#ifndef CK_GRIDWISE_GEMM_XDLOPS_V3R1_HPP
#define CK_GRIDWISE_GEMM_XDLOPS_V3R1_HPP

#include "common_header.hpp"
#include "multi_index_transform_helper.hpp"
#include "tensor_descriptor.hpp"
#include "tensor_descriptor_helper.hpp"
#include "blockwise_gemm_xdlops.hpp"
#include "blockwise_tensor_slice_transfer_v4r1.hpp"
#include "blockwise_tensor_slice_transfer_v6r1.hpp"
#include "threadwise_tensor_slice_transfer.hpp"
#include "gridwise_gemm_pipeline_v1.hpp"
#include "tensor_space_filling_curve.hpp"

namespace ck {

template <typename GridwiseGemm,
          typename FloatAB,
          typename FloatC,
          typename AGridDesc_AK0_M_AK1,
          typename BGridDesc_BK0_N_BK1,
          typename CGridDescriptor_MBlock_MXdlPerWave_MWaveMPerXdl_NBlock_NXdlPerWave_NWaveNPerXdl,
          typename AElementwiseOperation,
          typename BElementwiseOperation,
          typename CElementwiseOperation,
          typename Block2CTileMap,
          bool HasMainK0BlockLoop>
__global__ void
#if CK_USE_LAUNCH_BOUNDS
    __launch_bounds__(CK_MAX_THREAD_PER_BLOCK, CK_MIN_BLOCK_PER_CU)
#endif
        kernel_gemm_xdlops_v3r1(
            const FloatAB* __restrict__ p_a_grid,
            const FloatAB* __restrict__ p_b_grid,
            FloatC* __restrict__ p_c_grid,
            const AGridDesc_AK0_M_AK1 a_grid_desc_ak0_m_ak1,
            const BGridDesc_BK0_N_BK1 b_grid_desc_bk0_n_bk1,
            const CGridDescriptor_MBlock_MXdlPerWave_MWaveMPerXdl_NBlock_NXdlPerWave_NWaveNPerXdl
                c_grid_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl,
            const AElementwiseOperation a_element_op,
            const BElementwiseOperation b_element_op,
            const CElementwiseOperation c_element_op,
            const Block2CTileMap block_2_ctile_map)
{
#if (!defined(__HIP_DEVICE_COMPILE__)  || defined(__gfx908__) || defined(__gfx90a__))
    __shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()];

    GridwiseGemm::template Run<HasMainK0BlockLoop>(
        p_a_grid,
        p_b_grid,
        p_c_grid,
        p_shared,
        a_grid_desc_ak0_m_ak1,
        b_grid_desc_bk0_n_bk1,
        c_grid_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl,
        a_element_op,
        b_element_op,
        c_element_op,
        block_2_ctile_map);
#endif //end of if (defined(__gfx908__) || defined(__gfx90a__))
}

template <
    index_t BlockSize,
    typename FloatAB,
    typename FloatAcc,
    typename FloatCShuffle,
    typename FloatC,
    InMemoryDataOperationEnum CGlobalMemoryDataOperation,
    typename AGridDesc_AK0_M_AK1,
    typename BGridDesc_BK0_N_BK1,
    typename CGridDesc_M_N,
    typename AElementwiseOperation,
    typename BElementwiseOperation,
    typename CElementwiseOperation,
    index_t MPerBlock,
    index_t NPerBlock,
    index_t KPerBlock,
    index_t AK1Value,
    index_t BK1Value,
    index_t MPerXdl,
    index_t NPerXdl,
    index_t MXdlPerWave,
    index_t NXdlPerWave,
    typename ABlockTransferThreadClusterLengths_AK0_M_AK1,
    typename ABlockTransferThreadClusterArrangeOrder,
    typename ABlockTransferSrcAccessOrder,
    index_t ABlockTransferSrcVectorDim,
    index_t ABlockTransferSrcScalarPerVector,
    index_t ABlockTransferDstScalarPerVector_K1,
    bool AThreadTransferSrcResetCoordinateAfterRun,
    bool ABlockLdsExtraM,
    typename BBlockTransferThreadClusterLengths_BK0_N_BK1,
    typename BBlockTransferThreadClusterArrangeOrder,
    typename BBlockTransferSrcAccessOrder,
    index_t BBlockTransferSrcVectorDim,
    index_t BBlockTransferSrcScalarPerVector,
    index_t BBlockTransferDstScalarPerVector_K1,
    bool BThreadTransferSrcResetCoordinateAfterRun,
    bool BBlockLdsExtraN,
    index_t CShuffleMXdlPerWavePerShuffle,
    index_t CShuffleNXdlPerWavePerShuffle,
    typename CBlockTransferClusterLengths_MBlock_MXdlPerWave_MWaveMPerXdl_NBlock_NXdlPerWave_NWaveNPerXdl,
    index_t CBlockTransferScalarPerVector_NWaveNPerXdl,
    index_t NumPrefetch = 1>
struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v3r1
{
    static constexpr auto I0 = Number<0>{};
    static constexpr auto I1 = Number<1>{};
    static constexpr auto I2 = Number<2>{};
    static constexpr auto I3 = Number<3>{};
    static constexpr auto I4 = Number<4>{};
    static constexpr auto I5 = Number<5>{};
    static constexpr auto I6 = Number<6>{};
    static constexpr auto I7 = Number<7>{};

