#ifndef DEVICE_GEMM_XDL_HPP #define DEVICE_GEMM_XDL_HPP #include #include #include "device.hpp" #include "device_base.hpp" #include "device_gemm.hpp" #include "common_header.hpp" #include "tensor_layout.hpp" #include "tensor_descriptor.hpp" #include "tensor_descriptor_helper.hpp" #include "gridwise_gemm_xdlops_v2r3.hpp" #include "gemm_specialization.hpp" namespace ck { namespace tensor_operation { namespace device { template struct DeviceGemmXdl : public DeviceGemm { static constexpr auto I0 = Number<0>{}; static constexpr auto I1 = Number<1>{}; static constexpr auto I2 = Number<2>{}; static constexpr auto K1Number = Number{}; static auto MakeAGridDescriptor_K0_M_K1(index_t M, index_t K, index_t StrideA) { assert(K % K1 == 0); const index_t K0 = K / K1; const auto a_grid_desc_m_k = [&]() { if constexpr(is_same::value) { return make_naive_tensor_descriptor(make_tuple(M, K), make_tuple(StrideA, I1)); } else if constexpr(is_same::value) { return make_naive_tensor_descriptor(make_tuple(M, K), make_tuple(I1, StrideA)); } }(); if constexpr(GemmSpecialization == GemmSpecialization_t::MNPadding) { const auto PadM = (MPerBlock - M % MPerBlock) % MPerBlock; return transform_tensor_descriptor( a_grid_desc_m_k, make_tuple(make_unmerge_transform(make_tuple(K0, K1Number)), make_right_pad_transform(M, PadM)), make_tuple(Sequence<1>{}, Sequence<0>{}), make_tuple(Sequence<0, 2>{}, Sequence<1>{})); } else { return transform_tensor_descriptor( a_grid_desc_m_k, make_tuple(make_unmerge_transform(make_tuple(K0, K1Number)), make_pass_through_transform(M)), make_tuple(Sequence<1>{}, Sequence<0>{}), make_tuple(Sequence<0, 2>{}, Sequence<1>{})); } } static auto MakeBGridDescriptor_K0_N_K1(index_t K, index_t N, index_t StrideB) { assert(K % K1 == 0); const index_t K0 = K / K1; const auto b_grid_desc_k_n = [&]() { if constexpr(is_same::value) { return make_naive_tensor_descriptor(make_tuple(K, N), make_tuple(StrideB, I1)); } else if constexpr(is_same::value) { return make_naive_tensor_descriptor(make_tuple(K, N), make_tuple(I1, StrideB)); } }(); if constexpr(GemmSpecialization == GemmSpecialization_t::MNPadding) { const auto PadN = (NPerBlock - N % NPerBlock) % NPerBlock; return transform_tensor_descriptor( b_grid_desc_k_n, make_tuple(make_unmerge_transform(make_tuple(K0, K1Number)), make_right_pad_transform(N, PadN)), make_tuple(Sequence<0>{}, Sequence<1>{}), make_tuple(Sequence<0, 2>{}, Sequence<1>{})); } else { return transform_tensor_descriptor( b_grid_desc_k_n, make_tuple(make_unmerge_transform(make_tuple(K0, K1Number)), make_pass_through_transform(N)), make_tuple(Sequence<0>{}, Sequence<1>{}), make_tuple(Sequence<0, 2>{}, Sequence<1>{})); } } static auto MakeCGridDescriptor_M_N(index_t M, index_t N, index_t StrideC) { const auto c_grid_desc_m_n = [&]() { if constexpr(is_same::value) { return make_naive_tensor_descriptor(make_tuple(M, N), make_tuple(StrideC, I1)); } else if constexpr(is_same::value) { return make_naive_tensor_descriptor(make_tuple(M, N), make_tuple(I1, StrideC)); } }(); if constexpr(GemmSpecialization == GemmSpecialization_t::MNPadding) { const auto PadM = (MPerBlock - M % MPerBlock) % MPerBlock; const auto PadN = (NPerBlock - N % NPerBlock) % NPerBlock; return transform_tensor_descriptor( c_grid_desc_m_n, make_tuple(make_right_pad_transform(M, PadM), make_right_pad_transform(N, PadN)), make_tuple(Sequence<0>{}, Sequence<1>{}), make_tuple(Sequence<0>{}, Sequence<1>{})); } else { return transform_tensor_descriptor( c_grid_desc_m_n, make_tuple(make_pass_through_transform(M), make_pass_through_transform(N)), make_tuple(Sequence<0>{}, Sequence<1>{}), make_tuple(Sequence<0>{}, Sequence<1>{})); } } using AGridDesc_K0_M_K1 = decltype(MakeAGridDescriptor_K0_M_K1(1, 1, 1)); using BGridDesc_K0_N_K1 = decltype(MakeBGridDescriptor_K0_N_K1(1, 1, 1)); using CGridDesc_M_N = decltype(MakeCGridDescriptor_M_N(1, 1, 1)); // GridwiseGemm using GridwiseGemm = GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3< BlockSize, ADataType, // TODO: distinguish A/B datatype AccDataType, CDataType, InMemoryDataOperationEnum_t::Set, AGridDesc_K0_M_K1, BGridDesc_K0_N_K1, CGridDesc_M_N, AElementwiseOperation, BElementwiseOperation, CElementwiseOperation, MPerBlock, NPerBlock, K0PerBlock, MPerXDL, NPerXDL, K1, MXdlPerWave, NXdlPerWave, ABlockTransferThreadClusterLengths_K0_M_K1, ABlockTransferThreadClusterArrangeOrder, ABlockTransferSrcAccessOrder, ABlockTransferSrcVectorDim, ABlockTransferSrcScalarPerVector, ABlockTransferDstScalarPerVector_K1, false, // AThreadTransferSrcResetCoordinateAfterRun, ABlockLdsAddExtraM, BBlockTransferThreadClusterLengths_K0_N_K1, BBlockTransferThreadClusterArrangeOrder, BBlockTransferSrcAccessOrder, BBlockTransferSrcVectorDim, BBlockTransferSrcScalarPerVector, BBlockTransferDstScalarPerVector_K1, false, // BThreadTransferSrcResetCoordinateAfterRun, BBlockLdsAddExtraN, Sequence<0, 2, 4, 5, 6, 1, 3, 7>, // CThreadTransferSrcDstAccessOrder, CThreadTransferSrcDstVectorDim, CThreadTransferDstScalarPerVector, NumPrefetch>; // Argument struct Argument : public BaseArgument { Argument(const ADataType* p_a_grid, const BDataType* p_b_grid, CDataType* p_c_grid, index_t M, index_t N, index_t K, index_t StrideA, index_t StrideB, index_t StrideC, index_t M01, index_t N01, AElementwiseOperation a_element_op, BElementwiseOperation b_element_op, CElementwiseOperation c_element_op) : p_a_grid_{p_a_grid}, p_b_grid_{p_b_grid}, p_c_grid_{p_c_grid}, a_grid_desc_k0_m_k1_{}, b_grid_desc_k0_n_k1_{}, c_grid_desc_m_n_{}, c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_{}, block_2_ctile_map_{}, M01_{M01}, N01_{N01}, a_element_op_{a_element_op}, b_element_op_{b_element_op}, c_element_op_{c_element_op} { a_grid_desc_k0_m_k1_ = DeviceGemmXdl::MakeAGridDescriptor_K0_M_K1(M, K, StrideA); b_grid_desc_k0_n_k1_ = DeviceGemmXdl::MakeBGridDescriptor_K0_N_K1(K, N, StrideB); c_grid_desc_m_n_ = DeviceGemmXdl::MakeCGridDescriptor_M_N(M, N, StrideC); if(GridwiseGemm::CheckValidity( a_grid_desc_k0_m_k1_, b_grid_desc_k0_n_k1_, c_grid_desc_m_n_, M01_, N01_)) { c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_ = GridwiseGemm::MakeCGridDescriptor_M0_N0_M1_N1_M2_M3_M4_N2(c_grid_desc_m_n_); block_2_ctile_map_ = GridwiseGemm::MakeDefaultBlock2CTileMap(c_grid_desc_m_n_, M01, N01); } } // private: const ADataType* p_a_grid_; const BDataType* p_b_grid_; CDataType* p_c_grid_; AGridDesc_K0_M_K1 a_grid_desc_k0_m_k1_; BGridDesc_K0_N_K1 b_grid_desc_k0_n_k1_; CGridDesc_M_N c_grid_desc_m_n_; typename GridwiseGemm::CGridDesc_M0_N0_M1_N1_M2_M3_M4_N2 c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_; typename GridwiseGemm::DefaultBlock2CTileMap block_2_ctile_map_; index_t M01_; index_t N01_; AElementwiseOperation a_element_op_; BElementwiseOperation b_element_op_; CElementwiseOperation c_element_op_; }; // Invoker struct Invoker : public BaseInvoker { using Argument = DeviceGemmXdl::Argument; float Run(const Argument& arg, int nrepeat = 1) { { std::cout << "arg.a_grid_desc_k0_m_k1_{" << arg.a_grid_desc_k0_m_k1_.GetLength(I0) << ", " << arg.a_grid_desc_k0_m_k1_.GetLength(I1) << ", " << arg.a_grid_desc_k0_m_k1_.GetLength(I2) << "}" << std::endl; std::cout << "arg.b_grid_desc_k0_n_k1_{" << arg.b_grid_desc_k0_n_k1_.GetLength(I0) << ", " << arg.b_grid_desc_k0_n_k1_.GetLength(I1) << ", " << arg.b_grid_desc_k0_n_k1_.GetLength(I2) << "}" << std::endl; std::cout << "arg.c_grid_desc_m_n_{ " << arg.c_grid_desc_m_n_.GetLength(I0) << ", " << arg.c_grid_desc_m_n_.GetLength(I1) << "}" << std::endl; } if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_, arg.b_grid_desc_k0_n_k1_, arg.c_grid_desc_m_n_, arg.M01_, arg.N01_)) { throw