gemm_bquant_pipeline_ag_bg_cr_v3.hpp Source File

gemm_bquant_pipeline_ag_bg_cr_v3.hpp Source File#

Composable Kernel: gemm_bquant_pipeline_ag_bg_cr_v3.hpp Source File
// SPDX-License-Identifier: MIT
// Copyright (c) 2025, Advanced Micro Devices, Inc. All rights reserved.
 
#pragma once
 
#include <string>
#include <sstream>
 
#include "ck_tile/core.hpp"
#include "ck_tile/ops/gemm/pipeline/gemm_universal_pipeline_ag_bg_cr_policy.hpp"
#include "ck_tile/ops/gemm/pipeline/gemm_pipeline_ag_bg_cr_scheduler.hpp"
#include "ck_tile/ops/gemm_quant/pipeline/gemm_bquant_pipeline_ag_bg_cr_base.hpp"
#include "ck_tile/host/concat.hpp"
 
namespace ck_tile {
 
// Compute optimized pipeline
// GlobalPrefetchStages: 2
// LocalPreFillStages: 1
// LocalPreFetchStages: 1
// LocalSharedMemoryBuffer: 1
 
template <typename Problem>
struct BaseBQuantGemmPipelineAgBgCrCompV3 : public BaseGemmPipelineAgBgCrCompV3<Problem>
{
    template <typename RunFunction>
    CK_TILE_HOST_DEVICE static auto
    TailHandler(const RunFunction& run_func, bool has_hot_loop, TailNumber tail_number)
    {
        if(has_hot_loop)
        {
            if(tail_number == ck_tile::TailNumber::Full)
            {
                return run_func(
                    ck_tile::bool_constant<true>{},
                    ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Full>{});
            }
            else if(tail_number == ck_tile::TailNumber::Odd)
            {
                return run_func(
                    ck_tile::bool_constant<true>{},
                    ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Odd>{});
            }
            else if(tail_number == ck_tile::TailNumber::Even)
            {
                return run_func(
                    ck_tile::bool_constant<true>{},
                    ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Even>{});
            }
            else
            {
                throw std::runtime_error("Unsupported tail number for this operation !!!");
            }
        }
        else
        {
            if(tail_number == ck_tile::TailNumber::Full)
            {
                return run_func(
                    ck_tile::bool_constant<false>{},
                    ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Full>{});
            }
            else if(tail_number == ck_tile::TailNumber::Odd)
            {
                return run_func(
                    ck_tile::bool_constant<false>{},
                    ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Odd>{});
            }
            else if(tail_number == ck_tile::TailNumber::Even)
            {
                return run_func(
                    ck_tile::bool_constant<false>{},
                    ck_tile::integral_constant<ck_tile::TailNumber, ck_tile::TailNumber::Even>{});
            }
            else
            {
                throw std::runtime_error("Unsupported tail number for this operation !!!");
            }
        }
    }
};
 
template <typename Problem, typename Policy = GemmBQuantPipelineAgBgCrDefaultPolicy>
struct BQuantGemmPipelineAgBgCrCompV3 : public BaseBQuantGemmPipelineAgBgCrCompV3<Problem>
{
    using Base             = BaseGemmPipelineAgBgCrCompV3<Problem>;
    using PipelineImplBase = GemmBQuantPipelineAgBgCrImplBase<Problem, Policy>;
 
    using ADataType      = remove_cvref_t<typename Problem::ADataType>;
    using BDataType      = remove_cvref_t<typename Problem::BDataType>;
    using BQDataType     = remove_cvref_t<typename Problem::BQDataType>;
    using CDataType      = remove_cvref_t<typename Problem::CDataType>;
    using BlockGemmShape = remove_cvref_t<typename Problem::BlockGemmShape>;
    using QuantGroupSize = remove_cvref_t<typename Problem::QuantGroupSize>;
 
    static_assert(QuantGroupSize::kM == 1, "only N/K blocks for BQuant kernel!");
    using I0 = number<0>;
    using I1 = number<1>;
    using I2 = number<2>;
 
    static constexpr index_t APackedSize =
        ck_tile::numeric_traits<remove_cvref_t<ADataType>>::PackedSize;
    static constexpr index_t BPackedSize =
        ck_tile::numeric_traits<remove_cvref_t<BDataType>>::PackedSize;
 
