prototype2 qloop bottom-up cycle

include/ck/tensor_operation/gpu/grid/gridwise_batched_multihead_attention_backward_xdl_cshuffle_pt7.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include "ck/utility/common_header.hpp"
+#include "ck/utility/philox_rand.hpp"
+#include "ck/tensor_description/multi_index_transform_helper.hpp"
+#include "ck/tensor_description/tensor_descriptor.hpp"
+#include "ck/tensor_description/tensor_descriptor_helper.hpp"
+#include "ck/tensor_operation/gpu/grid/block_to_ctile_map.hpp"
+#include "ck/tensor_operation/gpu/grid/gridwise_gemm_pipeline_selector.hpp"
+#include "ck/tensor_operation/gpu/block/blockwise_gemm_xdlops.hpp"
+#include "ck/tensor_operation/gpu/block/thread_group_tensor_slice_transfer_v4r1.hpp"
+#include "ck/tensor_operation/gpu/block/thread_group_tensor_slice_transfer_v6r1.hpp"
+#include "ck/tensor_operation/gpu/thread/threadwise_tensor_slice_transfer.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/tensor_operation/gpu/block/blockwise_softmax.hpp"
+#include "ck/tensor_operation/gpu/block/blockwise_dropout.hpp"
+
+namespace ck {
+
+template <typename InputDataType,
+          typename OutputDataType,
+          typename ZDataType,
+          typename GemmDataType,
+          typename FloatGemmAcc,
+          typename FloatCShuffle,
+          typename FloatLSE,
+          typename AElementwiseOperation,
+          typename BElementwiseOperation,
+          typename SElementwiseOperation,
+          typename B1ElementwiseOperation,
+          typename CElementwiseOperation,
+          InMemoryDataOperationEnum CGlobalMemoryDataOperation,
+          typename QGridDesc_K0_M_K1,
+          typename KGridDesc_K0_N_K1,
+          typename KGridDesc_N_K,
+          typename ZGridDesc_M_N,
+          typename VGridDesc_N0_O_N1,
+          typename YGridDesc_M_O,
+          typename LSEGridDesc_M,
+          index_t NumGemmKPrefetchStage,
+          index_t BlockSize,
+          index_t MPerBlock,
+          index_t NPerBlock,
+          index_t KPerBlock,
+          index_t Gemm1NPerBlock,
+          index_t Gemm1KPerBlock,
+          index_t AK1Value,
+          index_t BK1Value,
+          index_t B1K1Value,
+          index_t MPerXdl,
+          index_t NPerXdl,
+          index_t MXdlPerWave,
+          index_t NXdlPerWave,
+          index_t Gemm1NXdlPerWave,
+          index_t Gemm2NXdlPerWave,
+          typename ABlockTransferThreadClusterLengths_AK0_M_AK1,
+          typename ABlockTransferThreadClusterArrangeOrder,
+          typename ABlockTransferSrcAccessOrder,
+          index_t ABlockTransferSrcVectorDim,
+          index_t ABlockTransferSrcScalarPerVector,
+          index_t ABlockTransferDstScalarPerVector_AK1,
+          bool AThreadTransferSrcResetCoordinateAfterRun, // ignored
+          index_t ABlockLdsExtraM,
+          typename BBlockTransferThreadClusterLengths_BK0_N_BK1,
+          typename BBlockTransferThreadClusterArrangeOrder,
+          typename BBlockTransferSrcAccessOrder,
+          index_t BBlockTransferSrcVectorDim,
+          index_t BBlockTransferSrcScalarPerVector,
+          index_t BBlockTransferDstScalarPerVector_BK1,
+          bool BThreadTransferSrcResetCoordinateAfterRun, // ignored
+          index_t BBlockLdsExtraN,
+          typename B1BlockTransferThreadClusterLengths_BK0_N_BK1,
+          typename B1BlockTransferThreadClusterArrangeOrder,
+          typename B1BlockTransferSrcAccessOrder,
+          index_t B1BlockTransferSrcVectorDim,
+          index_t B1BlockTransferSrcScalarPerVector,
+          index_t B1BlockTransferDstScalarPerVector_BK1,
+          bool B1ThreadTransferSrcResetCoordinateAfterRun,
+          index_t B1BlockLdsExtraN,
+          index_t CShuffleMXdlPerWavePerShuffle,
+          index_t CShuffleNXdlPerWavePerShuffle,
+          typename CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
+          index_t CShuffleBlockTransferScalarPerVector_NPerBlock,
+          LoopScheduler LoopSched,
+          bool PadN,
+          bool MaskOutUpperTriangle,
+          bool Deterministic,
+          PipelineVersion PipelineVer = PipelineVersion::v1>
+struct GridwiseBatchedMultiheadAttentionBackward_Xdl_CShuffle_V2
+{
+    static_assert(LoopSched == LoopScheduler::Default,
+                  "Non-default loop scheduler is currently not supported");
+
+    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>{};
+    static constexpr auto I8 = Number<8>{};
+    static constexpr auto I9 = Number<9>{};
+
+    static constexpr auto WaveSize = 64;
+    // K1 should be Number<...>
+    // Gemm0
+    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>{};
+
+    static constexpr auto Gemm0MWaves = MPerBlock / (MPerXdl * MXdlPerWave);
+    static constexpr auto Gemm0NWaves = NPerBlock / (NPerXdl * NXdlPerWave);
+
+    // Gemm1
+    static constexpr auto B1K0 = Number<Gemm1KPerBlock / B1K1Value>{};
+    static constexpr auto B1K1 = Number<B1K1Value>{};
+
+    using ThisThreadBlock = ThisThreadBlock<BlockSize>;
+
+    using GridwiseGemmPipe = remove_cvref_t<decltype(
+        GridwiseGemmPipeline_Selector<PipelineVer, NumGemmKPrefetchStage>())>;
+
+    // C desc for source in blockwise copy
+    __host__ __device__ static constexpr auto
+    MakeCGridDescriptor_M0_N0_M1_N1_M2_N2_M3_N3_N4_N5(const ZGridDesc_M_N& z_grid_desc_m_n)
+    {
+        const auto M = z_grid_desc_m_n.GetLength(I0);
+        const auto N = z_grid_desc_m_n.GetLength(I1);
+
+        constexpr auto mfma = MfmaSelector<GemmDataType, MPerXdl, NPerXdl>::selected_mfma;
+        constexpr auto N3   = mfma.num_groups_per_blk;
+        constexpr auto N4   = mfma.num_input_blks;
+        constexpr auto N5   = mfma.group_size;
+        return transform_tensor_descriptor(
+            z_grid_desc_m_n,
+            make_tuple(make_unmerge_transform(
+                           make_tuple(M / MPerBlock, MXdlPerWave, Gemm0MWaves, MPerXdl)),
+                       make_unmerge_transform(
+                           make_tuple(N / NPerBlock, NXdlPerWave, Gemm0NWaves, N3, N4, N5))),
+            make_tuple(Sequence<0>{}, Sequence<1>{}),
+            make_tuple(Sequence<0, 2, 4, 6>{}, Sequence<1, 3, 5, 7, 8, 9>{}));
+    }
+    __host__ __device__ static constexpr auto
+    MakeZGridDescriptor_M0_N0_M1_N1_M2_N2_M3_N3_N4_N5(const index_t M, const index_t N)
+    {
+        constexpr auto mfma = MfmaSelector<GemmDataType, MPerXdl, NPerXdl>::selected_mfma;
+        constexpr auto N3   = mfma.num_groups_per_blk;
+        constexpr auto N4   = mfma.num_input_blks;
+        constexpr auto N5   = mfma.group_size;
+        return transform_tensor_descriptor(
+            make_naive_tensor_descriptor_packed(make_tuple(M, N)),
+            make_tuple(make_unmerge_transform(
+                           make_tuple(M / MPerBlock, MXdlPerWave, Gemm0MWaves, MPerXdl)),
+                       make_unmerge_transform(
+                           make_tuple(N / NPerBlock, NXdlPerWave, Gemm0NWaves, N3, N4, N5))),
+            make_tuple(Sequence<0>{}, Sequence<1>{}),
+            make_tuple(Sequence<0, 2, 4, 6>{}, Sequence<1, 3, 5, 7, 8, 9>{}));
+    }
+
+    __device__ static auto GetGemm0WaveIdx()
+    {
+        const index_t thread_id = get_thread_local_1d_id();
+
+        constexpr auto threadid_to_wave_idx_adaptor = make_single_stage_tensor_adaptor(
+            make_tuple(make_merge_transform(make_tuple(Gemm0MWaves, Gemm0NWaves, WaveSize))),
+            make_tuple(Sequence<0, 1, 2>{}),
+            make_tuple(Sequence<0>{}));
+
+        return threadid_to_wave_idx_adaptor.CalculateBottomIndex(make_multi_index(thread_id));
+    }
+
+    __device__ static auto GetGemm0WaveMNIdx(const index_t thread_id)
+    {
+        constexpr auto wave_threadid_to_mn_idx_adaptor = make_single_stage_tensor_adaptor(
+            make_tuple(make_merge_transform(make_tuple(WaveSize / MPerXdl, MPerXdl))),
+            make_tuple(Sequence<0, 1>{}),
+            make_tuple(Sequence<0>{}));
+
+        return wave_threadid_to_mn_idx_adaptor.CalculateBottomIndex(make_multi_index(thread_id));
+    }
+
+    __host__ __device__ static constexpr auto GetABlockDescriptor_AK0PerBlock_MPerBlock_AK1()
+    {
+        // A matrix in LDS memory, dst of blockwise copy
+        return make_naive_tensor_descriptor(
+            make_tuple(AK0, Number<MPerBlock>{}, AK1),