    // K1 should be Number<...>
    static constexpr auto AK0 = Number<KPerBlock / AK1Value>{};
    static constexpr auto BK0 = Number<KPerBlock / BK1Value>{};
    static constexpr auto AK1 = Number<AK1Value>{};
    static constexpr auto BK1 = Number<BK1Value>{};

    __host__ __device__ static constexpr auto GetABlockDescriptor_AK0PerBlock_MPerBlock_AK1()
    {
        constexpr auto max_lds_align = AK1;

        // A matrix in LDS memory, dst of blockwise copy
        constexpr auto a_block_desc_ak0_m_ak1 = [&]() {
            if constexpr(ABlockLdsExtraM)
            {
                return make_naive_tensor_descriptor(
                    make_tuple(AK0, Number<MPerBlock>{}, AK1),
                    make_tuple(Number<MPerBlock + 1>{} * AK1, AK1, I1));
            }
            else
            {
                return make_naive_tensor_descriptor_aligned(
                    make_tuple(AK0, Number<MPerBlock>{}, AK1), max_lds_align);
            }
        }();

        return a_block_desc_ak0_m_ak1;
    }

    __host__ __device__ static constexpr auto GetBBlockDescriptor_BK0PerBlock_NPerBlock_BK1()
    {
        constexpr auto max_lds_align = BK1;

        // B matrix in LDS memory, dst of blockwise copy
        constexpr auto b_block_desc_bk0_n_bk1 = [&]() {
            if constexpr(BBlockLdsExtraN)
            {
                return make_naive_tensor_descriptor(
                    make_tuple(BK0, Number<NPerBlock>{}, BK1),
                    make_tuple(Number<NPerBlock + 1>{} * BK1, BK1, I1));
            }
            else
            {
                return make_naive_tensor_descriptor_aligned(
                    make_tuple(BK0, Number<NPerBlock>{}, BK1), max_lds_align);
            }
        }();

        return b_block_desc_bk0_n_bk1;
    }

    __host__ __device__ static constexpr auto
    GetCBlockDescriptor_MBlock_NXdlPerWave_MWaveMPerXdl_NBlock_NXdlPerWave_NWaveNPerXdl()
    {
        constexpr index_t MWave = MPerBlock / (MXdlPerWave * MPerXdl);
        constexpr index_t NWave = NPerBlock / (NXdlPerWave * NPerXdl);

        constexpr auto
            c_block_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl =
                make_naive_tensor_descriptor_packed(
                    make_tuple(I1,
                               Number<CShuffleMXdlPerWavePerShuffle>{},
                               Number<MWave * MPerXdl>{},
                               I1,
                               Number<CShuffleNXdlPerWavePerShuffle>{},
                               Number<NWave * NPerXdl>{}));

        return c_block_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl;
    }

    __host__ __device__ static constexpr index_t GetSharedMemoryNumberOfByte()
    {
        // LDS allocation for A and B: be careful of alignment
        constexpr auto a_block_desc_ak0_m_ak1 = GetABlockDescriptor_AK0PerBlock_MPerBlock_AK1();

        constexpr auto b_block_desc_bk0_n_bk1 = GetBBlockDescriptor_BK0PerBlock_NPerBlock_BK1();

        constexpr auto a_block_space_size_aligned =
            math::integer_least_multiple(a_block_desc_ak0_m_ak1.GetElementSpaceSize(), AK1);

        constexpr auto b_block_space_size_aligned =
            math::integer_least_multiple(b_block_desc_bk0_n_bk1.GetElementSpaceSize(), BK1);