    static constexpr index_t BQPackedSize =
        ck_tile::numeric_traits<remove_cvref_t<BQDataType>>::PackedSize;
 
    using ALayout  = remove_cvref_t<typename Problem::ALayout>;
    using BQLayout = remove_cvref_t<typename Problem::BQLayout>;
    using BLayout  = remove_cvref_t<typename Problem::BLayout>;
    using CLayout  = remove_cvref_t<typename Problem::CLayout>;
 
    using BlockGemm = remove_cvref_t<decltype(Policy::template GetBlockGemm<Problem>())>;
 
    static constexpr index_t BlockSize = Problem::kBlockSize;
    static constexpr index_t MPerBlock = BlockGemmShape::kM;
    static constexpr index_t NPerBlock = BlockGemmShape::kN;
    static constexpr index_t KPerBlock = BlockGemmShape::kK;
 
    static constexpr index_t NPerBlockBQ = BlockGemmShape::kN / QuantGroupSize::kN;
    static constexpr index_t KPerBlockBQ = BlockGemmShape::kK / QuantGroupSize::kK;
 
    static constexpr index_t GetVectorSizeA() { return Policy::template GetVectorSizeA<Problem>(); }
    static constexpr index_t GetVectorSizeB() { return Policy::template GetVectorSizeB<Problem>(); }
    static constexpr index_t GetVectorSizeC() { return Policy::template GetVectorSizeC<Problem>(); }
    static constexpr index_t GetVectorSizeBQ()
    {
        return Policy::template GetVectorSizeBQ<Problem>();
    }
 
    static constexpr index_t GetSmemPackA() { return Policy::template GetSmemPackA<Problem>(); }
    static constexpr index_t GetSmemPackB() { return Policy::template GetSmemPackB<Problem>(); }
 
    static constexpr bool kPadM = Problem::kPadM;
    static constexpr bool kPadN = Problem::kPadN;
    static constexpr bool kPadK = Problem::kPadK;
 
    static constexpr bool DoubleSmemBuffer = Problem::DoubleSmemBuffer;
 
    static constexpr bool HasHotLoop = Problem::HasHotLoop;
    static constexpr auto TailNum    = Problem::TailNum;
    static constexpr auto Scheduler  = Problem::Scheduler;
 
    using Base::PrefetchStages;
 
    [[nodiscard]] CK_TILE_HOST static const std::string GetName()
    {
        // clang-format off
        constexpr index_t WaveNumM = BlockGemmShape::BlockWarps::at(I0{});
        constexpr index_t WaveNumN = BlockGemmShape::BlockWarps::at(I1{});
        return concat('_', "bquant_pipeline_AgBgCrCompV3",
                      concat('x', MPerBlock, NPerBlock, KPerBlock),
                      BlockSize,
                      concat('x', WaveNumM, WaveNumN),
                      concat('x', BlockGemm::WarpGemm::kM, BlockGemm::WarpGemm::kN, BlockGemm::WarpGemm::kK),
                      concat('x', kPadM, kPadN, kPadK), QuantGroupSize::GetName());
        // clang-format on
    }
 
    CK_TILE_HOST_DEVICE static constexpr index_t GetSmemSize()
    {
        return Policy::template GetSmemSize<Problem>();
    }
 
    CK_TILE_HOST static std::string Print()
    {
        constexpr index_t MPerXDL = BlockGemm::WarpGemm::kM;
        constexpr index_t NPerXDL = BlockGemm::WarpGemm::kN;
        constexpr index_t KPerXDL = BlockGemm::WarpGemm::WarpGemmAttribute::Impl::kK;
 
        constexpr index_t WaveSize = 64;
        constexpr index_t WaveNumM = BlockGemmShape::BlockWarps::at(I0{});
        constexpr index_t WaveNumN = BlockGemmShape::BlockWarps::at(I1{});
 
        constexpr index_t A_LDS_Read_Width = GetSmemPackA();
        constexpr index_t B_LDS_Read_Width = GetSmemPackB();
 
        constexpr index_t A_LDS_Write_Width = GetSmemPackA();
        constexpr index_t B_LDS_Write_Width = GetSmemPackB();
 