+            make_tuple(Number<MPerBlock + ABlockLdsExtraM>{} * AK1, AK1, I1));
+    }
+
+    __host__ __device__ static constexpr auto GetBBlockDescriptor_BK0PerBlock_NPerBlock_BK1()
+    {
+        // B matrix in LDS memory, dst of blockwise copy
+        return make_naive_tensor_descriptor(
+            make_tuple(BK0, Number<NPerBlock>{}, BK1),
+            make_tuple(Number<NPerBlock + BBlockLdsExtraN>{} * BK1, BK1, I1));
+    }
+
+    template <typename AccThreadDesc_M0_N0_M1_N1_M2_M3_M4_N2>
+    __host__ __device__ static constexpr auto GetA1SrcThreadDescriptor_AK0PerBlock_MPerBlock_AK1(
+        const AccThreadDesc_M0_N0_M1_N1_M2_M3_M4_N2& acc_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2)
+    {
+        // acc_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2 to a_src_thread_desc_k0_m_k1
+        // m0_m1_m2_m3 -> k0
+        // n0_n1_n2 -> m
+        // m4 -> k1
+        // NOTE: had to use merge_v3 or will spit out compilation errors
+        const auto m0 = acc_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I0);
+        const auto n0 = acc_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I1);
+        const auto m1 = acc_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I2);
+        const auto n1 = acc_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I3);
+        const auto m2 = acc_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I4);
+        const auto m3 = acc_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I5);
+        const auto m4 = acc_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I6);
+        const auto n2 = acc_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I7);
+
+        return transform_tensor_descriptor(
+            acc_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2,
+            make_tuple(make_merge_transform_v3_division_mod(make_tuple(m0, m1, m2, m3)),
+                       make_merge_transform_v3_division_mod(make_tuple(n0, n1, n2)),
+                       make_pass_through_transform(m4)),
+            make_tuple(Sequence<0, 2, 4, 5>{}, Sequence<1, 3, 7>{}, Sequence<6>{}),
+            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}));
+    }
+
+    __host__ __device__ static constexpr auto GetB1BlockDescriptor_BK0PerBlock_NPerBlock_BK1()
+    {
+        // B1 matrix in LDS memory, dst of blockwise copy
+        return make_naive_tensor_descriptor(
+            make_tuple(B1K0, Number<Gemm1NPerBlock>{}, B1K1),
+            make_tuple(Number<Gemm1NPerBlock + B1BlockLdsExtraN>{} * B1K1, B1K1, I1));
+    }
+
+    __host__ __device__ static constexpr auto
+    GetCShuffleBlockDescriptor_MBlock_MPerBlock_NBlock_NPerBlock()
+    {
+        constexpr index_t MWave = Gemm0NWaves;
+        constexpr index_t NWave = Gemm0MWaves;
+
+        constexpr auto c_shuffle_block_desc_mblock_mperblock_nblock_nperblock =
+            make_naive_tensor_descriptor_packed(
+                make_tuple(I1,
+                           Number<CShuffleMXdlPerWavePerShuffle * MWave * MPerXdl>{},
+                           I1,
+                           Number<CShuffleNXdlPerWavePerShuffle * NWave * NPerXdl>{}));
+
+        return c_shuffle_block_desc_mblock_mperblock_nblock_nperblock;
+    }
+
+    template <typename Gemm2Param>
+    __host__ __device__ static constexpr auto GetA2BlockDescriptor_K0_M_K1()
+    {
+        return make_naive_tensor_descriptor(
+            make_tuple(Number<Gemm2Param::A_K0>{},
+                       Number<Gemm2Param::Gemm2_M>{},
+                       Number<Gemm2Param::A_K1>{}),
+            make_tuple(Number<Gemm2Param::Gemm2_M + Gemm2Param::A_LdsPad>{} *
+                           Number<Gemm2Param::A_K1>{},
+                       Number<Gemm2Param::A_K1>{},
+                       I1));
+    }
+
+    template <typename Gemm2Param>
+    __host__ __device__ static constexpr auto GetB2BlockDescriptor_K0_N_K1()
+    {
+        return make_naive_tensor_descriptor(
+            make_tuple(Number<Gemm2Param::B_K0>{},
+                       Number<Gemm2Param::Gemm2_N>{},
+                       Number<Gemm2Param::B_K1>{}),
+            make_tuple(Number<Gemm2Param::Gemm2_N + Gemm2Param::B_LdsPad>{} *
+                           Number<Gemm2Param::B_K1>{},
+                       Number<Gemm2Param::B_K1>{},
+                       I1));
+    }
+
+    __host__ __device__ static constexpr bool
+    CheckValidity(const QGridDesc_K0_M_K1& q_grid_desc_k0_m_k1,
+                  const KGridDesc_K0_N_K1& k_grid_desc_k0_n_k1,
+                  const VGridDesc_N0_O_N1& v_grid_desc_n0_o_n1,
+                  const YGridDesc_M_O& y_grid_desc_m_o)
+    {
+        static_assert((MPerBlock % (MPerXdl * MXdlPerWave) == 0) &&
+                          (NPerBlock % (NXdlPerWave * NPerXdl)) == 0,
+                      "Invalid tuning param!");
+
+        const auto M      = q_grid_desc_k0_m_k1.GetLength(I1);
+        const auto N      = k_grid_desc_k0_n_k1.GetLength(I1);
+        const auto K      = q_grid_desc_k0_m_k1.GetLength(I0) * q_grid_desc_k0_m_k1.GetLength(I2);
+        const auto Gemm1N = v_grid_desc_n0_o_n1.GetLength(I1);
+
+        // This assumption reduces implemention complexity by categorizing 6 separate GEMMs into 3
+        // types of GEMM operations, therefore some code body can be reused accordingly
+        // P_MNK / dP_MNO Gemm (Gemm0 rcr)
+        // Y_MON / dQ_MKN Gemm (Gemm1 rrr)
+        // dV_NOM / dK_NKM Gemm (Gemm2 crr)
+        if(Gemm1N != K)
+        {
+            std::cerr << "SizeK must be equal to SizeO (equal attention head size)" << '\n';
+            return false;
+        }
+
+        if(!(M == y_grid_desc_m_o.GetLength(I0) && Gemm1N == y_grid_desc_m_o.GetLength(I1)))
+        {
+            return false;
+        }
+
+        if(!(M % MPerBlock == 0 && N % NPerBlock == 0 && K % KPerBlock == 0 &&
+             Gemm1N % Gemm1NPerBlock == 0))
+        {
+            return false;
+        }
+
+        // check gemm0 gridwise gemm pipeline
+        const auto num_gemm0_k_loop = K / KPerBlock;
+        if(!GridwiseGemmPipe::IsSupported(num_gemm0_k_loop))
+        {
+            return false;
+        }
+
+        // check gemm1 gridwise gemm pipeline
+        if(!(NPerBlock % Gemm1KPerBlock == 0))
+        {
+            return false;
+        }
+
+        const auto num_gemm1_k_inner_loop = NPerBlock / Gemm1KPerBlock;
+        if(!GridwiseGemmPipe::IsSupported(num_gemm1_k_inner_loop))
+        {
+            return false;
+        }
+
+        // TODO: also check validity of all components (blockwise-copy, threadwise-copy, etc)
+        return true;
+    }
+
+    __host__ __device__ static constexpr bool CalculateHasMainKBlockLoop(index_t K)
+    {
+        const index_t num_loop = K / KPerBlock;
+
+        return GridwiseGemmPipe::CalculateHasMainLoop(num_loop);
+    }
+
+    __host__ __device__ static constexpr auto
+    MakeYGridDescriptor_MBlock_MPerBlock_OBlock_OPerBlock(const YGridDesc_M_O& y_grid_desc_m_o)
+    {
+        const auto M = y_grid_desc_m_o.GetLength(I0);
+        const auto O = y_grid_desc_m_o.GetLength(I1);
+
+        const auto MBlock = M / MPerBlock;
+        const auto OBlock = O / Gemm1NPerBlock;
+
+        const auto y_grid_desc_mblock_mperblock_oblock_operblock = transform_tensor_descriptor(
+            y_grid_desc_m_o,
+            make_tuple(make_unmerge_transform(make_tuple(MBlock, Number<MPerBlock>{})),
+                       make_unmerge_transform(make_tuple(OBlock, Number<Gemm1NPerBlock>{}))),
+            make_tuple(Sequence<0>{}, Sequence<1>{}),
+            make_tuple(Sequence<0, 1>{}, Sequence<2, 3>{}));
+
+        return y_grid_desc_mblock_mperblock_oblock_operblock;
+    }
+
+    template <typename SrcBlockwiseGemm>
+    __host__ __device__ static constexpr auto
+    MakeLSEGridDescriptor_MB_M0_M1_M2_M3_M4(const LSEGridDesc_M& lse_grid_desc_m)
+    {
+        const index_t M      = lse_grid_desc_m.GetLength(I0);
+        const index_t MBlock = M / MPerBlock;
+        constexpr auto SrcBlockDesc_M0_N0_M1_N1_M2_M3_M4_N2 =
+            SrcBlockwiseGemm::GetCBlockDescriptor_M0_N0_M1_N1_M2_M3_M4_N2();
+        // M0 MXdlPerWave, M1 MWave, M2 num_groups_per_blk, M3 num_input_blks, M4 group_size
+        const auto M0 = SrcBlockDesc_M0_N0_M1_N1_M2_M3_M4_N2.GetLength(I0);
