/*************************************************************************************************** * Copyright (c) 2023 - 2024 NVIDIA CORPORATION & AFFILIATES. All rights reserved. * SPDX-License-Identifier: BSD-3-Clause * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions are met: * * 1. Redistributions of source code must retain the above copyright notice, this * list of conditions and the following disclaimer. * * 2. Redistributions in binary form must reproduce the above copyright notice, * this list of conditions and the following disclaimer in the documentation * and/or other materials provided with the distribution. * * 3. Neither the name of the copyright holder nor the names of its * contributors may be used to endorse or promote products derived from * this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE * DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE * FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL * DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR * SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, * OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. * **************************************************************************************************/ /* \file \brief Defines operations for all GEMM operation kinds in CUTLASS Library. */ #pragma once #include "cutlass/cutlass.h" #include "cutlass/library/library.h" #include "library_internal.h" #include "cutlass/gemm/dispatch_policy.hpp" /////////////////////////////////////////////////////////////////////////////////////////////////// namespace cutlass::library { /////////////////////////////////////////////////////////////////////////////////////////////////// template class GemmOperation3xBase : public Operation { public: using Operator = Operator_; using OperatorArguments = typename Operator::Arguments; using ElementA = typename Operator::ElementA; using LayoutA = typename Operator::LayoutA; using ElementB = typename Operator::ElementB; using LayoutB = typename Operator::LayoutB; using ElementC = typename Operator::ElementC; using LayoutC = typename Operator::LayoutC; using ElementD = typename Operator::ElementD; using LayoutD = typename Operator::LayoutD; // assuming all tensors use same type for StrideIndex using StrideIndex = typename Operator::LayoutA::Index; using ElementAccumulator = typename Operator::ElementAccumulator; using ElementCompute = typename Operator::EpilogueOutputOp::ElementCompute; private: GemmDescription description_; public: /// Constructor GemmOperation3xBase(char const *name = "unknown_gemm", GemmKind gemm_kind_ = GemmKind::kGemm) { description_.name = name; description_.provider = Provider::kCUTLASS; description_.kind = OperationKind::kGemm; description_.gemm_kind = gemm_kind_; description_.tile_description.threadblock_shape = make_Coord( Operator::ThreadblockShape::kM, Operator::ThreadblockShape::kN, Operator::ThreadblockShape::kK); if constexpr (Operator::ArchTag::kMinComputeCapability >= 90) { description_.tile_description.cluster_shape = make_Coord( Operator::ClusterShape::kM, Operator::ClusterShape::kN, Operator::ClusterShape::kK); } description_.tile_description.threadblock_stages = Operator::kStages; description_.tile_description.warp_count = make_Coord( Operator::WarpCount::kM, Operator::WarpCount::kN, Operator::WarpCount::kK); description_.tile_description.math_instruction.instruction_shape = make_Coord( Operator::InstructionShape::kM, Operator::InstructionShape::kN, Operator::InstructionShape::kK); description_.tile_description.math_instruction.element_accumulator = NumericTypeMap::kId; description_.tile_description.math_instruction.opcode_class = OpcodeClassMap::kId; description_.tile_description.math_instruction.math_operation = MathOperationMap::kId; description_.tile_description.minimum_compute_capability = ArchMap::kMin; description_.tile_description.maximum_compute_capability = ArchMap::kMax; description_.A = make_TensorDescription(Operator::kAlignmentA); description_.B = make_TensorDescription(Operator::kAlignmentB); description_.C = make_TensorDescription(Operator::kAlignmentC); description_.D = make_TensorDescription(Operator::kAlignmentD); description_.element_epilogue = NumericTypeMap::kId; description_.split_k_mode = SplitKMode::kNone; description_.transform_A = ComplexTransformMap::kId; description_.transform_B = ComplexTransformMap::kId; } /// Returns the description of the GEMM operation virtual OperationDescription const & description() const { return description_; } /// Returns the description of the GEMM operation GemmDescription const& get_gemm_description() const { return description_; } }; /////////////////////////////////////////////////////////////////////////////////////////////////// template class GemmUniversal3xOperation : public GemmOperation3xBase { public: using Operator = Operator_; using OperatorArguments = typename Operator::Arguments; using ElementA = typename Operator::ElementA; using LayoutA = typename Operator::LayoutA; using ElementB = typename Operator::ElementB; using LayoutB = typename Operator::LayoutB; using ElementC = typename Operator::ElementC; using LayoutC = typename Operator::LayoutC; using ElementD = typename Operator::ElementD; using LayoutD = typename Operator::LayoutD; using ElementAccumulator = typename Operator::ElementAccumulator; using ElementCompute = typename Operator::EpilogueOutputOp::ElementCompute; using CollectiveMainloop = typename Operator::CollectiveMainloop; using CollectiveEpilogue = typename Operator::CollectiveEpilogue; using