        constexpr index_t A_Buffer_Load_Inst_Num =
            MPerBlock * KPerBlock / (BlockSize * GetVectorSizeA());
        constexpr index_t B_Buffer_Load_Inst_Num =
            NPerBlock * KPerBlock / (BlockSize * GetVectorSizeB());
        constexpr index_t BQ_Buffer_Load_Inst_Num =
            NPerBlock * KPerBlockBQ / (BlockSize * GetVectorSizeBQ());
 
        constexpr index_t A_LDS_Write_Inst_Num =
            MPerBlock * KPerBlock / (BlockSize * A_LDS_Write_Width);
        constexpr index_t B_LDS_Write_Inst_Num =
            NPerBlock * KPerBlock / (BlockSize * B_LDS_Write_Width);
 
        constexpr index_t A_LDS_Read_Inst_Num =
            WaveNumN * MPerBlock * KPerBlock / (BlockSize * A_LDS_Read_Width);
        constexpr index_t B_LDS_Read_Inst_Num =
            WaveNumM * NPerBlock * KPerBlock / (BlockSize * B_LDS_Read_Width);
 
        constexpr index_t C_MFMA_Inst_Num = MPerBlock * NPerBlock * KPerBlock /
                                            (BlockSize / WaveSize) / (MPerXDL * NPerXDL * KPerXDL);
 
        auto str = std::stringstream{};
 
        str << "A/B vector size: " << GetVectorSizeA() << ", " << GetVectorSizeB() << ", "
            << "BQ vector size: " << GetVectorSizeBQ() << "\n"
            << "A/B LDS read/write width: " << A_LDS_Read_Width << ", " << B_LDS_Read_Width << "\n"
            << "A/B buffer load inst: " << A_Buffer_Load_Inst_Num << ", " << B_Buffer_Load_Inst_Num
            << ", " << "BQ buffer load inst: " << BQ_Buffer_Load_Inst_Num << "\n"
            << "A/B LDS write inst: " << A_LDS_Write_Inst_Num << ", " << B_LDS_Write_Inst_Num
            << "\n"
            << "A/B LDS read inst: " << A_LDS_Read_Inst_Num << ", " << B_LDS_Read_Inst_Num << "\n"
            << "C MFMA inst: " << C_MFMA_Inst_Num << "\n"
            << "QuantGroupSize: " << QuantGroupSize::GetName() << "\n"
            << "KPack: " << BlockGemm::Traits::KPack << "\n"
            << "PrefetchStages: " << PrefetchStages << "\n";
        return str.str();
    }
 
    template <GemmPipelineScheduler Scheduler>
    struct PipelineImpl : public PipelineImplBase
    {
    };
 
    template <>
    struct PipelineImpl<GemmPipelineScheduler::Intrawave> : public PipelineImplBase
    {
        using Base = PipelineImplBase;
 
        template <bool HasHotLoop,
                  TailNumber TailNum,
                  typename ADramBlockWindowTmp,
                  typename BDramBlockWindowTmp,
                  typename BQDramBlockWindowTmp,
                  typename AElementFunction,
                  typename BElementFunction>
        CK_TILE_DEVICE auto operator()(const ADramBlockWindowTmp& a_dram_block_window_tmp,
                                       const AElementFunction& a_element_func,
                                       const BDramBlockWindowTmp& b_dram_block_window_tmp,
                                       const BElementFunction& b_element_func,
                                       const BQDramBlockWindowTmp& bq_dram_block_window_tmp,
                                       index_t num_loop,
                                       void* p_smem) const
        {
            static_assert(
                std::is_same_v<ADataType, remove_cvref_t<typename ADramBlockWindowTmp::DataType>> &&
                    std::is_same_v<BDataType,
                                   remove_cvref_t<typename BDramBlockWindowTmp::DataType>> &&
                    std::is_same_v<BQDataType,
                                   remove_cvref_t<typename BQDramBlockWindowTmp::DataType>>,
                "A/B/BQ Dram block window should have the same data type as appropriate "
                "([A|B|BQ]DataType) defined in Problem definition!");
 