+        const auto M1 = SrcBlockDesc_M0_N0_M1_N1_M2_M3_M4_N2.GetLength(I2);
+        const auto M2 = SrcBlockDesc_M0_N0_M1_N1_M2_M3_M4_N2.GetLength(I4);
+        const auto M3 = SrcBlockDesc_M0_N0_M1_N1_M2_M3_M4_N2.GetLength(I5);
+        const auto M4 = SrcBlockDesc_M0_N0_M1_N1_M2_M3_M4_N2.GetLength(I6);
+
+        const auto lse_grid_desc_mb_m0_m1_m2_m3_m4 = transform_tensor_descriptor(
+            lse_grid_desc_m,
+            make_tuple(make_unmerge_transform(make_tuple(MBlock, M0, M1, M2, M3, M4))),
+            make_tuple(Sequence<0>{}),
+            make_tuple(Sequence<0, 1, 2, 3, 4, 5>{}));
+
+        return lse_grid_desc_mb_m0_m1_m2_m3_m4;
+    }
+
+    __device__ static auto MakeKGradGridDesc_NBlock_NPerBlock_OBlock_OPerBlock(
+        const KGridDesc_K0_N_K1& k_grid_desc_k0_n_k1)
+    {
+        const auto O0 = k_grid_desc_k0_n_k1.GetLength(I0);
+        const auto N  = k_grid_desc_k0_n_k1.GetLength(I1);
+        const auto O1 = k_grid_desc_k0_n_k1.GetLength(I2);
+        const auto O  = O0 * O1;
+
+        const auto NBlock = N / NPerBlock;
+        const auto OBlock = O / Gemm1NPerBlock;
+
+        const auto k_grid_desc_n_o = transform_tensor_descriptor(
+            k_grid_desc_k0_n_k1,
+            make_tuple(make_pass_through_transform(N),
+                       make_merge_transform_v3_division_mod(make_tuple(O0, O1))),
+            make_tuple(Sequence<1>{}, Sequence<0, 2>{}),
+            make_tuple(Sequence<0>{}, Sequence<1>{}));
+
+        return transform_tensor_descriptor(
+            k_grid_desc_n_o,
+            make_tuple(make_unmerge_transform(make_tuple(NBlock, Number<NPerBlock>{})),
+                       make_unmerge_transform(make_tuple(OBlock, Number<Gemm1NPerBlock>{}))),
+            make_tuple(Sequence<0>{}, Sequence<1>{}),
+            make_tuple(Sequence<0, 1>{}, Sequence<2, 3>{}));
+    }
+
+    __device__ static auto MakeVGradGridDesc_NBlock_NPerBlock_OBlock_OPerBlock(
+        const VGridDesc_N0_O_N1& v_grid_desc_n0_o_n1)
+    {
+        const auto N0 = v_grid_desc_n0_o_n1.GetLength(I0);
+        const auto O  = v_grid_desc_n0_o_n1.GetLength(I1);
+        const auto N1 = v_grid_desc_n0_o_n1.GetLength(I2);
+        const auto N  = N0 * N1;
+
+        const auto NBlock = N / NPerBlock;
+        const auto OBlock = O / Gemm1NPerBlock;
+
+        const auto v_grid_desc_n_o = transform_tensor_descriptor(
+            v_grid_desc_n0_o_n1,
+            make_tuple(make_pass_through_transform(O),
+                       make_merge_transform_v3_division_mod(make_tuple(N0, N1))),
+            make_tuple(Sequence<1>{}, Sequence<0, 2>{}),
+            make_tuple(Sequence<1>{}, Sequence<0>{}));
+
+        return transform_tensor_descriptor(
+            v_grid_desc_n_o,
+            make_tuple(make_unmerge_transform(make_tuple(NBlock, Number<NPerBlock>{})),
+                       make_unmerge_transform(make_tuple(OBlock, Number<Gemm1NPerBlock>{}))),
+            make_tuple(Sequence<0>{}, Sequence<1>{}),
+            make_tuple(Sequence<0, 1>{}, Sequence<2, 3>{}));
+    }
+
+    __device__ static auto MakeQGradGridDesc_M_K(const QGridDesc_K0_M_K1& q_grid_desc_k0_m_k1)
+    {
+        const auto K_K0 = q_grid_desc_k0_m_k1.GetLength(I0);
+        const auto M    = q_grid_desc_k0_m_k1.GetLength(I1);
+        const auto K_K1 = q_grid_desc_k0_m_k1.GetLength(I2);
+
+        return transform_tensor_descriptor(
+            q_grid_desc_k0_m_k1,
+            make_tuple(make_pass_through_transform(M),
+                       make_merge_transform_v3_division_mod(make_tuple(K_K0, K_K1))),
+            make_tuple(Sequence<1>{}, Sequence<0, 2>{}),
+            make_tuple(Sequence<0>{}, Sequence<1>{}));
+    }
+
+    // return block_id to C matrix tile idx (m0, n0) mapping
+    __host__ __device__ static constexpr auto
+    MakeDefaultBlock2CTileMap(const KGridDesc_N_K& k_grid_desc_n_k)
+    {
+        return BlockToCTileMap_M00_N0_M01Adapt<NPerBlock, Gemm1NPerBlock, KGridDesc_N_K>(
+            k_grid_desc_n_k);
+    }
+
+    using YGridDescriptor_MBlock_MPerBlock_OBlock_OPerBlock = remove_cvref_t<decltype(
+        MakeYGridDescriptor_MBlock_MPerBlock_OBlock_OPerBlock(YGridDesc_M_O{}))>;
+
+    using DefaultBlock2CTileMap =
+        remove_cvref_t<decltype(MakeDefaultBlock2CTileMap(KGridDesc_N_K{}))>;
+
+    using ZGridDescriptor_M0_N0_M1_N1_M2_N2_M3_N3_N4_N5 = remove_cvref_t<decltype(
+        MakeCGridDescriptor_M0_N0_M1_N1_M2_N2_M3_N3_N4_N5(ZGridDesc_M_N{}))>;
+
+    // S / dP Gemm (type 1 rcc)
+    struct Gemm0
+    {
+        // A matrix in LDS memory, dst of blockwise copy
+        static constexpr auto a_block_desc_ak0_m_ak1 =
+            GetABlockDescriptor_AK0PerBlock_MPerBlock_AK1();
+
+        // B matrix in LDS memory, dst of blockwise copy
+        static constexpr auto b_block_desc_bk0_n_bk1 =
+            GetBBlockDescriptor_BK0PerBlock_NPerBlock_BK1();
+
+        template <typename ABlockDesc_AK0_M_AK1>
+        __host__ __device__ static constexpr auto
+        MakeGemm0AMmaTileDescriptor_M0_M1_M2_K(const ABlockDesc_AK0_M_AK1&)
+        {
+            constexpr index_t MWaves = MPerBlock / (MXdlPerWave * MPerXdl);
+
+            return MakeGemmMmaTileDescriptor_MN0_MN1_MN2_K<MXdlPerWave, MWaves, MPerXdl>(
+                ABlockDesc_AK0_M_AK1{});
+        }
+
+        template <typename BBlockDesc_BK0_N_BK1>
+        __host__ __device__ static constexpr auto
+        MakeGemm0BMmaTileDescriptor_N0_N1_N2_K(const BBlockDesc_BK0_N_BK1&)
+        {
+            constexpr index_t NWaves = NPerBlock / (NXdlPerWave * NPerXdl);
+
+            return MakeGemmMmaTileDescriptor_MN0_MN1_MN2_K<NXdlPerWave, NWaves, NPerXdl>(
+                BBlockDesc_BK0_N_BK1{});
+        }
+
+        template <typename GridDesc_K0_M_K1>
+        using ABlockwiseCopy =
+            ThreadGroupTensorSliceTransfer_v4r1<ThisThreadBlock,
+                                                AElementwiseOperation,
+                                                tensor_operation::element_wise::PassThrough,
+                                                InMemoryDataOperationEnum::Set,
+                                                Sequence<AK0, MPerBlock, AK1>,
+                                                ABlockTransferThreadClusterLengths_AK0_M_AK1,
+                                                ABlockTransferThreadClusterArrangeOrder,
+                                                InputDataType,
+                                                GemmDataType,
+                                                GridDesc_K0_M_K1,
+                                                decltype(a_block_desc_ak0_m_ak1),
+                                                ABlockTransferSrcAccessOrder,
+                                                Sequence<1, 0, 2>,
+                                                ABlockTransferSrcVectorDim,
+                                                2,
+                                                ABlockTransferSrcScalarPerVector,
+                                                ABlockTransferDstScalarPerVector_AK1,
+                                                1,
+                                                1,
+                                                true, // SrcResetCoord
+                                                true, // DstResetCoord
+                                                NumGemmKPrefetchStage>;
+
+        template <typename GridDesc_K0_N_K1>
+        using BBlockwiseCopy =
+            ThreadGroupTensorSliceTransfer_v4r1<ThisThreadBlock,
+                                                BElementwiseOperation,
+                                                tensor_operation::element_wise::PassThrough,
+                                                InMemoryDataOperationEnum::Set,
+                                                Sequence<BK0, NPerBlock, BK1>,
+                                                BBlockTransferThreadClusterLengths_BK0_N_BK1,
+                                                BBlockTransferThreadClusterArrangeOrder,
+                                                InputDataType,
+                                                GemmDataType,
+                                                GridDesc_K0_N_K1,
+                                                decltype(b_block_desc_bk0_n_bk1),
