350 lines
14 KiB
C++
350 lines
14 KiB
C++
/***************************************************************************************************
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* Copyright (c) 2023 - 2024 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 Defines operations for all GEMM operation kinds in CUTLASS Library.
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*/
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#pragma once
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#include "cutlass/cutlass.h"
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#include "cutlass/library/library.h"
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#include "library_internal.h"
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#include "cutlass/gemm/dispatch_policy.hpp"
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///////////////////////////////////////////////////////////////////////////////////////////////////
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namespace cutlass::library {
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///////////////////////////////////////////////////////////////////////////////////////////////////
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template <typename Operator_>
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class GemmOperation3xBase : public Operation {
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public:
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using Operator = Operator_;
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using OperatorArguments = typename Operator::Arguments;
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using ElementA = typename Operator::ElementA;
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using LayoutA = typename Operator::LayoutA;
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using ElementB = typename Operator::ElementB;
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using LayoutB = typename Operator::LayoutB;
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using ElementC = typename Operator::ElementC;
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using LayoutC = typename Operator::LayoutC;
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using ElementD = typename Operator::ElementD;
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using LayoutD = typename Operator::LayoutD;
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// assuming all tensors use same type for StrideIndex
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using StrideIndex = typename Operator::LayoutA::Index;
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using ElementAccumulator = typename Operator::ElementAccumulator;
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using ElementCompute = typename Operator::EpilogueOutputOp::ElementCompute;
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private:
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GemmDescription description_;
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public:
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/// Constructor
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GemmOperation3xBase(char const *name = "unknown_gemm", GemmKind gemm_kind_ = GemmKind::kGemm) {
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description_.name = name;
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description_.provider = Provider::kCUTLASS;
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description_.kind = OperationKind::kGemm;
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description_.gemm_kind = gemm_kind_;
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description_.tile_description.threadblock_shape = make_Coord(
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Operator::ThreadblockShape::kM,
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Operator::ThreadblockShape::kN,
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Operator::ThreadblockShape::kK);
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if constexpr (Operator::ArchTag::kMinComputeCapability >= 90) {
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description_.tile_description.cluster_shape = make_Coord(
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Operator::ClusterShape::kM,
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Operator::ClusterShape::kN,
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Operator::ClusterShape::kK);
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}
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description_.tile_description.threadblock_stages = Operator::kStages;
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description_.tile_description.warp_count = make_Coord(
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Operator::WarpCount::kM,
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Operator::WarpCount::kN,
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Operator::WarpCount::kK);
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description_.tile_description.math_instruction.instruction_shape = make_Coord(
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Operator::InstructionShape::kM,
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Operator::InstructionShape::kN,
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Operator::InstructionShape::kK);
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description_.tile_description.math_instruction.element_accumulator =
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NumericTypeMap<ElementAccumulator>::kId;
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description_.tile_description.math_instruction.opcode_class =
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OpcodeClassMap<typename Operator::OperatorClass>::kId;
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description_.tile_description.math_instruction.math_operation =
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MathOperationMap<typename Operator::MathOperator>::kId;
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description_.tile_description.minimum_compute_capability =
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ArchMap<typename Operator::ArchTag, typename Operator::OperatorClass>::kMin;
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description_.tile_description.maximum_compute_capability =
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ArchMap<typename Operator::ArchTag, typename Operator::OperatorClass>::kMax;
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description_.A = make_TensorDescription<ElementA, LayoutA>(Operator::kAlignmentA);
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description_.B = make_TensorDescription<ElementB, LayoutB>(Operator::kAlignmentB);
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description_.C = make_TensorDescription<ElementC, LayoutC>(Operator::kAlignmentC);
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description_.D = make_TensorDescription<ElementD, LayoutD>(Operator::kAlignmentD);
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description_.element_epilogue = NumericTypeMap<ElementCompute>::kId;
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description_.split_k_mode = SplitKMode::kNone;
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description_.transform_A = ComplexTransformMap<Operator::kTransformA>::kId;
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description_.transform_B = ComplexTransformMap<Operator::kTransformB>::kId;
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}
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/// Returns the description of the GEMM operation
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virtual OperationDescription const & description() const {
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return description_;
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}
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/// Returns the description of the GEMM operation
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GemmDescription const& get_gemm_description() const {
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return description_;