        // LDS allocation for C shuffle in LDS
        constexpr auto c_block_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl =
            GetCBlockDescriptor_MBlock_NXdlPerWave_MWaveMPerXdl_NBlock_NXdlPerWave_NWaveNPerXdl();

        constexpr auto c_block_size =
            c_block_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl
                .GetElementSpaceSize();

        return math::max((a_block_space_size_aligned + b_block_space_size_aligned) *
                             sizeof(FloatAB),
                         c_block_size * sizeof(FloatCShuffle));
    }

    // block_id to matrix tile idx (m0, n0) mapping are controlled by {M01, N01}
    __host__ __device__ static constexpr bool
    CheckValidity(const AGridDesc_AK0_M_AK1& a_grid_desc_ak0_m_ak1,
                  const BGridDesc_BK0_N_BK1& b_grid_desc_bk0_n_bk1,
                  const CGridDesc_M_N& c_grid_desc_m_n,
                  index_t M01,
                  index_t N01)
    {
        // static_assert(is_known_at_compile_time<remove_cv_t<decltype(AK1)>>::value &&
        //               is_known_at_compile_time<remove_cv_t<decltype(BK1)>>::value,
        //               "wrong! K1 need to be known at compile-time");

        static_assert((MPerBlock % (MPerXdl * MXdlPerWave) == 0) &&
                          (NPerBlock % (NXdlPerWave * NPerXdl)) == 0,
                      "Invalid tuning param!");

        const auto M = a_grid_desc_ak0_m_ak1.GetLength(I1);
        const auto N = b_grid_desc_bk0_n_bk1.GetLength(I1);
        const auto K = a_grid_desc_ak0_m_ak1.GetLength(I0) * a_grid_desc_ak0_m_ak1.GetLength(I2);

        if(!(M == c_grid_desc_m_n.GetLength(I0) && N == c_grid_desc_m_n.GetLength(I1)))
            return false;

        if(!(M % MPerBlock == 0 && N % NPerBlock == 0 && K % KPerBlock == 0))
            return false;

        // check NumPrefetch
        if constexpr(NumPrefetch == 1)
        {
            // 1-stage prefetch always supported
        }
        else if constexpr(NumPrefetch == 2)
        {
            // 2-stage prefetch currently only support even number of K0 loop
            // TODO: add support for odd number of K0 loop
            if(!((K / KPerBlock) % 2 == 0))
            {
                return false;
            }
        }
        else
        {
            return false;
        }

        // check M01, N01
        constexpr auto M1 = Number<MPerBlock>{};
        constexpr auto N1 = Number<NPerBlock>{};

        const auto M0 = M / M1;
        const auto N0 = N / N1;

        if(!(M0 % M01 == 0 && N0 % N01 == 0))
            return false;

        // TODO: also check validity of all components (blockwise-copy, threadwise-copy, etc)
        return true;
    }

    __host__ __device__ static constexpr index_t
    CalculateGridSize(const CGridDesc_M_N& c_grid_desc_m_n)
    {
        const auto M = c_grid_desc_m_n.GetLength(I0);
        const auto N = c_grid_desc_m_n.GetLength(I1);

        const index_t grid_size = (M / MPerBlock) * (N / NPerBlock);

        return grid_size;
    }

    // TODO move this function into GEMM-pipeline class
    __host__ __device__ static constexpr bool CalculateHasMainK0BlockLoop(index_t K0)
    {
        const bool has_main_k0_block_loop = ((K0 * AK1) / (NumPrefetch * KPerBlock)) > 1;

        return has_main_k0_block_loop;
    }

    __host__ __device__ static constexpr auto
    MakeCGridDescriptor_MBlock_MXdlPerWave_MWaveMPerXdl_NBlock_NXdlPerWave_NWaveNPerXdl(
        const CGridDesc_M_N& c_grid_desc_m_n)
    {
        const auto M = c_grid_desc_m_n.GetLength(I0);
        const auto N = c_grid_desc_m_n.GetLength(I1);

        const auto MBlock = M / MPerBlock;
        const auto NBlock = N / NPerBlock;

        constexpr index_t MWave = MPerBlock / (MXdlPerWave * MPerXdl);
        constexpr index_t NWave = NPerBlock / (NXdlPerWave * NPerXdl);