+                                                BBlockTransferSrcAccessOrder,
+                                                Sequence<1, 0, 2>,
+                                                BBlockTransferSrcVectorDim,
+                                                2,
+                                                BBlockTransferSrcScalarPerVector,
+                                                BBlockTransferDstScalarPerVector_BK1,
+                                                1,
+                                                1,
+                                                true, // SrcResetCoord
+                                                true, // DstResetCoord
+                                                NumGemmKPrefetchStage>;
+
+        static constexpr index_t KPack =
+            math::max(math::lcm(AK1, BK1),
+                      MfmaSelector<GemmDataType, MPerXdl, NPerXdl>::selected_mfma.k_per_blk);
+
+        // Blockwise gemm with transposed XDL output
+        using BlockwiseGemm = BlockwiseGemmXdlops_v2<
+            BlockSize,
+            GemmDataType,
+            FloatGemmAcc,
+            decltype(a_block_desc_ak0_m_ak1),
+            decltype(b_block_desc_bk0_n_bk1),
+            decltype(MakeGemm0AMmaTileDescriptor_M0_M1_M2_K(a_block_desc_ak0_m_ak1)),
+            decltype(MakeGemm0BMmaTileDescriptor_N0_N1_N2_K(b_block_desc_bk0_n_bk1)),
+            MPerBlock,
+            NPerBlock,
+            KPerBlock,
+            MPerXdl,
+            NPerXdl,
+            MXdlPerWave,
+            NXdlPerWave,
+            KPack>;
+
+        static constexpr auto a_block_slice_copy_step = make_multi_index(KPerBlock / AK1, 0, 0);
+        static constexpr auto b_block_slice_copy_step = make_multi_index(KPerBlock / BK1, 0, 0);
+    };
+
+    // dV / dK Gemm (type 2 rrr)
+    template <typename ASrcThreadDesc_M0_N0_M1_N1_M2_M3_M4_N2,
+              typename ASrcBlockDesc_M0_N0_M1_N1_M2_M3_M4_N2>
+    struct Gemm1
+    {
+        private:
+        static constexpr auto m0 = ASrcThreadDesc_M0_N0_M1_N1_M2_M3_M4_N2{}.GetLength(I0);
+        static constexpr auto n0 = ASrcThreadDesc_M0_N0_M1_N1_M2_M3_M4_N2{}.GetLength(I1);
+        static constexpr auto m1 = ASrcThreadDesc_M0_N0_M1_N1_M2_M3_M4_N2{}.GetLength(I2);
+        static constexpr auto n1 = ASrcThreadDesc_M0_N0_M1_N1_M2_M3_M4_N2{}.GetLength(I3);
+        static constexpr auto m2 = ASrcThreadDesc_M0_N0_M1_N1_M2_M3_M4_N2{}.GetLength(I4);
+        static constexpr auto m3 = ASrcThreadDesc_M0_N0_M1_N1_M2_M3_M4_N2{}.GetLength(I5);
+        static constexpr auto m4 = ASrcThreadDesc_M0_N0_M1_N1_M2_M3_M4_N2{}.GetLength(I6);
+        static constexpr auto n2 = ASrcThreadDesc_M0_N0_M1_N1_M2_M3_M4_N2{}.GetLength(I7);
+
+        // M2 num_groups_per_blk, M3 num_input_blks, M4 group_size
+        static constexpr auto M3 = ASrcBlockDesc_M0_N0_M1_N1_M2_M3_M4_N2{}.GetLength(I5);
+
+        public:
+        static constexpr auto AThreadSliceLength_K0 = Number<Gemm1KPerBlock / m4 / M3>{};
+        static constexpr auto AThreadSliceLength_M  = Number<n0 * n1 * n2>{};
+        static constexpr auto AThreadSliceLength_K1 = Number<m4>{};
+
+        // A source matrix layout in AccVGPR
+        static constexpr auto a_src_thread_desc_k0_m_k1 =
+            GetA1SrcThreadDescriptor_AK0PerBlock_MPerBlock_AK1(
+                ASrcThreadDesc_M0_N0_M1_N1_M2_M3_M4_N2{});
+
+        // A matrix in VGPR memory, dst of AccVGPR-to-VGPR copy
+        static constexpr auto a_thread_desc_k0_m_k1 = make_naive_tensor_descriptor_packed(
+            make_tuple(AThreadSliceLength_K0, AThreadSliceLength_M, AThreadSliceLength_K1));
+
+        // B matrix in LDS memory, dst of blockwise copy
+        static constexpr auto b_block_desc_bk0_n_bk1 =
+            GetB1BlockDescriptor_BK0PerBlock_NPerBlock_BK1();
+
+        template <typename ABlockDesc_AK0_M_AK1>
+        __host__ __device__ static constexpr auto
+        MakeGemm1AMmaTileDescriptor_M0_M1_M2_K(const ABlockDesc_AK0_M_AK1&)
+        {
+            return MakeGemmMmaTileDescriptor_MN0_MN1_MN2_K<NXdlPerWave, 1, 1>(
+                ABlockDesc_AK0_M_AK1{});
+        }
+
+        template <typename BBlockDesc_BK0_N_BK1>
+        __host__ __device__ static constexpr auto
+        MakeGemm1BMmaTileDescriptor_N0_N1_N2_K(const BBlockDesc_BK0_N_BK1&)
+        {
+            constexpr index_t Gemm1NWaves = Gemm1NPerBlock / (Gemm1NXdlPerWave * NPerXdl);
+            return MakeGemmMmaTileDescriptor_MN0_MN1_MN2_K<Gemm1NXdlPerWave, Gemm1NWaves, NPerXdl>(
+                BBlockDesc_BK0_N_BK1{});
+        }
+
+        static constexpr auto ASrcScalarPerVector = m4;
+
+        using AThreadSliceLengths_K0_M_K1 = decltype(a_thread_desc_k0_m_k1.GetLengths());
+
+        template <typename ElementwiseOp = tensor_operation::element_wise::PassThrough>
+        using ABlockwiseCopy =
+            ThreadwiseTensorSliceTransfer_StaticToStatic<FloatGemmAcc,
+                                                         GemmDataType,
+                                                         decltype(a_src_thread_desc_k0_m_k1),
+                                                         decltype(a_thread_desc_k0_m_k1),
+                                                         ElementwiseOp,
+                                                         AThreadSliceLengths_K0_M_K1,
+                                                         Sequence<1, 0, 2>,
+                                                         2,
+                                                         ASrcScalarPerVector>;
+
+        template <typename GridDesc_K0_N_K1>
+        using BBlockwiseCopy =
+            ThreadGroupTensorSliceTransfer_v4r1<ThisThreadBlock,
+                                                BElementwiseOperation,
+                                                tensor_operation::element_wise::PassThrough,
+                                                InMemoryDataOperationEnum::Set,
+                                                Sequence<B1K0, Gemm1NPerBlock, B1K1>,
+                                                B1BlockTransferThreadClusterLengths_BK0_N_BK1,
+                                                B1BlockTransferThreadClusterArrangeOrder,
+                                                InputDataType,
+                                                GemmDataType,
+                                                GridDesc_K0_N_K1,
+                                                decltype(b_block_desc_bk0_n_bk1),
+                                                B1BlockTransferSrcAccessOrder,
+                                                Sequence<1, 0, 2>,
+                                                B1BlockTransferSrcVectorDim,
+                                                2,
+                                                B1BlockTransferSrcScalarPerVector,
+                                                B1BlockTransferDstScalarPerVector_BK1,
+                                                1,
+                                                1,
+                                                B1ThreadTransferSrcResetCoordinateAfterRun,
+                                                true, // DstResetCoord
+                                                NumGemmKPrefetchStage>;
+
+        // for a_block_slice_copy_step to be able to address static buffers, it MUST be a
+        // tuple-based container as well as containing ONLY integral constants
+        static constexpr auto a_block_slice_copy_step = make_tuple(AThreadSliceLength_K0, I0, I0);
+        static constexpr auto b_block_slice_copy_step =
+            make_multi_index(Gemm1KPerBlock / B1K1, 0, 0);
+
+        // selected_mfma.group_size or B1K1 <= Gemm1KPack <= selected_mfma.group_size
+        // selected_mfma.k_per_blk <= Gemm1KPack
+        //
+        // Following similar rationale behind Gemm0KPack, let Gemm1KPack be the lowest common
+        // multiples of A1K1 (predetermined by selected_mfma.group_size) and B1K1. But in this case
+        // Gemm1KPack can't be higher than A1K1 itself because A1 matrix is distributed in VGPRs
+        // with 'group_size' amount of contiguous elements. Having Gemm1KPack greater than A1K1 will
+        // cause mismatch in summation index for example c[0:7] = a1[[0:3, 8:11]] * b1[0:7].
