// Operation performed by GEMM
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typename Operator,
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/// Blas3 computation mode
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BlasMode BlasMode_,
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/// Whether the schedule of problems to visit has been precomputed
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GroupScheduleMode GroupScheduleMode_
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>
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struct DefaultRank2KGrouped<ElementA, LayoutA, TransformA, kAlignmentA,
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ElementB, LayoutB, TransformB, kAlignmentB,
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ElementC, LayoutC,
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FillModeC, ElementAccumulator, OperatorClass, ArchTag, ThreadblockShape,
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WarpShape, InstructionShape, EpilogueOutputOp,
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ThreadblockSwizzle, Stages, Operator, BlasMode_, GroupScheduleMode_,
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typename std::enable_if< ! cutlass::is_complex<ElementAccumulator>::value>::type
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> {
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// If true, we must construct a 'transposed-and-exchanged' Rank2K operator.
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static bool const kInternalTranspose = platform::is_same<LayoutC, layout::ColumnMajor>::value;
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using MapArguments = kernel::detail::Rank2KMapArguments<
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ElementA,
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LayoutA,
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TransformA,
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kAlignmentA,
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ElementB,
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LayoutB,
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TransformB,
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kAlignmentB,
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LayoutC,
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FillModeC,
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kInternalTranspose
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>;
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// Define the default grouped Rank2K kernel
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using DefaultRank2Kkernel = typename kernel::DefaultRank2K<
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typename MapArguments::ElementA,
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typename MapArguments::LayoutA,
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MapArguments::kAlignmentA,
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typename MapArguments::ElementB,
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typename MapArguments::LayoutB,
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MapArguments::kAlignmentB,
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ElementC,
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typename MapArguments::LayoutC,
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MapArguments::kFillModeC,
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ElementAccumulator,
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OperatorClass,
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ArchTag,
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ThreadblockShape,
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WarpShape,
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InstructionShape,
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EpilogueOutputOp,
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ThreadblockSwizzle,
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Stages,
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false, // SplitKSerial
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Operator,
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BlasMode_
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>::Rank2Kkernel;
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/// Define the kernel in terms of the default kernel
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using Rank2Kkernel = kernel::Rank2KGrouped<
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typename DefaultRank2Kkernel::Mma1,
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typename DefaultRank2Kkernel::Mma2,
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typename DefaultRank2Kkernel::Epilogue,
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ThreadblockSwizzle,
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TransformA,
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TransformB,
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DefaultRank2Kkernel::kFillModeC,
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DefaultRank2Kkernel::kBlasMode,
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GroupScheduleMode_,
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kInternalTranspose
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>;
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};
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/////////////////////////////////////////////////////////////////////////////////////////////////
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//
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// Complex-valued grouped Rank2K
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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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/// Complex elementwise transformation on A operand
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ComplexTransform TransformA,
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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 B matrix operand
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typename ElementB,
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/// Layout type for B matrix operand
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typename LayoutB,
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/// Complex elementwise transformation on B operand
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ComplexTransform TransformB,
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/// Access granularity of B matrix in units of elements
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int kAlignmentB,
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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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/// Operation performed by GEMM
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typename Operator,
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/// Blas3 computation mode
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BlasMode BlasMode_,
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/// Whether the schedule of problems to visit has been precomputed
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GroupScheduleMode GroupScheduleMode_
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>
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struct DefaultRank2KGrouped<ElementA, LayoutA, TransformA, kAlignmentA,
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ElementB, LayoutB, TransformB, kAlignmentB,
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ElementC, LayoutC,
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FillModeC, ElementAccumulator, OperatorClass, ArchTag, ThreadblockShape,
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WarpShape, InstructionShape, EpilogueOutputOp,
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ThreadblockSwizzle, Stages, Operator, BlasMode_, GroupScheduleMode_,
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typename std::enable_if<cutlass::is_complex<ElementAccumulator>::value>::type
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> {
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// If true, we must construct a 'transposed-and-exchanged' Rank2K operator.
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static bool const kInternalTranspose = platform::is_same<LayoutC, layout::ColumnMajor>::value;
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using MapArguments = kernel::detail::Rank2KMapArguments<
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ElementA,
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LayoutA,
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TransformA,
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kAlignmentA,
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ElementB,
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LayoutB,
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TransformB,
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kAlignmentB,
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LayoutC,
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FillModeC,
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kInternalTranspose
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>;
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// Define the default grouped Rank2K kernel
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using DefaultRank2Kkernel = typename kernel::DefaultRank2KComplex<
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typename MapArguments::ElementA,
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typename MapArguments::LayoutA,
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typename MapArguments::ElementB,
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typename MapArguments::LayoutB,
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ElementC,
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typename MapArguments::LayoutC,
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MapArguments::kFillModeC,
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ElementAccumulator,
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OperatorClass,
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ArchTag,
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ThreadblockShape,
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WarpShape,
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InstructionShape,
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EpilogueOutputOp,
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ThreadblockSwizzle,
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Stages,
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MapArguments::kTransformA,
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MapArguments::kTransformB,
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Operator,
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false, // SplitKSerial
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BlasMode_
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>::Rank2Kkernel;
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/// Define the kernel in terms of the default kernel
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/// Pass through the user-provided TransformA and TransformB so as to
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/// correctly set public-facing TransformA and TransformB in kernel::Rank2KGrouped.
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/// This is needed because kernel::DefaultRank2KComplex may change TransformA and
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/// TransformB that become template arguments to Mma1 and Mma2.
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using Rank2Kkernel = kernel::Rank2KGrouped<
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typename DefaultRank2Kkernel::Mma1,
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typename DefaultRank2Kkernel::Mma2,
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typename DefaultRank2Kkernel::Epilogue,
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ThreadblockSwizzle,
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TransformA,
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TransformB,
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DefaultRank2Kkernel::kFillModeC,
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DefaultRank2Kkernel::kBlasMode,
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GroupScheduleMode_,
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kInternalTranspose
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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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/////////////////////////////////////////////////////////////////////////////////////////////////
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