        const auto c_grid_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl =
            transform_tensor_descriptor(
                c_grid_desc_m_n,
                make_tuple(make_unmerge_transform(make_tuple(
                               MBlock, Number<MXdlPerWave>{}, Number<MWave * MPerXdl>{})),
                           make_unmerge_transform(make_tuple(
                               NBlock, Number<NXdlPerWave>{}, Number<NWave * NPerXdl>{}))),
                make_tuple(Sequence<0>{}, Sequence<1>{}),
                make_tuple(Sequence<0, 1, 2>{}, Sequence<3, 4, 5>{}));

        return c_grid_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl;
    }

    // return block_id to C matrix tile idx (m0, n0) mapping
    __host__ __device__ static constexpr auto
    MakeDefaultBlock2CTileMap(const CGridDesc_M_N& c_grid_desc_m_n, index_t M01, index_t N01)
    {
        const auto M = c_grid_desc_m_n.GetLength(I0);
        const auto N = c_grid_desc_m_n.GetLength(I1);

        constexpr auto M1 = Number<MPerBlock>{};
        constexpr auto N1 = Number<NPerBlock>{};

        const auto M0 = M / M1;
        const auto N0 = N / N1;

        const auto M00 = M0 / M01;
        const auto N00 = N0 / N01;

        const auto m00_m01_n00_n01_to_m0_n0_block_cluster_adaptor =
            make_single_stage_tensor_adaptor(
                make_tuple(make_unmerge_transform(make_tuple(M00, M01)),
                           make_unmerge_transform(make_tuple(N00, N01))),
                make_tuple(Sequence<0>{}, Sequence<1>{}),
                make_tuple(Sequence<0, 2>{}, Sequence<1, 3>{}));

        const auto cblockid_to_m00_m01_n00_n01_block_cluster_adaptor =
            make_single_stage_tensor_adaptor(
                make_tuple(make_merge_transform(make_tuple(M00, N00, M01, N01))),
                make_tuple(Sequence<0, 1, 2, 3>{}),
                make_tuple(Sequence<0>{}));

        const auto cblockid_to_m0_n0_block_cluster_adaptor =
            chain_tensor_adaptors(m00_m01_n00_n01_to_m0_n0_block_cluster_adaptor,
                                  cblockid_to_m00_m01_n00_n01_block_cluster_adaptor);

        return cblockid_to_m0_n0_block_cluster_adaptor;
    }
    using CGridDescriptor_MBlock_MXdlPerWave_MWaveMPerXdl_NBlock_NXdlPerWave_NWaveNPerXdl =
        remove_cvref_t<decltype(
            MakeCGridDescriptor_MBlock_MXdlPerWave_MWaveMPerXdl_NBlock_NXdlPerWave_NWaveNPerXdl(
                CGridDesc_M_N{}))>;

    using DefaultBlock2CTileMap =
        remove_cvref_t<decltype(MakeDefaultBlock2CTileMap(CGridDesc_M_N{}, 1, 1))>;

    template <bool HasMainK0BlockLoop, typename Block2CTileMap = DefaultBlock2CTileMap>
    __device__ static void
    Run(const FloatAB* __restrict__ p_a_grid,
        const FloatAB* __restrict__ p_b_grid,
        FloatC* __restrict__ p_c_grid,
        void* __restrict__ p_shared,
        const AGridDesc_AK0_M_AK1& a_grid_desc_ak0_m_ak1,
        const BGridDesc_BK0_N_BK1& b_grid_desc_bk0_n_bk1,
        const CGridDescriptor_MBlock_MXdlPerWave_MWaveMPerXdl_NBlock_NXdlPerWave_NWaveNPerXdl&
            c_grid_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl,
        const AElementwiseOperation& a_element_op,
        const BElementwiseOperation& b_element_op,
        const CElementwiseOperation& c_element_op,
        const Block2CTileMap& block_2_ctile_map)
    {
        const auto a_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
            p_a_grid, a_grid_desc_ak0_m_ak1.GetElementSpaceSize());
        const auto b_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
            p_b_grid, b_grid_desc_bk0_n_bk1.GetElementSpaceSize());
        auto c_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
            p_c_grid,
            c_grid_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl
                .GetElementSpaceSize());

        // divide block work by [M, N]
        const auto block_work_idx =
            block_2_ctile_map.CalculateBottomIndex(make_multi_index(get_block_1d_id()));

        // HACK: this force m/n_block_data_idx_on_grid into SGPR
        const index_t m_block_data_idx_on_grid =
            __builtin_amdgcn_readfirstlane(block_work_idx[I0] * MPerBlock);

        const index_t n_block_data_idx_on_grid =
            __builtin_amdgcn_readfirstlane(block_work_idx[I1] * NPerBlock);