+        // therefore we may just as well assign Gemm1KPack = group_size
+        static constexpr index_t GemmKPack =
+            MfmaSelector<GemmDataType, MPerXdl, NPerXdl>::selected_mfma.group_size;
+
+        using BlockwiseGemm = BlockwiseGemmXdlops_v2<
+            BlockSize,
+            GemmDataType,
+            FloatGemmAcc,
+            decltype(a_thread_desc_k0_m_k1),
+            decltype(b_block_desc_bk0_n_bk1),
+            decltype(MakeGemm1AMmaTileDescriptor_M0_M1_M2_K(a_thread_desc_k0_m_k1)),
+            decltype(MakeGemm1BMmaTileDescriptor_N0_N1_N2_K(b_block_desc_bk0_n_bk1)),
+            NPerBlock,
+            Gemm1NPerBlock,
+            Gemm1KPerBlock,
+            MPerXdl,
+            NPerXdl,
+            NXdlPerWave,
+            Gemm1NXdlPerWave,
+            GemmKPack,
+            true,      // TransposeC
+            GemmKPack, // AMmaKStride
+            GemmKPack * XdlopsGemm<GemmDataType, MPerXdl, NPerXdl, GemmKPack, false>{}
+                            .K0PerXdlops /* BMmaKStride */>;
+    };
+
+    // dQ Gemm (type 3 crr)
+    // Describes tuning parameter for C2_m_n = A2_m_k * B2_k_n
+    template <index_t Sum_K_ = NPerXdl * 2>
+    struct Gemm2Params_
+    {
+        static constexpr index_t Gemm2_M = MPerBlock;
+        static constexpr index_t Gemm2_K = NPerBlock;
+        static constexpr index_t Gemm2_N = Gemm1NPerBlock;
+        static constexpr index_t Sum_K   = Sum_K_;
+
+        static constexpr index_t A_K1     = 8; // P will be row-major
+        static constexpr index_t A_K0     = Sum_K / A_K1;
+        static constexpr index_t A_LdsPad = 0; // how many multiples of K1 per M * K1 elements
+
+        static constexpr index_t B_K1     = B1K1; // dY assumed row-major, typically =2 for fp16
+        static constexpr index_t B_K0     = Sum_K / B_K1;
+        static constexpr index_t B_LdsPad = 0; // how many multiples of K1 per N * K1 elements
+
+        static_assert(Sum_K % NPerXdl == 0, "");
+
+        static constexpr index_t BSrcVectorDim       = 1; // Gemm2_N dimension
+        static constexpr index_t BSrcScalarPerVector = 4;
+
+        static constexpr index_t GemmNWave   = Gemm2_N / Gemm2NXdlPerWave / NPerXdl;
+        static constexpr index_t GemmMWave   = BlockSize / get_warp_size() / GemmNWave;
+        static constexpr index_t GemmNRepeat = Gemm2NXdlPerWave;
+        static constexpr index_t GemmMRepeat = Gemm2_M / GemmMWave / MPerXdl;
+        static constexpr index_t GemmKPack =
+            math::max(math::lcm(A_K1, B_K1),
+                      MfmaSelector<GemmDataType, MPerXdl, NPerXdl>::selected_mfma.k_per_blk);
+
+        using BBlockSliceLengths = Sequence<B_K0, Gemm2_N, B_K1>;
+        using BThreadClusterLengths =
+            Sequence<BlockSize / (Gemm2_N / BSrcScalarPerVector), Gemm2_N / BSrcScalarPerVector, 1>;
+        using BThreadClusterArrangeOrder = Sequence<0, 2, 1>;
+
+        __host__ __device__ static constexpr auto GetABlockSliceLengths_M0_K0_M1_K1_M2_K2()
+        {
+            // perform manual unmerge: n -> n_repeat, n_waves, n_per_xdl
+            constexpr index_t k  = Gemm2Params::Sum_K - 1;
+            constexpr index_t k2 = k % NPerXdl;
+            constexpr index_t k1 = k / NPerXdl % Gemm0NWaves;
+            constexpr index_t k0 = k / NPerXdl / Gemm0NWaves % NXdlPerWave;
+
+            // perform manual unmerge: m -> m_repeat, m_waves, m_per_xdl
+            constexpr index_t m  = Gemm2Params::Gemm2_M - 1;
+            constexpr index_t m2 = m % MPerXdl;
+            constexpr index_t m1 = m / MPerXdl % Gemm0MWaves;
+            constexpr index_t m0 = m / MPerXdl / Gemm0MWaves % MXdlPerWave;
+
+            // assume 256 decomposed into 2 x 4 x 32
+            // 1d idx ( 32 - 1) -> 3d idx 0, 0, 31 -> 3d dim 1 x 1 x 32
+            // 1d idx (256 - 1) -> 3d idx 1, 3, 31 -> 3d dim 2 x 4 x 32
+            return Sequence<m0, k0, m1, k1, m2, k2>{} + Sequence<1, 1, 1, 1, 1, 1>{};
+        }
+
+        __host__ __device__ static constexpr auto GetABlockSliceLengths_M0_K0_M1_K1()
+        {
+            return generate_sequence_v2(
+                [](auto I) { return GetABlockSliceLengths_M0_K0_M1_K1_M2_K2().At(I); },
+                Number<4>{});
+        }
+
+        using ABlockSliceLengths_M0_K0_M1_K1 =
+            decltype(GetABlockSliceLengths_M0_K0_M1_K1()); //(2, 1, 1, 2) //(4, 1, 1, 2)
+    };
+    using Gemm2Params = Gemm2Params_<>; // tune later
+
+    // dQ Gemm (type 3 crr)
+    template <typename Gemm2Params, typename ASrcBlockwiseGemm>
+    struct Gemm2
+    {
+        private:
+        static constexpr auto a_src_block_desc_m0_n0_m1_n1_m2_m3_m4_n2 =
+            ASrcBlockwiseGemm::GetCBlockDescriptor_M0_N0_M1_N1_M2_M3_M4_N2();
+        static constexpr auto M0 = a_src_block_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I0); // repeat
+        static constexpr auto N0 = a_src_block_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I1);
+        static constexpr auto M1 = a_src_block_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I2); // wave
+        static constexpr auto N1 = a_src_block_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I3);
+        static constexpr auto M2 = a_src_block_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I4); // xdl
+        static constexpr auto M3 = a_src_block_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I5);
+        static constexpr auto M4 = a_src_block_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I6);
+        static constexpr auto N2 = a_src_block_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I7);
+
+        public:
+        // A source matrix layout in VGPR, src of VGPR-to-LDS copy
+        static constexpr auto a_src_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2 =
+            ASrcBlockwiseGemm::GetCThreadDescriptor_M0_N0_M1_N1_M2_M3_M4_N2();
+
+        // A matrix in LDS memory, dst of blockwise copy
+        static constexpr auto a_block_desc_k0_m_k1 = GetA2BlockDescriptor_K0_M_K1<Gemm2Params>();
+
+        // B matrix in LDS memory, dst of blockwise copy
+        static constexpr auto b_block_desc_k0_n_k1 = GetB2BlockDescriptor_K0_N_K1<Gemm2Params>();
+
+        __host__ __device__ static constexpr auto MakeABlockDesc_M0_K0_M1_K1_M2_M3_M4_K2()
+        {
+            const auto K0_ = a_block_desc_k0_m_k1.GetLength(I0);
+            const auto M_  = a_block_desc_k0_m_k1.GetLength(I1);
+            const auto K1_ = a_block_desc_k0_m_k1.GetLength(I2);
+
+            const auto a_block_desc_m_k = transform_tensor_descriptor(
+                a_block_desc_k0_m_k1,
+                make_tuple(make_merge_transform_v3_division_mod(make_tuple(K0_, K1_)),
+                           make_pass_through_transform(M_)),
+                make_tuple(Sequence<0, 2>{}, Sequence<1>{}),
+                make_tuple(Sequence<1>{}, Sequence<0>{}));
+
+            // HACK: for unmerge transform, the length of highest dim is irrelevant so we put dummy
+            // variable I1 there
+            return transform_tensor_descriptor(
+                a_block_desc_m_k,
+                make_tuple(make_unmerge_transform(make_tuple(I1, M1, M2, M3, M4)),
+                           make_unmerge_transform(make_tuple(I1, N1, N2))),
+                make_tuple(Sequence<0>{}, Sequence<1>{}),
+                make_tuple(Sequence<0, 2, 4, 5, 6>{}, Sequence<1, 3, 7>{}));
+        }
+
+        // Note: we will perform sub-workgroup VGPR-to-LDS copy to save LDS space, therefore the
+        // destination coordinate can overlap between wavefronts in a workgroup as seen in the mod
+        // operation before returning the values
+        __host__ __device__ static auto MakeAThreadOriginOnBlock_M0_K0_M1_K1_M2_M3_M4_K2()
+        {
+            const auto a_thread_origin_on_block_idx =
+                ASrcBlockwiseGemm::CalculateCThreadOriginDataIndex8D(I0, I0, I0, I0);
+
+            constexpr auto a_block_slice_lengths_m0_k0_m1_k1 =
+                typename Gemm2Params::ABlockSliceLengths_M0_K0_M1_K1{}; // mrepeat, nrepeat,
+                                                                        // mwaves, nwaves,
+
+            return make_tuple(
+                a_thread_origin_on_block_idx[I0],                                         // mrepeat
+                a_thread_origin_on_block_idx[I1],                                         // nrepeat
+                a_thread_origin_on_block_idx[I2] % a_block_slice_lengths_m0_k0_m1_k1[I2], // mwave