            constexpr bool is_a_col_major =
                std::is_same_v<ALayout, tensor_layout::gemm::ColumnMajor>;
            constexpr bool is_bq_col_major =
                std::is_same_v<BQLayout, tensor_layout::gemm::ColumnMajor>;
            constexpr bool is_b_row_major = std::is_same_v<BLayout, tensor_layout::gemm::RowMajor>;
 
            static_assert(is_bq_col_major, "Bq must be col major (row major not supported yet)");
            static_assert(KPerBlockBQ == BQDramBlockWindowTmp{}.get_window_lengths()[I0{}] &&
                              NPerBlockBQ == BQDramBlockWindowTmp{}.get_window_lengths()[I1{}],
                          "Bq block window has incorrect lengths for defined BqLayout!");
 
            static_assert(is_a_col_major
                              ? (KPerBlock == ADramBlockWindowTmp{}.get_window_lengths()[I0{}] &&
                                 MPerBlock == ADramBlockWindowTmp{}.get_window_lengths()[I1{}])
                              : (MPerBlock == ADramBlockWindowTmp{}.get_window_lengths()[I0{}] &&
                                 KPerBlock == ADramBlockWindowTmp{}.get_window_lengths()[I1{}]),
                          "A block window has incorrect lengths for defined ALayout!");
            static_assert(is_b_row_major
                              ? (KPerBlock == BDramBlockWindowTmp{}.get_window_lengths()[I0{}] &&
                                 NPerBlock == BDramBlockWindowTmp{}.get_window_lengths()[I1{}])
                              : (NPerBlock == BDramBlockWindowTmp{}.get_window_lengths()[I0{}] &&
                                 KPerBlock == BDramBlockWindowTmp{}.get_window_lengths()[I1{}]),
                          "B block window has incorrect lengths for defined BLayout!");
 
            using ADramTileWindowStep  = typename ADramBlockWindowTmp::BottomTensorIndex;
            using BDramTileWindowStep  = typename BDramBlockWindowTmp::BottomTensorIndex;
            using BQDramTileWindowStep = typename BQDramBlockWindowTmp::BottomTensorIndex;
 
            auto&& [a_lds_block, b_lds_block] = Base::GetABLdsTensorViews(p_smem);
 
            constexpr auto a_lds_load_tile_distr =
                make_static_tile_distribution(BlockGemm::MakeABlockDistributionEncode());
            constexpr auto b_lds_load_tile_distr =
                make_static_tile_distribution(BlockGemm::MakeBBlockDistributionEncode());
 
            auto&& [a_copy_dram_window, a_copy_lds_window, a_lds_gemm_window] =
                Base::GetAWindows(a_dram_block_window_tmp, a_lds_block, a_lds_load_tile_distr);
            auto&& [b_copy_dram_window, b_copy_lds_window, b_lds_gemm_window] =
                Base::GetBWindows(b_dram_block_window_tmp, b_lds_block, b_lds_load_tile_distr);
            auto bq_copy_dram_window = Base::GetBQDramLoadWindow(bq_dram_block_window_tmp);
 
            using ABlockTileDistr  = decltype(a_copy_dram_window.get_tile_distribution());
            using BBlockTileDistr  = decltype(b_copy_dram_window.get_tile_distribution());
            using BQBlockTileDistr = decltype(bq_copy_dram_window.get_tile_distribution());
 
            using ABlockTile =
                decltype(make_static_distributed_tensor<ADataType>(ABlockTileDistr{}));
            using BBlockTile =
                decltype(make_static_distributed_tensor<BDataType>(BBlockTileDistr{}));
            using BQBlockTile =
                decltype(make_static_distributed_tensor<BQDataType>(BQBlockTileDistr{}));
 
            auto block_gemm = BlockGemm();
 
            ABlockTile a_block_tile;
            BBlockTile b_block_tile;
            BQBlockTile bq_block_tile[2];
            int currIdx = 0;
 
            auto c_block_tile = block_gemm.MakeCBlockTile();
 
            constexpr ADramTileWindowStep a_dram_tile_window_step =
                is_a_col_major ? make_array(KPerBlock, 0) : make_array(0, KPerBlock);
            constexpr BDramTileWindowStep b_dram_tile_window_step =
                is_b_row_major ? make_array(KPerBlock, 0) : make_array(0, KPerBlock);
            constexpr BQDramTileWindowStep bq_dram_tile_window_step =
                is_bq_col_major ? make_array(KPerBlockBQ, 0) : make_array(0, KPerBlockBQ);
 