        // lds max alignment
        constexpr auto max_lds_align = math::lcm(AK1, BK1);

        // A matrix in LDS memory, dst of blockwise copy
        constexpr auto a_block_desc_ak0_m_ak1 = GetABlockDescriptor_AK0PerBlock_MPerBlock_AK1();

        // B matrix in LDS memory, dst of blockwise copy
        constexpr auto b_block_desc_bk0_n_bk1 = GetBBlockDescriptor_BK0PerBlock_NPerBlock_BK1();

        // A matrix blockwise copy
        auto a_blockwise_copy =
            BlockwiseTensorSliceTransfer_v4r1<BlockSize,
                                              AElementwiseOperation,
                                              ck::tensor_operation::element_wise::PassThrough,
                                              InMemoryDataOperationEnum::Set,
                                              Sequence<AK0, MPerBlock, AK1>,
                                              ABlockTransferThreadClusterLengths_AK0_M_AK1,
                                              ABlockTransferThreadClusterArrangeOrder,
                                              FloatAB,
                                              FloatAB,
                                              decltype(a_grid_desc_ak0_m_ak1),
                                              decltype(a_block_desc_ak0_m_ak1),
                                              ABlockTransferSrcAccessOrder,
                                              Sequence<1, 0, 2>,
                                              ABlockTransferSrcVectorDim,
                                              2,
                                              ABlockTransferSrcScalarPerVector,
                                              ABlockTransferDstScalarPerVector_K1,
                                              1,
                                              1,
                                              AThreadTransferSrcResetCoordinateAfterRun,
                                              true,
                                              NumPrefetch>(
                a_grid_desc_ak0_m_ak1,
                make_multi_index(0, m_block_data_idx_on_grid, 0),
                a_element_op,
                a_block_desc_ak0_m_ak1,
                make_multi_index(0, 0, 0),
                ck::tensor_operation::element_wise::PassThrough{});

        // B matrix blockwise copy
        auto b_blockwise_copy =
            BlockwiseTensorSliceTransfer_v4r1<BlockSize,
                                              BElementwiseOperation,
                                              ck::tensor_operation::element_wise::PassThrough,
                                              InMemoryDataOperationEnum::Set,
                                              Sequence<BK0, NPerBlock, BK1>,
                                              BBlockTransferThreadClusterLengths_BK0_N_BK1,
                                              BBlockTransferThreadClusterArrangeOrder,
                                              FloatAB,
                                              FloatAB,
                                              decltype(b_grid_desc_bk0_n_bk1),
                                              decltype(b_block_desc_bk0_n_bk1),
                                              BBlockTransferSrcAccessOrder,
                                              Sequence<1, 0, 2>,
                                              BBlockTransferSrcVectorDim,
                                              2,
                                              BBlockTransferSrcScalarPerVector,
                                              BBlockTransferDstScalarPerVector_K1,
                                              1,
                                              1,
                                              BThreadTransferSrcResetCoordinateAfterRun,
                                              true,
                                              NumPrefetch>(
                b_grid_desc_bk0_n_bk1,
                make_multi_index(0, n_block_data_idx_on_grid, 0),
                b_element_op,
                b_block_desc_bk0_n_bk1,
                make_multi_index(0, 0, 0),
                ck::tensor_operation::element_wise::PassThrough{});

        // GEMM definition
        //   c_mtx += transpose(a_mtx) * b_mtx
        //     a_mtx[K0PerBlock, MPerBlock] is in LDS
        //     b_mtx[K0PerBlock, NPerBlock] is in LDS
        //     c_mtx[MPerBlock, NPerBlock] is distributed among threads, and saved in
        //       register
        // sanity check
        constexpr index_t k_pack = math::max(
            math::lcm(AK1, BK1), MfmaSelector<FloatAB, MPerXdl, NPerXdl>::selected_mfma.k_per_blk);

        auto blockwise_gemm =
            BlockwiseGemmXdlops_k0mk1_k0nk1_m0n0m1n1m2m3m4n2_v1<BlockSize,
                                                                FloatAB,
                                                                FloatAcc,
                                                                decltype(a_block_desc_ak0_m_ak1),
                                                                decltype(b_block_desc_bk0_n_bk1),
                                                                MPerXdl,
                                                                NPerXdl,
                                                                MXdlPerWave,
                                                                NXdlPerWave,
                                                                k_pack>{};

        auto c_thread_buf = blockwise_gemm.GetCThreadBuffer();