+                a_thread_origin_on_block_idx[I3] % a_block_slice_lengths_m0_k0_m1_k1[I3], // nwave
+                a_thread_origin_on_block_idx[I4],                                         // xdlops
+                a_thread_origin_on_block_idx[I5],
+                a_thread_origin_on_block_idx[I6],
+                a_thread_origin_on_block_idx[I7]);
+        }
+
+        static constexpr auto a_block_desc_m0_k0_m1_k1_m2_m3_m4_k2 =
+            MakeABlockDesc_M0_K0_M1_K1_M2_M3_M4_K2();
+
+        using ASrcBlockSliceWindowIterator =
+            SpaceFillingCurve<Sequence<M0, N0, M1, N1>,
+                              Sequence<0, 1, 2, 3>,
+                              typename Gemm2Params::ABlockSliceLengths_M0_K0_M1_K1,
+                              false>;
+
+        template <typename ElementwiseOp = tensor_operation::element_wise::PassThrough>
+        using ABlockwiseCopy = ThreadwiseTensorSliceTransfer_v1r3<
+            FloatGemmAcc,
+            GemmDataType,
+            decltype(a_src_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2),
+            decltype(a_block_desc_m0_k0_m1_k1_m2_m3_m4_k2),
+            ElementwiseOp,
+            Sequence<Gemm2Params::ABlockSliceLengths_M0_K0_M1_K1::At(I0), // ThreadSliceLengths
+                     Gemm2Params::ABlockSliceLengths_M0_K0_M1_K1::At(I1),
+                     I1,
+                     I1,
+                     M2,
+                     I1,
+                     M4,
+                     I1>,
+            Sequence<0, 1, 2, 3, 4, 5, 6, 7>,
+            7, // DstVectorDim
+            1, // DstScalarPerVector
+            InMemoryDataOperationEnum::Set,
+            1, // DstScalarStrideInVector
+            true>;
+
+        template <typename GridDesc_K0_N_K1>
+        using BBlockwiseCopy = ThreadGroupTensorSliceTransfer_v4r1<
+            ThisThreadBlock,
+            tensor_operation::element_wise::PassThrough,
+            tensor_operation::element_wise::PassThrough,
+            InMemoryDataOperationEnum::Set,
+            typename Gemm2Params::BBlockSliceLengths,
+            typename Gemm2Params::BThreadClusterLengths,
+            typename Gemm2Params::BThreadClusterArrangeOrder,
+            InputDataType,
+            GemmDataType,
+            GridDesc_K0_N_K1,
+            decltype(b_block_desc_k0_n_k1),
+            typename Gemm2Params::BThreadClusterArrangeOrder, // access order == thread order
+            Sequence<1, 0, 2>,
+            Gemm2Params::BSrcVectorDim,
+            2, // DstVectorDim
+            Gemm2Params::BSrcScalarPerVector,
+            Gemm2Params::B_K1,
+            1,
+            1,
+            true,
+            true,
+            1>;
+
+        using BlockwiseGemm =
+            BlockwiseGemmXdlops_k0mk1_k0nk1_m0n0m1n1m2m3m4n2_v1<BlockSize,
+                                                                GemmDataType,
+                                                                FloatGemmAcc,
+                                                                decltype(a_block_desc_k0_m_k1),
+                                                                decltype(b_block_desc_k0_n_k1),
+                                                                MPerXdl,
+                                                                NPerXdl,
+                                                                Gemm2Params::GemmMRepeat,
+                                                                Gemm2Params::GemmNRepeat,
+                                                                Gemm2Params::GemmKPack,
+                                                                true>; // TranspossC
+
+        static constexpr auto b_block_slice_copy_step = make_multi_index(Gemm2Params::B_K0, 0, 0);
+        static constexpr auto c_block_slice_copy_step =
+            make_multi_index(-Gemm2Params::GemmMRepeat, 0, 0, 0, 0, 0, 0, 0);
+        static constexpr auto b_block_reset_copy_step =
+            make_multi_index(-NPerBlock / Gemm2Params::B_K1, 0, 0);
+
+        template <typename CGradDesc_M_N>
+        __host__ __device__ static auto
+        MakeCGridDesc_M0_N0_M1_N1_M2_N2_N3_N4(const CGradDesc_M_N& c_grid_desc_m_n)
+        {
+            // HACK: for unmerge transform, the length of highest dim is irrelevant so we put dummy
+            // variable I1 there
+            const auto c_grid_desc_m0_n0_m1_n1_m2_n2 = transform_tensor_descriptor(
+                c_grid_desc_m_n,
+                make_tuple(make_unmerge_transform(make_tuple(I1, Gemm2Params::GemmMWave, MPerXdl)),
+                           make_unmerge_transform(make_tuple(I1, Gemm2Params::GemmNWave, NPerXdl))),
+                make_tuple(Sequence<0>{}, Sequence<1>{}),
+                make_tuple(Sequence<0, 2, 4>{}, Sequence<1, 3, 5>{}));
+
+            const auto c_grid_desc_m0_n0_m1_n1_m2_n2_n3_n4 =
+                BlockwiseGemm{}.xdlops_gemm.MakeCDescriptor_M0_N0_M1_N1_M2_N2_N3_N4(
+                    c_grid_desc_m0_n0_m1_n1_m2_n2);
+
+            return c_grid_desc_m0_n0_m1_n1_m2_n2_n3_n4;
+        }
+
+        static constexpr auto c_thread_desc_m0_n0_m1_n1_m2_n2_n3_n4 =
+            BlockwiseGemm::GetCThreadDescriptor_M0_N0_M1_N1_M2_N2_N3_N4();
+
+        __host__ __device__ static auto GetCThreadOriginOnBlock_M0_N0_M1_N1_M2_N2_N3_N4()
+        {
+            return to_multi_index(BlockwiseGemm::CalculateCThreadOriginDataIndex8D(I0, I0, I0, I0));
+        }
+
+        template <typename CGridDesc_M0_N0_M1_N1_M2_N2_N3_N4,
+                  typename ElementwiseOp = tensor_operation::element_wise::PassThrough>
+        using CBlockwiseCopy = ThreadwiseTensorSliceTransfer_v1r3<
+            FloatGemmAcc,
+            OutputDataType,
+            decltype(c_thread_desc_m0_n0_m1_n1_m2_n2_n3_n4),
+            CGridDesc_M0_N0_M1_N1_M2_N2_N3_N4,
+            ElementwiseOp,                                                // CElementwiseOperation
+            decltype(c_thread_desc_m0_n0_m1_n1_m2_n2_n3_n4.GetLengths()), // SliceLengths
+            Sequence<0, 1, 2, 3, 4, 5, 6, 7>,                             // AccessOrder
+            7,                                                            // VectorDim
+            2,                                                            // ScalarPerVector
+            InMemoryDataOperationEnum::AtomicAdd, // GlobalMemoryDataOperation
+            1,                                    // DstScalarStrideInVector
+            true>;
+    };
+
+    template <index_t BlockSize_, index_t BlockSliceLength_M_, index_t BlockSliceLength_O_>
+    struct YDotYGrad_M_O_
+    {
+        static constexpr index_t SrcScalarPerVector = 16 / sizeof(InputDataType);
+        static constexpr auto ThreadClusterLength_O =
+            Number<BlockSliceLength_O_ / SrcScalarPerVector>{};
+        static constexpr auto ThreadClusterLength_M = Number<BlockSize_ / ThreadClusterLength_O>{};
+        static constexpr auto ThreadSliceLength_O   = Number<SrcScalarPerVector>{};
+        static constexpr auto ThreadSliceLength_M =
+            Number<BlockSliceLength_M_ * ThreadClusterLength_O / BlockSize_>{};
+
+        static_assert(ThreadClusterLength_O * ThreadSliceLength_O == BlockSliceLength_O_, "");
+        static_assert(ThreadClusterLength_M * ThreadSliceLength_M == BlockSliceLength_M_, "");
+
+        using SrcBufType = StaticBuffer<AddressSpaceEnum::Vgpr,
+                                        FloatGemmAcc,
+                                        ThreadSliceLength_M * ThreadSliceLength_O,
+                                        true>;
+
+        using DstBufType =
+            StaticBuffer<AddressSpaceEnum::Vgpr, FloatGemmAcc, ThreadSliceLength_M, true>;
+    };
+    using YDotYGrad_M_O = YDotYGrad_M_O_<BlockSize, MPerBlock, Gemm1NPerBlock>;
+
+    // PGrad Gemm has the same layout as P = Q * K^T Gemm (A row-major B col-major)
+    struct PGradGemmTile_M_N_O
+    {
+        // TODO:
+        // Make all input tensors 2D and transform them into appropriate 3D form in kernel to make
+        // things more concise
+        template <typename YGradGridDesc_M0_O_M1_>
+        __device__ static auto
+        MakeYGradGridDesc_O0_M_O1(const YGradGridDesc_M0_O_M1_& ygrad_grid_desc_m0_o_m1)
+        {
+            const auto M0 = ygrad_grid_desc_m0_o_m1.GetLength(I0);
+            const auto O  = ygrad_grid_desc_m0_o_m1.GetLength(I1);
+            const auto M1 = ygrad_grid_desc_m0_o_m1.GetLength(I2);
+
+            constexpr auto Y_O1 = AK1;
+            const auto Y_O0     = O / Y_O1;
+