std::runtime_error( "wrong! GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3 has invalid setting"); } const index_t grid_size = GridwiseGemm::CalculateGridSize(arg.c_grid_desc_m_n_); const auto K0 = arg.a_grid_desc_k0_m_k1_.GetLength(I0); const bool has_main_k0_block_loop = GridwiseGemm::CalculateHasMainK0BlockLoop(K0); float ave_time = 0; if(has_main_k0_block_loop) { const auto kernel = kernel_gemm_xdlops_v2r3< GridwiseGemm, ADataType, // TODO: distiguish A/B datatype CDataType, remove_reference_t, remove_reference_t, remove_reference_t, AElementwiseOperation, BElementwiseOperation, CElementwiseOperation, remove_reference_t, true>; ave_time = launch_and_time_kernel(kernel, nrepeat, dim3(grid_size), dim3(BlockSize), 0, arg.p_a_grid_, arg.p_b_grid_, arg.p_c_grid_, arg.a_grid_desc_k0_m_k1_, arg.b_grid_desc_k0_n_k1_, arg.c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_, arg.a_element_op_, arg.b_element_op_, arg.c_element_op_, arg.block_2_ctile_map_); } else { const auto kernel = kernel_gemm_xdlops_v2r3< GridwiseGemm, ADataType, // TODO: distiguish A/B datatype CDataType, remove_reference_t, remove_reference_t, remove_reference_t, AElementwiseOperation, BElementwiseOperation, CElementwiseOperation, remove_reference_t, false>; ave_time = launch_and_time_kernel(kernel, nrepeat, dim3(grid_size), dim3(BlockSize), 0, arg.p_a_grid_, arg.p_b_grid_, arg.p_c_grid_, arg.a_grid_desc_k0_m_k1_, arg.b_grid_desc_k0_n_k1_, arg.c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_, arg.a_element_op_, arg.b_element_op_, arg.c_element_op_, arg.block_2_ctile_map_); } return ave_time; } // polymorphic float Run(const BaseArgument* p_arg, int nrepeat = 1) override { return Run(*dynamic_cast(p_arg), nrepeat); } }; static constexpr bool IsValidCompilationParameter() { // TODO: properly implement this check return true; } static bool IsSupportedArgument(const Argument& arg) { return GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_, arg.b_grid_desc_k0_n_k1_, arg.c_grid_desc_m_n_, arg.M01_, arg.N01_); } // polymorphic bool IsSupportedArgument(const BaseArgument* p_arg) override { return IsSupportedArgument(*dynamic_cast(p_arg)); } static auto MakeArgument(const ADataType* p_a, const BDataType* p_b, CDataType* p_c, index_t M, index_t N, index_t K, index_t StrideA, index_t StrideB, index_t StrideC, AElementwiseOperation a_element_op, BElementwiseOperation b_element_op, CElementwiseOperation c_element_op) { return Argument{p_a, p_b, p_c, M, N, K, StrideA, StrideB, StrideC, 1, 1, a_element_op, b_element_op, c_element_op}; } static auto MakeInvoker() { return Invoker{}; } // polymorphic std::unique_ptr MakeArgumentPointer(const void* p_a, const void* p_b, void* p_c, index_t M, index_t N, index_t K, index_t StrideA, index_t StrideB, index_t StrideC, AElementwiseOperation a_element_op, BElementwiseOperation b_element_op, CElementwiseOperation c_element_op, index_t /* KBatch */ = 1) override { return std::make_unique(static_cast(p_a), static_cast(p_b), static_cast(p_c), M, N, K, StrideA, StrideB, StrideC, 1, 1, a_element_op, b_element_op, c_element_op); } // polymorphic std::unique_ptr MakeInvokerPointer() override { return std::make_unique(Invoker{}); } // polymorphic std::string GetTypeString() const override { auto str = std::stringstream(); // clang-format off str << "DeviceGemmXdl" << "<" << BlockSize << ", " << MPerBlock << ", " << NPerBlock << ", " << K0PerBlock << ", " << K1 << ", " << MPerXDL << ", " << NPerXDL << ", " << MXdlPerWave << ", " << NXdlPerWave << ">"; // clang-format on return str.str(); } }; } // namespace device } // namespace tensor_operation } // namespace ck #endif