        // LDS allocation for A and B: be careful of alignment
        constexpr auto a_block_space_size_aligned = math::integer_least_multiple(
            a_block_desc_ak0_m_ak1.GetElementSpaceSize(), max_lds_align);

        auto a_block_buf = make_dynamic_buffer<AddressSpaceEnum::Lds>(
            static_cast<FloatAB*>(p_shared), a_block_desc_ak0_m_ak1.GetElementSpaceSize());

        auto b_block_buf = make_dynamic_buffer<AddressSpaceEnum::Lds>(
            static_cast<FloatAB*>(p_shared) + a_block_space_size_aligned,
            b_block_desc_bk0_n_bk1.GetElementSpaceSize());

        constexpr auto a_block_slice_copy_step = make_multi_index(KPerBlock / AK1, 0, 0);
        constexpr auto b_block_slice_copy_step = make_multi_index(KPerBlock / BK1, 0, 0);

        // gridwise GEMM pipeline
        const auto gridwise_gemm_pipeline =
            GridwiseGemmPipeline_v1<remove_cvref_t<decltype(a_grid_desc_ak0_m_ak1)>,
                                    remove_cvref_t<decltype(a_block_desc_ak0_m_ak1)>,
                                    remove_cvref_t<decltype(a_blockwise_copy)>,
                                    remove_cvref_t<decltype(a_grid_buf)>,
                                    remove_cvref_t<decltype(a_block_buf)>,
                                    remove_cvref_t<decltype(a_block_slice_copy_step)>,
                                    remove_cvref_t<decltype(b_grid_desc_bk0_n_bk1)>,
                                    remove_cvref_t<decltype(b_block_desc_bk0_n_bk1)>,
                                    remove_cvref_t<decltype(b_blockwise_copy)>,
                                    remove_cvref_t<decltype(b_grid_buf)>,
                                    remove_cvref_t<decltype(b_block_buf)>,
                                    remove_cvref_t<decltype(b_block_slice_copy_step)>,
                                    remove_cvref_t<decltype(blockwise_gemm)>,
                                    remove_cvref_t<decltype(c_thread_buf)>,
                                    NumPrefetch,
                                    HasMainK0BlockLoop>{};

        const index_t num_k_block_main_loop = __builtin_amdgcn_readfirstlane(
            (a_grid_desc_ak0_m_ak1.GetLength(I0) * a_grid_desc_ak0_m_ak1.GetLength(I2)) /
            KPerBlock);

        gridwise_gemm_pipeline.Run(a_grid_desc_ak0_m_ak1,
                                   a_block_desc_ak0_m_ak1,
                                   a_blockwise_copy,
                                   a_grid_buf,
                                   a_block_buf,
                                   a_block_slice_copy_step,
                                   b_grid_desc_bk0_n_bk1,
                                   b_block_desc_bk0_n_bk1,
                                   b_blockwise_copy,
                                   b_grid_buf,
                                   b_block_buf,
                                   b_block_slice_copy_step,
                                   blockwise_gemm,
                                   c_thread_buf,
                                   num_k_block_main_loop);

        // shuffle C and write out
        {
            static_assert(MXdlPerWave % CShuffleMXdlPerWavePerShuffle == 0 &&
                              NXdlPerWave % CShuffleNXdlPerWavePerShuffle == 0,
                          "wrong!");

            constexpr index_t MWave = MPerBlock / (MXdlPerWave * MPerXdl);
            constexpr index_t NWave = NPerBlock / (NXdlPerWave * NPerXdl);

            // TODO: hacky, fix it!
            constexpr auto c_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2 =
                blockwise_gemm.GetCThreadDescriptor_M0_N0_M1_N1_M2_M3_M4_N2();

            // TODO: hacky, fix it!
            // c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp is only used to get lengths
            constexpr auto c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp =
                blockwise_gemm.GetCBlockDescriptor_M0_N0_M1_N1_M2_M3_M4_N2();

            constexpr auto M0 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I0);
            constexpr auto N0 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I1);
            constexpr auto M1 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I2);
            constexpr auto N1 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I3);
            constexpr auto M2 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I4);
            constexpr auto M3 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I5);
            constexpr auto M4 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I6);
            constexpr auto N2 = c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2_tmp.GetLength(I7);

            constexpr auto c_block_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl =
                GetCBlockDescriptor_MBlock_NXdlPerWave_MWaveMPerXdl_NBlock_NXdlPerWave_NWaveNPerXdl();