+            const auto ygrad_grid_desc_o0_m_o1 = transform_tensor_descriptor(
+                ygrad_grid_desc_m0_o_m1,
+                make_tuple(make_unmerge_transform(make_tuple(Y_O0, Y_O1)),
+                           make_merge_transform_v3_division_mod(make_tuple(M0, M1))),
+                make_tuple(Sequence<1>{}, Sequence<0, 2>{}),
+                make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
+
+            return ygrad_grid_desc_o0_m_o1;
+        }
+
+        template <typename VGridDesc_N0_O_N1_>
+        __device__ static auto MakeVGridDesc_O0_N_O1(const VGridDesc_N0_O_N1_& v_grid_desc_n0_o_n1)
+        {
+            const auto N0 = v_grid_desc_n0_o_n1.GetLength(I0);
+            const auto O  = v_grid_desc_n0_o_n1.GetLength(I1);
+            const auto N1 = v_grid_desc_n0_o_n1.GetLength(I2);
+
+            constexpr auto V_O1 = BK1;
+            const auto V_O0     = O / V_O1;
+
+            const auto v_grid_desc_o0_n_o1 = transform_tensor_descriptor(
+                v_grid_desc_n0_o_n1,
+                make_tuple(make_unmerge_transform(make_tuple(V_O0, V_O1)),
+                           make_merge_transform_v3_division_mod(make_tuple(N0, N1))),
+                make_tuple(Sequence<1>{}, Sequence<0, 2>{}),
+                make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
+
+            return v_grid_desc_o0_n_o1;
+        }
+    };
+
+    // QGrad Gemm has the same layout as Y = P * V Gemm (A in acc B row-major)
+    struct QGradGemmTile_M_K_N
+    {
+        template <typename KGridDesc_K0_N_K1_>
+        __device__ static auto MakeKGridDesc_N0_K_N1(const KGridDesc_K0_N_K1_& k_grid_desc_k0_n_k1)
+        {
+            const auto K_K0 = k_grid_desc_k0_n_k1.GetLength(I0);
+            const auto N    = k_grid_desc_k0_n_k1.GetLength(I1);
+            const auto K_K1 = k_grid_desc_k0_n_k1.GetLength(I2);
+
+            constexpr auto K_N1 = B1K1;
+            const auto K_N0     = N / K_N1;
+
+            const auto k_grid_desc_n0_k_n1 = transform_tensor_descriptor(
+                k_grid_desc_k0_n_k1,
+                make_tuple(make_unmerge_transform(make_tuple(K_N0, K_N1)),
+                           make_merge_transform_v3_division_mod(make_tuple(K_K0, K_K1))),
+                make_tuple(Sequence<1>{}, Sequence<0, 2>{}),
+                make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
+
+            return k_grid_desc_n0_k_n1;
+        }
+    };
+
+    struct KGradGemmTile_N_K_M
+    {
+        // B position
+        template <typename QGridDesc_K0_M_K1_>
+        __device__ static auto MakeQGridDesc_M0_K_M1(const QGridDesc_K0_M_K1_& q_grid_desc_k0_m_k1)
+        {
+            const auto Q_K0 = q_grid_desc_k0_m_k1.GetLength(I0);
+            const auto M    = q_grid_desc_k0_m_k1.GetLength(I1);
+            const auto Q_K1 = q_grid_desc_k0_m_k1.GetLength(I2);
+
+            constexpr auto Q_M1 = B1K1;
+            const auto Q_M0     = M / Q_M1;
+
+            const auto q_grid_desc_m0_k_m1 = transform_tensor_descriptor(
+                q_grid_desc_k0_m_k1,
+                make_tuple(make_unmerge_transform(make_tuple(Q_M0, Q_M1)),
+                           make_merge_transform_v3_division_mod(make_tuple(Q_K0, Q_K1))),
+                make_tuple(Sequence<1>{}, Sequence<0, 2>{}),
+                make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
+
+            return q_grid_desc_m0_k_m1;
+        }
+    };
+
+    struct SharedMemTrait
+    {
+        // LDS allocation for A and B: be careful of alignment
+        static constexpr auto a_block_desc_ak0_m_ak1 =
+            GetABlockDescriptor_AK0PerBlock_MPerBlock_AK1();
+        static constexpr auto b_block_desc_bk0_n_bk1 =
+            GetBBlockDescriptor_BK0PerBlock_NPerBlock_BK1();
+        static constexpr auto b1_block_desc_bk0_n_bk1 =
+            GetB1BlockDescriptor_BK0PerBlock_NPerBlock_BK1();
+        static constexpr auto a2_block_desc_k0_m_k1 = GetA2BlockDescriptor_K0_M_K1<Gemm2Params>();
+        static constexpr auto b2_block_desc_k0_n_k1 = GetB2BlockDescriptor_K0_N_K1<Gemm2Params>();
+
+        static constexpr auto max_lds_align = Number<16 / sizeof(GemmDataType)>{};
+
+        static constexpr auto a_block_space_size_aligned = math::integer_least_multiple(
+            a_block_desc_ak0_m_ak1.GetElementSpaceSize(), max_lds_align);
+        static constexpr auto b_block_space_size_aligned = math::integer_least_multiple(
+            b_block_desc_bk0_n_bk1.GetElementSpaceSize(), max_lds_align);
+        static constexpr auto b1_block_space_size_aligned = math::integer_least_multiple(
+            b1_block_desc_bk0_n_bk1.GetElementSpaceSize(), max_lds_align);
+        static constexpr auto a2_block_space_size_aligned = math::integer_least_multiple(
+            a2_block_desc_k0_m_k1.GetElementSpaceSize(), max_lds_align);
+        static constexpr auto b2_block_space_size_aligned = math::integer_least_multiple(
+            b2_block_desc_k0_n_k1.GetElementSpaceSize(), max_lds_align);
+
+        static constexpr auto a_block_space_offset  = 0;
+        static constexpr auto b_block_space_offset  = a_block_space_size_aligned.value;
+        static constexpr auto b1_block_space_offset = 0;
+        static constexpr auto a2_block_space_offset = 0;
+        static constexpr auto b2_block_space_offset = a2_block_space_size_aligned.value;
+
+        // LDS allocation for reduction
+        static constexpr index_t reduction_space_size_aligned =
+            math::integer_least_multiple(BlockSize, max_lds_align);
+
+        static constexpr auto reduction_space_offset = 0;
+
+        // LDS allocation for C shuffle in LDS
+        static constexpr auto c_shuffle_block_desc_mblock_mperblock_nblock_nperblock =
+            GetCShuffleBlockDescriptor_MBlock_MPerBlock_NBlock_NPerBlock();
+        static constexpr auto c_block_space_size =
+            c_shuffle_block_desc_mblock_mperblock_nblock_nperblock.GetElementSpaceSize();
+    };
+
+    __host__ __device__ static constexpr index_t GetSharedMemoryNumberOfByte()
+    {
+        const index_t gemm0_bytes_end = (SharedMemTrait::a_block_space_size_aligned +
+                                         SharedMemTrait::b_block_space_size_aligned) *
+                                        sizeof(GemmDataType);
+        const index_t gemm1_bytes_end =
+            (SharedMemTrait::b1_block_space_offset + SharedMemTrait::b1_block_space_size_aligned) *
+            sizeof(GemmDataType);
+        const index_t gemm2_bytes_end = (SharedMemTrait::a2_block_space_size_aligned +
+                                         SharedMemTrait::b2_block_space_size_aligned) *
+                                        sizeof(GemmDataType);
+
+        const index_t softmax_bytes_end = (SharedMemTrait::reduction_space_offset +
+                                           SharedMemTrait::reduction_space_size_aligned) *
+                                          sizeof(FloatGemmAcc);
+        const index_t c_block_bytes_end =
+            SharedMemTrait::c_block_space_size * sizeof(FloatCShuffle);
+
+        return math::max(gemm0_bytes_end,
+                         gemm1_bytes_end,
+                         gemm2_bytes_end,
+                         softmax_bytes_end,
+                         c_block_bytes_end);
+    }
+
+    template <bool HasMainKBlockLoop,
+              typename Block2CTileMap,
+              typename C0MatrixMask,
+              typename YGradGridDesc_M0_O_M1>
+    __device__ static void Run(const InputDataType* __restrict__ p_q_grid,
+                               const InputDataType* __restrict__ p_k_grid,
+                               ZDataType* __restrict__ p_z_grid,
+                               const InputDataType* __restrict__ p_v_grid,
+                               const InputDataType* __restrict__ p_y_grid,
+                               const FloatLSE* __restrict__ p_lse_grid,
+                               const InputDataType* __restrict__ p_ygrad_grid,
+                               OutputDataType* __restrict__ p_qgrad_grid,
+                               OutputDataType* __restrict__ p_kgrad_grid,
+                               OutputDataType* __restrict__ p_vgrad_grid,
+                               void* __restrict__ p_shared,
+                               const AElementwiseOperation& a_element_op,
+                               const BElementwiseOperation& b_element_op,
+                               const SElementwiseOperation& s_element_op,
+                               const B1ElementwiseOperation& b1_element_op,