            // DRAM prefetch (global read 0)
            Base::GlobalPrefetch(a_block_tile, a_copy_dram_window, a_dram_tile_window_step);
            Base::GlobalPrefetch(b_block_tile, b_copy_dram_window, b_dram_tile_window_step);
            Base::GlobalPrefetch(
                bq_block_tile[currIdx], bq_copy_dram_window, bq_dram_tile_window_step);
 
            tile_elementwise_inout([](auto& c) { c = 0; }, c_block_tile);
 
            if constexpr(is_a_col_major)
            {
                auto a_shuffle_tmp = make_static_distributed_tensor<ADataType>(
                    Policy::template make_shuffled_2d_static_tile_distribution<Problem>());
                transpose_tile2d(a_shuffle_tmp, a_block_tile);
                Base::LocalPrefill(a_copy_lds_window, a_shuffle_tmp, a_element_func);
            }
            else
            {
                Base::LocalPrefill(a_copy_lds_window, a_block_tile, a_element_func);
            }
 
            if constexpr(is_b_row_major)
            {
                auto b_shuffle_tmp = make_static_distributed_tensor<BDataType>(
                    Policy::template make_shuffled_2d_static_tile_distribution<Problem>());
                transpose_tile2d(b_shuffle_tmp, b_block_tile);
                Base::LocalPrefill(b_copy_lds_window, b_shuffle_tmp, b_element_func);
            }
            else
            {
                Base::LocalPrefill(b_copy_lds_window, b_block_tile, b_element_func);
            }
 
            Base::GlobalPrefetch(a_block_tile, a_copy_dram_window, a_dram_tile_window_step);
            Base::GlobalPrefetch(b_block_tile, b_copy_dram_window, b_dram_tile_window_step);
 
            block_sync_lds();
 
            block_gemm.LocalPrefetch(a_lds_gemm_window, b_lds_gemm_window);
 
            __builtin_amdgcn_sched_barrier(0);
 
            if constexpr(HasHotLoop)
            {
                constexpr index_t tail_count =
                    ((TailNum == TailNumber::Full) || (TailNum == TailNumber::Odd)) ? 1 : 2;
                index_t i = 0;
                do
                {
                    block_sync_lds();
 
                    if constexpr(is_a_col_major)
                    {
                        auto a_shuffle_tmp = make_static_distributed_tensor<ADataType>(
                            Policy::template MakeShuffledARegTileDistribution<Problem>());
                        transpose_tile2d(a_shuffle_tmp, a_block_tile);
                        Base::LocalPrefill(a_copy_lds_window, a_shuffle_tmp, a_element_func);
                    }
                    else
                    {
                        Base::LocalPrefill(a_copy_lds_window, a_block_tile, a_element_func);
                    }
                    if constexpr(is_b_row_major)
                    {
                        auto b_shuffle_tmp = make_static_distributed_tensor<BDataType>(
                            Policy::template MakeShuffledBRegTileDistribution<Problem>());
                        transpose_tile2d(b_shuffle_tmp, b_block_tile);
                        Base::LocalPrefill(b_copy_lds_window, b_shuffle_tmp, b_element_func);
                    }
                    else
                    {
                        Base::LocalPrefill(b_copy_lds_window, b_block_tile, b_element_func);
                    }
 
                    Base::GlobalPrefetch(a_block_tile, a_copy_dram_window, a_dram_tile_window_step);
                    Base::GlobalPrefetch(b_block_tile, b_copy_dram_window, b_dram_tile_window_step);
                    Base::GlobalPrefetch(bq_block_tile[(currIdx + 1) % 2],
                                         bq_copy_dram_window,
                                         bq_dram_tile_window_step);
 
                    block_gemm(
                        c_block_tile, bq_block_tile[currIdx], a_lds_gemm_window, b_lds_gemm_window);
 
                    currIdx = (currIdx + 1) % 2;
 
                    block_sync_lds();
 