            auto c_shuffle_block_buf = make_dynamic_buffer<AddressSpaceEnum::Lds>(
                static_cast<FloatCShuffle*>(p_shared),
                c_block_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl
                    .GetElementSpaceSize());

            constexpr auto c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2 = transform_tensor_descriptor(
                c_block_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl,
                make_tuple(
                    make_freeze_transform(I0), // freeze mblock
                    make_pass_through_transform(
                        Number<CShuffleMXdlPerWavePerShuffle>{}), // M0 (MXdlPerWave) per shuffle
                    make_unmerge_transform(
                        make_tuple(M1, M2, M3, M4)), // M1 = MWave, M2 * M3 * M4 = MPerXdl
                    make_freeze_transform(I0),       // freeze nblock
                    make_pass_through_transform(
                        Number<CShuffleNXdlPerWavePerShuffle>{}), // N0 (NXdlPerWave) per shuffle
                    make_unmerge_transform(
                        make_tuple(N1, N2))), // M1 = MWave, M2 * M3 * M4 = MPerXdl
                make_tuple(Sequence<0>{},
                           Sequence<1>{},
                           Sequence<2>{},
                           Sequence<3>{},
                           Sequence<4>{},
                           Sequence<5>{}),
                make_tuple(Sequence<>{},
                           Sequence<0>{},
                           Sequence<2, 4, 5, 6>{},
                           Sequence<>{},
                           Sequence<1>{},
                           Sequence<3, 7>{}));

            // calculate origin of thread output tensor on global memory
            //     blockwise GEMM c matrix starting index
            const auto c_thread_mtx_on_block =
                blockwise_gemm.CalculateCThreadOriginDataIndex(I0, I0, I0, I0);

            const index_t m_thread_data_on_block = c_thread_mtx_on_block[I0];
            const index_t n_thread_data_on_block = c_thread_mtx_on_block[I1];

            const auto m_thread_data_on_block_to_m0_m1_m2_m3_m4_adaptor =
                make_single_stage_tensor_adaptor(
                    make_tuple(make_merge_transform(make_tuple(M0, M1, M2, M3, M4))),
                    make_tuple(Sequence<0, 1, 2, 3, 4>{}),
                    make_tuple(Sequence<0>{}));

            const auto m_thread_data_on_block_idx =
                m_thread_data_on_block_to_m0_m1_m2_m3_m4_adaptor.CalculateBottomIndex(
                    make_multi_index(m_thread_data_on_block));

            const auto n_thread_data_on_block_to_n0_n1_n2_adaptor =
                make_single_stage_tensor_adaptor(
                    make_tuple(make_merge_transform(make_tuple(N0, N1, N2))),
                    make_tuple(Sequence<0, 1, 2>{}),
                    make_tuple(Sequence<0>{}));

            const auto n_thread_data_on_block_idx =
                n_thread_data_on_block_to_n0_n1_n2_adaptor.CalculateBottomIndex(
                    make_multi_index(n_thread_data_on_block));

            // VGPR to LDS
            auto c_thread_copy_vgpr_to_lds =
                ThreadwiseTensorSliceTransfer_v1r3<FloatAcc,
                                                   FloatCShuffle,
                                                   decltype(c_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2),
                                                   decltype(c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2),
                                                   ck::tensor_operation::element_wise::PassThrough,
                                                   Sequence<CShuffleMXdlPerWavePerShuffle,
                                                            CShuffleNXdlPerWavePerShuffle,
                                                            I1,
                                                            I1,
                                                            M2,
                                                            I1,
                                                            M4,
                                                            I1>,
                                                   Sequence<0, 1, 2, 3, 4, 5, 6, 7>,
                                                   7,
                                                   1,
                                                   InMemoryDataOperationEnum::Set,
                                                   1,
                                                   true>{
                    c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2,
                    make_multi_index(0,
                                     0,
                                     m_thread_data_on_block_idx[I1],
                                     n_thread_data_on_block_idx[I1],
                                     m_thread_data_on_block_idx[I2],
                                     m_thread_data_on_block_idx[I3],
                                     m_thread_data_on_block_idx[I4],
                                     n_thread_data_on_block_idx[I2]),
                    ck::tensor_operation::element_wise::PassThrough{}};