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}
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};
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///////////////////////////////////////////////////////////////////////////////////////////////////
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template <typename Operator_>
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class GemmUniversal3xOperation : public GemmOperation3xBase<Operator_> {
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public:
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using Operator = Operator_;
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using OperatorArguments = typename Operator::Arguments;
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using ElementA = typename Operator::ElementA;
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using LayoutA = typename Operator::LayoutA;
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using ElementB = typename Operator::ElementB;
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using LayoutB = typename Operator::LayoutB;
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using ElementC = typename Operator::ElementC;
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using LayoutC = typename Operator::LayoutC;
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using ElementD = typename Operator::ElementD;
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using LayoutD = typename Operator::LayoutD;
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using ElementAccumulator = typename Operator::ElementAccumulator;
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using ElementCompute = typename Operator::EpilogueOutputOp::ElementCompute;
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using CollectiveMainloop = typename Operator::CollectiveMainloop;
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using CollectiveEpilogue = typename Operator::CollectiveEpilogue;
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using ThreadEpilogueOp = typename CollectiveEpilogue::ThreadEpilogueOp;
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public:
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/// Constructor
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GemmUniversal3xOperation(char const *name = "unknown_gemm"):
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GemmOperation3xBase<Operator_>(name, GemmKind::kUniversal) {}
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protected:
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/// Constructs the arguments structure given the configuration and arguments
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static Status construct_arguments_(
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OperatorArguments &operator_args, GemmUniversalConfiguration const *configuration) {
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// NOTE: GemmUniversalConfiguration does not contain problem shapes or batch strides
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// Do nothing here and construct kernel arguments in update_arguments_ instead
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// We also cannot construct TMA descriptors without all the arguments available
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operator_args.mode = configuration->mode;
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return Status::kSuccess;
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}
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template<class FusionArgs, class = void>
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struct UpdateFusionArgs {
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static Status update_(FusionArgs const& fusion_args, GemmUniversalArguments const &arguments) {
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// If a custom EVT is instantiated then it is the users's responsibility
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// to ensure alpha and beta are updated appropriately
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return Status::kSuccess;
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}
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};
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template<class FusionArgs>
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struct UpdateFusionArgs<FusionArgs, cute::void_t<decltype(FusionArgs{}.alpha)>> {
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static Status update_(FusionArgs& fusion_args, GemmUniversalArguments const &arguments) {
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if (arguments.pointer_mode == ScalarPointerMode::kHost) {
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fusion_args.alpha = *static_cast<ElementCompute const *>(arguments.alpha);
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fusion_args.beta = *static_cast<ElementCompute const *>(arguments.beta);
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fusion_args.alpha_ptr = nullptr;
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fusion_args.beta_ptr = nullptr;
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return Status::kSuccess;
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}
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else if (arguments.pointer_mode == ScalarPointerMode::kDevice) {
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fusion_args.alpha = 0;
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fusion_args.beta = 0;
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fusion_args.alpha_ptr = static_cast<ElementCompute const *>(arguments.alpha);
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fusion_args.beta_ptr = static_cast<ElementCompute const *>(arguments.beta);
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return Status::kSuccess;
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}
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else {
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return Status::kErrorInvalidProblem;
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}
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}
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};
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/// Constructs the arguments structure given the configuration and arguments
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static Status update_arguments_(
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OperatorArguments &operator_args,
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GemmUniversalArguments const *arguments) {
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Status status = Status::kSuccess;
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status = UpdateFusionArgs<decltype(operator_args.epilogue.thread)>::update_(
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operator_args.epilogue.thread, *arguments);
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if (status != Status::kSuccess) {
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return status;
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}
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// TODO: type erase Arguments structure in 3.0 GEMM
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operator_args.problem_shape = cute::make_shape(
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arguments->problem_size.m(),
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arguments->problem_size.n(),
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arguments->problem_size.k(),
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arguments->batch_count);
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// update arguments
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operator_args.mainloop.ptr_A = static_cast<ElementA const *>(arguments->A);
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operator_args.mainloop.ptr_B = static_cast<ElementB const *>(arguments->B);
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operator_args.epilogue.ptr_C = static_cast<ElementC const *>(arguments->C);