ThreadEpilogueOp = typename CollectiveEpilogue::ThreadEpilogueOp; public: /// Constructor GemmUniversal3xOperation(char const *name = "unknown_gemm"): GemmOperation3xBase(name, GemmKind::kUniversal) {} protected: /// Constructs the arguments structure given the configuration and arguments static Status construct_arguments_( OperatorArguments &operator_args, GemmUniversalConfiguration const *configuration) { // NOTE: GemmUniversalConfiguration does not contain problem shapes or batch strides // Do nothing here and construct kernel arguments in update_arguments_ instead // We also cannot construct TMA descriptors without all the arguments available operator_args.mode = configuration->mode; return Status::kSuccess; } template struct UpdateFusionArgs { static Status update_(FusionArgs const& fusion_args, GemmUniversalArguments const &arguments) { // If a custom EVT is instantiated then it is the users's responsibility // to ensure alpha and beta are updated appropriately return Status::kSuccess; } }; template struct UpdateFusionArgs> { static Status update_(FusionArgs& fusion_args, GemmUniversalArguments const &arguments) { if (arguments.pointer_mode == ScalarPointerMode::kHost) { fusion_args.alpha = *static_cast(arguments.alpha); fusion_args.beta = *static_cast(arguments.beta); fusion_args.alpha_ptr = nullptr; fusion_args.beta_ptr = nullptr; return Status::kSuccess; } else if (arguments.pointer_mode == ScalarPointerMode::kDevice) { fusion_args.alpha = 0; fusion_args.beta = 0; fusion_args.alpha_ptr = static_cast(arguments.alpha); fusion_args.beta_ptr = static_cast(arguments.beta); return Status::kSuccess; } else { return Status::kErrorInvalidProblem; } } }; /// Constructs the arguments structure given the configuration and arguments static Status update_arguments_( OperatorArguments &operator_args, GemmUniversalArguments const *arguments) { Status status = Status::kSuccess; status = UpdateFusionArgs::update_( operator_args.epilogue.thread, *arguments); if (status != Status::kSuccess) { return status; } // TODO: type erase Arguments structure in 3.0 GEMM operator_args.problem_shape = cute::make_shape( arguments->problem_size.m(), arguments->problem_size.n(), arguments->problem_size.k(), arguments->batch_count); // update arguments operator_args.mainloop.ptr_A = static_cast(arguments->A); operator_args.mainloop.ptr_B = static_cast(arguments->B); operator_args.epilogue.ptr_C = static_cast(arguments->C); operator_args.epilogue.ptr_D = static_cast(arguments->D); operator_args.mainloop.dA = cute::make_int_tuple_from( arguments->lda, arguments->batch_stride_A); operator_args.mainloop.dB = cute::make_int_tuple_from( arguments->ldb, arguments->batch_stride_B); operator_args.epilogue.dC = cute::make_int_tuple_from( arguments->ldc, arguments->batch_stride_C); operator_args.epilogue.dD = operator_args.epilogue.dC; /* Query device SM count to pass onto the kernel as an argument, where needed */ operator_args.hw_info.sm_count = arguments->sm_count; if constexpr (!std::is_const_v) { using Enum_t = decltype(operator_args.scheduler.raster_order); switch (arguments->raster_order) { case RasterOrder::kAlongN: operator_args.scheduler.raster_order = Enum_t::AlongN; break; case RasterOrder::kAlongM: operator_args.scheduler.raster_order = Enum_t::AlongM; break; default: operator_args.scheduler.raster_order = Enum_t::Heuristic; } } return status; } public: /// Returns success if the operation can proceed Status can_implement( void const *configuration_ptr, void const *arguments_ptr) const override { GemmUniversalConfiguration const *configuration = static_cast(configuration_ptr); GemmUniversalArguments const *arguments = static_cast(arguments_ptr); OperatorArguments args; auto status = update_arguments_(args, arguments); if (status != Status::kSuccess) { return status; } // can_implement rules may need access to problem shape args.problem_shape = cute::make_shape( configuration->problem_size.m(), configuration->problem_size.n(), configuration->problem_size.k(), configuration->batch_count); return Operator::can_implement(args); } /// Gets the host-side workspace uint64_t get_host_workspace_size(void const *configuration) const override { return sizeof(Operator); } /// Gets the device-side workspace uint64_t get_device_workspace_size( void const *configuration_ptr,void const *arguments_ptr) const override { OperatorArguments args; auto status = update_arguments_( args, static_cast(arguments_ptr)); if (status != Status::kSuccess) { return 0; } uint64_t size = Operator::get_workspace_size(args); return size; } /// Initializes the workspace Status initialize( void const *configuration_ptr, void *host_workspace, void *device_workspace, cudaStream_t stream = nullptr) const override { Operator *op = new (host_workspace) Operator; return Status::kSuccess; } /// Runs the kernel Status run( void const *arguments_ptr, void *host_workspace, void *device_workspace = nullptr, cudaStream_t stream = nullptr) const override { OperatorArguments args; Status status = update_arguments_(args, static_cast(arguments_ptr)); if (status != Status::kSuccess) { return status; } Operator *op = static_cast(host_workspace); // We need to call initialize() since we have to rebuild TMA desc for every new set of args status = op->run(args, device_workspace, stream); return status; } }; /////////////////////////////////////////////////////////////////////////////////////////////////// } // namespace cutlass::library ///////////////////////////////////////////////////////////////////////////////////////////////////