            // LDS to global
            auto c_block_copy_lds_to_global = BlockwiseTensorSliceTransfer_v6r1<
                BlockSize,                  // index_t BlockSize,
                CElementwiseOperation,      // ElementwiseOperation,
                CGlobalMemoryDataOperation, // DstInMemOp,
                Sequence<1,
                         CShuffleMXdlPerWavePerShuffle,
                         MWave * MPerXdl,
                         1,
                         CShuffleNXdlPerWavePerShuffle,
                         NWave * NPerXdl>, // BlockSliceLengths,
                CBlockTransferClusterLengths_MBlock_MXdlPerWave_MWaveMPerXdl_NBlock_NXdlPerWave_NWaveNPerXdl,
                Sequence<0, 1, 2, 3, 4, 5>, // typename ThreadClusterArrangeOrder,
                FloatCShuffle,              // typename SrcData,
                FloatC,                     // typename DstData,
                decltype(
                    c_block_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl),
                decltype(
                    c_grid_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl),
                Sequence<0, 1, 2, 3, 4, 5>,                 // typename DimAccessOrder,
                5,                                          // index_t VectorDim,
                CBlockTransferScalarPerVector_NWaveNPerXdl, // index_t ScalarPerVector,
                true,  // bool ThreadTransferSrcResetCoordinateAfterRun,
                false> // bool ThreadTransferDstResetCoordinateAfterRun>
                {c_block_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl,
                 make_multi_index(0, 0, 0, 0, 0, 0),
                 c_grid_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl,
                 make_multi_index(block_work_idx[I0], 0, 0, block_work_idx[I1], 0, 0),
                 c_element_op};

            constexpr auto mxdlperwave_forward_step =
                make_multi_index(0, CShuffleMXdlPerWavePerShuffle, 0, 0, 0, 0);
            constexpr auto nxdlperwave_forward_step =
                make_multi_index(0, 0, 0, 0, CShuffleNXdlPerWavePerShuffle, 0);
            constexpr auto nxdlperwave_backward_step =
                make_multi_index(0, 0, 0, 0, -CShuffleNXdlPerWavePerShuffle, 0);

            static_for<0, MXdlPerWave, CShuffleMXdlPerWavePerShuffle>{}([&](auto mxdlperwave_iter) {
                constexpr auto mxdlperwave = mxdlperwave_iter;

                static_for<0,
                           NXdlPerWave,
                           CShuffleNXdlPerWavePerShuffle>{}([&](auto nxdlperwave_iter) {
                    constexpr bool nxdlperwave_forward_sweep =
                        (mxdlperwave % (2 * CShuffleMXdlPerWavePerShuffle) == 0);

                    constexpr index_t nxdlperwave_value =
                        nxdlperwave_forward_sweep
                            ? nxdlperwave_iter
                            : (NXdlPerWave - nxdlperwave_iter - CShuffleNXdlPerWavePerShuffle);

                    constexpr auto nxdlperwave = Number<nxdlperwave_value>{};

                    // make sure it's safe to do ds_write
                    block_sync_lds();

                    // VGPR to LDS
                    c_thread_copy_vgpr_to_lds.Run(
                        c_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2,
                        make_tuple(mxdlperwave, nxdlperwave, I0, I0, I0, I0, I0, I0),
                        c_thread_buf,
                        c_block_desc_m0_n0_m1_n1_m2_m3_m4_n2,
                        c_shuffle_block_buf);

                    // make sure it's safe to do ds_read
                    block_sync_lds();

                    // LDS to global
                    c_block_copy_lds_to_global.Run(
                        c_block_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl,
                        c_shuffle_block_buf,
                        c_grid_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl,
                        c_grid_buf);

                    // move on nxdlperwave dimension
                    if constexpr(nxdlperwave_forward_sweep &&
                                 (nxdlperwave < NXdlPerWave - CShuffleNXdlPerWavePerShuffle))
                    {
                        c_block_copy_lds_to_global.MoveDstSliceWindow(
                            c_grid_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl,
                            nxdlperwave_forward_step);
                    }
                    else if constexpr((!nxdlperwave_forward_sweep) && (nxdlperwave > 0))
                    {
                        c_block_copy_lds_to_global.MoveDstSliceWindow(
                            c_grid_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl,
                            nxdlperwave_backward_step);
                    }
                });

                // move on mxdlperwave dimension
                if constexpr(mxdlperwave < MXdlPerWave - CShuffleMXdlPerWavePerShuffle)
                {
                    c_block_copy_lds_to_global.MoveDstSliceWindow(
                        c_grid_desc_mblock_mxdlperwave_mwavemperxdl_nblock_nxdlperwave_nwavenperxdl,
                        mxdlperwave_forward_step);
                }
            });
        }
    }
};

} // namespace ck
#endif