                    block_gemm.LocalPrefetch(a_lds_gemm_window, b_lds_gemm_window);
                    __builtin_amdgcn_sched_barrier(0);
 
                    i += 1;
                } while(i < (num_loop - tail_count));
            }
            // tail
            if constexpr((TailNum == TailNumber::Full) || (TailNum == TailNumber::Odd))
            {
                block_gemm(
                    c_block_tile, bq_block_tile[currIdx], a_lds_gemm_window, b_lds_gemm_window);
            }
            else
            {
                Base::GlobalPrefetch(bq_block_tile[(currIdx + 1) % 2],
                                     bq_copy_dram_window,
                                     bq_dram_tile_window_step);
                block_gemm(
                    c_block_tile, bq_block_tile[currIdx], a_lds_gemm_window, b_lds_gemm_window);
                block_sync_lds();
 
                currIdx = (currIdx + 1) % 2;
 
                if constexpr(is_a_col_major)
                {
                    auto a_shuffle_tmp = make_static_distributed_tensor<ADataType>(
                        Policy::template MakeShuffledARegTileDistribution<Problem>());
                    transpose_tile2d(a_shuffle_tmp, a_block_tile);
                    Base::LocalPrefill(a_copy_lds_window, a_shuffle_tmp, a_element_func);
                }
                else
                {
                    Base::LocalPrefill(a_copy_lds_window, a_block_tile, a_element_func);
                }
                if constexpr(is_b_row_major)
                {
                    auto b_shuffle_tmp = make_static_distributed_tensor<BDataType>(
                        Policy::template MakeShuffledBRegTileDistribution<Problem>());
                    transpose_tile2d(b_shuffle_tmp, b_block_tile);
                    Base::LocalPrefill(b_copy_lds_window, b_shuffle_tmp, b_element_func);
                }
                else
                {
                    Base::LocalPrefill(b_copy_lds_window, b_block_tile, b_element_func);
                }
                block_sync_lds();
                block_gemm.LocalPrefetch(a_lds_gemm_window, b_lds_gemm_window);
                block_gemm(
                    c_block_tile, bq_block_tile[currIdx], a_lds_gemm_window, b_lds_gemm_window);
            }
            return c_block_tile;
        }
    };
    template <typename ADramBlockWindowTmp,
              typename BDramBlockWindowTmp,
              typename BQDramBlockWindowTmp>
    CK_TILE_DEVICE auto operator()(const ADramBlockWindowTmp& a_dram_block_window_tmp,
                                   const BDramBlockWindowTmp& b_dram_block_window_tmp,
                                   const BQDramBlockWindowTmp& bq_dram_block_window_tmp,
                                   index_t num_loop,
                                   void* p_smem) const
    {
        return PipelineImpl<Scheduler>{}.template operator()<HasHotLoop, TailNum>(
            a_dram_block_window_tmp,
            [](const ADataType& a) { return a; },
            b_dram_block_window_tmp,
            [](const BDataType& b) { return b; },
            bq_dram_block_window_tmp,
            num_loop,
            p_smem);
    }
    template <typename ADramBlockWindowTmp,
              typename BDramBlockWindowTmp,
              typename BQDramBlockWindowTmp>
    CK_TILE_DEVICE auto operator()(const ADramBlockWindowTmp& a_dram_block_window_tmp,
                                   const BDramBlockWindowTmp& b_dram_block_window_tmp,
                                   const BQDramBlockWindowTmp& bq_dram_block_window_tmp,
                                   index_t num_loop,
                                   bool has_hot_loop,
                                   TailNumber tail_number,
                                   void* p_smem) const
    {
        const auto RunPipeline = [&](auto has_hot_loop_, auto tail_number_) {
            constexpr bool hot_loop = has_hot_loop_.value;
            constexpr auto tail_num = tail_number_.value;
            return PipelineImpl<Scheduler>{}.template operator()<hot_loop, tail_num>(
                a_dram_block_window_tmp,
                [](const ADataType& a) { return a; },
                b_dram_block_window_tmp,
                [](const BDataType& b) { return b; },
                bq_dram_block_window_tmp,
                num_loop,
                p_smem);
        };
        return Base::TailHandler(RunPipeline, has_hot_loop, tail_number);
    }
};
 
} // namespace ck_tile