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operator_args.epilogue.ptr_D = static_cast<ElementD *>(arguments->D);
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operator_args.mainloop.dA = cute::make_int_tuple_from<typename Operator::GemmKernel::StrideA>(
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arguments->lda, arguments->batch_stride_A);
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operator_args.mainloop.dB = cute::make_int_tuple_from<typename Operator::GemmKernel::StrideB>(
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arguments->ldb, arguments->batch_stride_B);
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operator_args.epilogue.dC = cute::make_int_tuple_from<typename Operator::GemmKernel::StrideC>(
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arguments->ldc, arguments->batch_stride_C);
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operator_args.epilogue.dD = operator_args.epilogue.dC;
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/* Query device SM count to pass onto the kernel as an argument, where needed */
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operator_args.hw_info.sm_count = arguments->sm_count;
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if constexpr (!std::is_const_v<decltype(operator_args.scheduler.raster_order)>) {
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using Enum_t = decltype(operator_args.scheduler.raster_order);
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switch (arguments->raster_order) {
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case RasterOrder::kAlongN:
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operator_args.scheduler.raster_order = Enum_t::AlongN;
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break;
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case RasterOrder::kAlongM:
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operator_args.scheduler.raster_order = Enum_t::AlongM;
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break;
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default:
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operator_args.scheduler.raster_order = Enum_t::Heuristic;
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}
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}
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return status;
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}
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public:
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/// Returns success if the operation can proceed
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Status can_implement(
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void const *configuration_ptr, void const *arguments_ptr) const override {
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GemmUniversalConfiguration const *configuration =
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static_cast<GemmUniversalConfiguration const *>(configuration_ptr);
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GemmUniversalArguments const *arguments =
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static_cast<GemmUniversalArguments const *>(arguments_ptr);
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OperatorArguments args;
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auto status = update_arguments_(args, arguments);
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if (status != Status::kSuccess) {
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return status;
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}
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// can_implement rules may need access to problem shape
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args.problem_shape = cute::make_shape(
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configuration->problem_size.m(),
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configuration->problem_size.n(),
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configuration->problem_size.k(),
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configuration->batch_count);
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return Operator::can_implement(args);
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}
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/// Gets the host-side workspace
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uint64_t get_host_workspace_size(void const *configuration) const override {
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return sizeof(Operator);
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}
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/// Gets the device-side workspace
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uint64_t get_device_workspace_size(
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void const *configuration_ptr,void const *arguments_ptr) const override {
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OperatorArguments args;
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auto status = update_arguments_(
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args, static_cast<GemmUniversalArguments const *>(arguments_ptr));
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if (status != Status::kSuccess) {
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return 0;
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}
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uint64_t size = Operator::get_workspace_size(args);
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return size;
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}
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/// Initializes the workspace
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Status initialize(
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void const *configuration_ptr,
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void *host_workspace,
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void *device_workspace,
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cudaStream_t stream = nullptr) const override {
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Operator *op = new (host_workspace) Operator;
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return Status::kSuccess;
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}
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/// Runs the kernel
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Status run(
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void const *arguments_ptr,
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void *host_workspace,
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void *device_workspace = nullptr,
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cudaStream_t stream = nullptr) const override {
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OperatorArguments args;
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Status status = update_arguments_(args, static_cast<GemmUniversalArguments const *>(arguments_ptr));
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if (status != Status::kSuccess) {
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return status;
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}
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Operator *op = static_cast<Operator *>(host_workspace);
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// We need to call initialize() since we have to rebuild TMA desc for every new set of args
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status = op->run(args, device_workspace, stream);
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return status;
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}
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};
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///////////////////////////////////////////////////////////////////////////////////////////////////
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} // namespace cutlass::library
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///////////////////////////////////////////////////////////////////////////////////////////////////
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