/*************************************************************************************************** * Copyright (c) 2017 - 2023 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. * **************************************************************************************************/ #include "cute/tensor.hpp" #include "cutlass/epilogue/thread/linear_combination.h" #include "cutlass/gemm/collective/collective_builder.hpp" #include "cutlass/gemm/kernel/gemm_universal.hpp" #include "cutlass/epilogue/collective/default_epilogue.hpp" namespace nvrtc { namespace thread { template< typename ElementA, typename ElementB, typename ElementC, typename TileShape, typename ClusterShape, bool kTransA, bool kTransB, int RANK_M, int RANK_N, int RANK_K, int RANK_L > struct ContractionKernel { using ElementScalar = float; using ElementAccum = float; using EpilogueThread = cutlass::epilogue::thread::LinearCombination; static constexpr cute::GMMA::Major majorA = ! kTransA ? cute::GMMA::Major::MN : cute::GMMA::Major::K; static constexpr cute::GMMA::Major majorB = ! kTransB ? cute::GMMA::Major::K : cute::GMMA::Major::MN; /// Kernel config typedef int64_t stride_type; typedef int32_t extent_type; static constexpr const stride_type* stride_null = nullptr; static constexpr const extent_type* extent_null = nullptr; template static constexpr auto make_stride_tuple(Indexable const& t, int n, int64_t init_default = 0) { static_assert(Rank > 1); if constexpr (IsMajor) { return cute::transform(cute::make_seq{}, [&](auto i) { if constexpr (i == 0) { return cute::Int<1>{}; } else { return i < n ? t[i] : init_default; } }); } else { return cute::make_int_tuple(t, n, init_default); } } using StrideA = decltype(cute::make_stride( make_stride_tuple(stride_null, 0, 0), make_stride_tuple(stride_null, 0, 0), cute::make_int_tuple(stride_null, 0, 0))); using StrideB = decltype(cute::make_stride( make_stride_tuple(stride_null, 0, 0), make_stride_tuple(stride_null, 0, 0), cute::make_int_tuple(stride_null, 0, 0))); using StrideC = decltype(cute::make_stride( cute::make_int_tuple(stride_null, 0, 0), cute::make_int_tuple(stride_null, 0, 0), cute::make_int_tuple(stride_null, 0, 0))); using ProblemShape = decltype(cute::make_shape( cute::make_int_tuple(extent_null, 0, 0), cute::make_int_tuple(extent_null, 0, 0), cute::make_int_tuple(extent_null, 0, 0), cute::make_int_tuple(extent_null, 0, 0))); using CollectiveOp = typename cutlass::gemm::collective::CollectiveBuilder< cutlass::arch::Sm90, cutlass::arch::OpClassTensorOp, ElementA, StrideA, 16 / sizeof(ElementA), ElementB, StrideB, 16 / sizeof(ElementB), ElementAccum, TileShape, ClusterShape, cutlass::gemm::collective::StageCountAuto, cutlass::gemm::KernelTmaWarpSpecialized >::CollectiveOp; using EpilogueOutputOp = cutlass::epilogue::collective::DefaultEpilogue; using CollectiveEpilogue = cutlass::epilogue::collective::detail::Sm90TmaWarpSpecializedAdapter; using Kernel = cutlass::gemm::kernel::GemmUniversal< ProblemShape, CollectiveOp, CollectiveEpilogue>; }; } // namespace nvrtc } // namespace thread