+                               const CElementwiseOperation& c_element_op,
+                               const QGridDesc_K0_M_K1& q_grid_desc_k0_m_k1,
+                               const KGridDesc_K0_N_K1& k_grid_desc_k0_n_k1,
+                               const ZGridDescriptor_M0_N0_M1_N1_M2_N2_M3_N3_N4_N5&
+                                   z_grid_desc_m0_n0_m1_n1_m2_n2_m3_n3_n4_n5,
+                               const VGridDesc_N0_O_N1& v_grid_desc_n0_o_n1,
+                               const YGridDescriptor_MBlock_MPerBlock_OBlock_OPerBlock&
+                                   y_grid_desc_mblock_mperblock_oblock_operblock,
+                               const LSEGridDesc_M& lse_grid_desc_m,
+                               const YGradGridDesc_M0_O_M1& ygrad_grid_desc_m0_o_m1,
+                               const Block2CTileMap& block_2_ctile_map,
+                               const C0MatrixMask& c0_matrix_mask,
+                               const float p_drop,
+                               ck::philox& ph,
+                               const index_t block_idx_n)
+    {
+        const FloatGemmAcc p_dropout  = type_convert<FloatGemmAcc>(1.0f - p_drop);
+        const FloatGemmAcc rp_dropout = type_convert<FloatGemmAcc>(1.0f / p_dropout);
+        const ushort p_dropout_in_16bits =
+            __builtin_amdgcn_readfirstlane(std::floor(p_dropout * 65535.0));
+        const tensor_operation::element_wise::Scale scale_rp_dropout(s_element_op.Value() *
+                                                                     rp_dropout);
+
+        const auto q_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
+            p_q_grid, q_grid_desc_k0_m_k1.GetElementSpaceSize());
+        const auto k_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
+            p_k_grid, k_grid_desc_k0_n_k1.GetElementSpaceSize());
+        const auto v_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
+            p_v_grid, v_grid_desc_n0_o_n1.GetElementSpaceSize());
+        const auto y_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
+            p_y_grid, y_grid_desc_mblock_mperblock_oblock_operblock.GetElementSpaceSize());
+        const auto lse_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
+            p_lse_grid, lse_grid_desc_m.GetElementSpaceSize());
+        const auto ygrad_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
+            p_ygrad_grid, ygrad_grid_desc_m0_o_m1.GetElementSpaceSize());
+        auto vgrad_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
+            p_vgrad_grid, v_grid_desc_n0_o_n1.GetElementSpaceSize());
+        auto qgrad_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
+            p_qgrad_grid, q_grid_desc_k0_m_k1.GetElementSpaceSize());
+        auto kgrad_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
+            p_kgrad_grid, k_grid_desc_k0_n_k1.GetElementSpaceSize());
+
+        // divide block work by [N, K]
+        const auto block_work_idx =
+            block_2_ctile_map.CalculateBottomIndex(make_multi_index(get_block_1d_id()));
+
+        const index_t block_work_idx_n = Deterministic ? block_idx_n : block_work_idx[I0];
+
+        // HACK: this force n_block_data_idx_on_grid into SGPR
+        const index_t n_block_data_idx_on_grid =
+            __builtin_amdgcn_readfirstlane(block_work_idx_n * NPerBlock);
+
+        const index_t num_gemm0_m_block_outer_loop = q_grid_desc_k0_m_k1.GetLength(I1) / MPerBlock;
+        constexpr index_t num_gemm1_k_block_inner_loop = MPerBlock / Gemm1KPerBlock;
+
+        // 6 GEMM operations are categorized into 3 buckets. SizeK == SizeO == head_dim
+        // S_MNK  / dP_MNO Gemm (Gemm0 rcc)
+        // dV_NOM / dK_NKM Gemm (Gemm1 rrr)
+        // Y_MON  / dQ_MKN Gemm (Gemm2 crr)
+
+        //
+        // set up S / dP Gemm (type 1 rcc)
+        //
+
+        // Gemm0: LDS allocation for A and B: be careful of alignment
+        auto gemm0_a_block_buf = make_dynamic_buffer<AddressSpaceEnum::Lds>(
+            static_cast<GemmDataType*>(p_shared) + SharedMemTrait::a_block_space_offset,
+            Gemm0::a_block_desc_ak0_m_ak1.GetElementSpaceSize());
+
+        auto gemm0_b_block_buf = make_dynamic_buffer<AddressSpaceEnum::Lds>(
+            static_cast<GemmDataType*>(p_shared) + SharedMemTrait::b_block_space_offset,
+            Gemm0::b_block_desc_bk0_n_bk1.GetElementSpaceSize());
+
+        // Gemm0: gridwise GEMM pipeline
+        // Only supports LoopScheduler::Default
+        const auto gemm0_gridwise_gemm_pipeline =
+            GridwiseGemmPipeline_Selector<PipelineVer,
+                                          NumGemmKPrefetchStage,
+                                          LoopScheduler::Default>();
+        // S: A matrix blockwise copy
+        auto s_gemm_tile_q_blockwise_copy =
+            typename Gemm0::template ABlockwiseCopy<decltype(q_grid_desc_k0_m_k1)>(
+                q_grid_desc_k0_m_k1,
+                make_multi_index(0,
+                                 MPerBlock * (num_gemm0_m_block_outer_loop - 1),
+                                 0), // will loop over GemmM dimension
+                a_element_op,
+                Gemm0::a_block_desc_ak0_m_ak1,
+                make_multi_index(0, 0, 0),
+                tensor_operation::element_wise::PassThrough{});
+
+        // S: B matrix blockwise copy
+        auto s_gemm_tile_k_blockwise_copy =
+            typename Gemm0::template BBlockwiseCopy<decltype(k_grid_desc_k0_n_k1)>(
+                k_grid_desc_k0_n_k1,
+                make_multi_index(0, n_block_data_idx_on_grid, 0),
+                b_element_op,
+                Gemm0::b_block_desc_bk0_n_bk1,
+                make_multi_index(0, 0, 0),
+                tensor_operation::element_wise::PassThrough{});
+
+        // S: blockwise gemm
+        auto s_blockwise_gemm = typename Gemm0::BlockwiseGemm{}; // TransposeC
+
+        auto s_slash_p_thread_buf = s_blockwise_gemm.GetCThreadBuffer();
+
+        const auto s_gemm_tile_q_block_reset_copy_step =
+            make_multi_index(-q_grid_desc_k0_m_k1.GetLength(I0), -MPerBlock, 0);
+        const auto s_gemm_tile_k_block_reset_copy_step =
+            make_multi_index(-k_grid_desc_k0_n_k1.GetLength(I0), 0, 0);
+
+        const index_t num_k_block_main_loop = __builtin_amdgcn_readfirstlane(
+            (q_grid_desc_k0_m_k1.GetLength(I0) * q_grid_desc_k0_m_k1.GetLength(I2)) / KPerBlock);
+
+        // dP: transform input and output tensor descriptors
+        const auto ygrad_grid_desc_o0_m_o1 =
+            PGradGemmTile_M_N_O::MakeYGradGridDesc_O0_M_O1(ygrad_grid_desc_m0_o_m1);
+        const auto v_grid_desc_o0_n_o1 =
+            PGradGemmTile_M_N_O::MakeVGridDesc_O0_N_O1(v_grid_desc_n0_o_n1);
+
+        // dP: A matrix blockwise copy
+        auto pgrad_gemm_tile_ygrad_blockwise_copy =
+            typename Gemm0::template ABlockwiseCopy<decltype(ygrad_grid_desc_o0_m_o1)>(
+                ygrad_grid_desc_o0_m_o1,
+                make_multi_index(0,
+                                 MPerBlock * (num_gemm0_m_block_outer_loop - 1),
+                                 0), // will loop over GemmM dimension
+                tensor_operation::element_wise::PassThrough{},
+                Gemm0::a_block_desc_ak0_m_ak1,
+                make_multi_index(0, 0, 0),
+                tensor_operation::element_wise::PassThrough{});
+
+        // dP: B matrix blockwise copy
+        auto pgrad_gemm_tile_v_blockwise_copy =
+            typename Gemm0::template BBlockwiseCopy<decltype(v_grid_desc_o0_n_o1)>(
+                v_grid_desc_o0_n_o1,
+                make_multi_index(0, n_block_data_idx_on_grid, 0),
+                tensor_operation::element_wise::PassThrough{},
+                Gemm0::b_block_desc_bk0_n_bk1,
+                make_multi_index(0, 0, 0),
+                tensor_operation::element_wise::PassThrough{});
+
+        // dP: blockwise gemm
+        // we need separate blockwise gemm object because we need separate thread buffer
+        auto pgrad_blockwise_gemm = typename Gemm0::BlockwiseGemm{};
+
+        auto pgrad_thread_buf = pgrad_blockwise_gemm.GetCThreadBuffer();
+
+        const auto pgrad_gemm_tile_ygrad_block_reset_copy_step =
+            make_multi_index(-ygrad_grid_desc_o0_m_o1.GetLength(I0), -MPerBlock, 0);
+        const auto pgrad_gemm_tile_v_block_reset_copy_step =
+            make_multi_index(-v_grid_desc_o0_n_o1.GetLength(I0), 0, 0);
+
+        const index_t num_o_block_main_loop = __builtin_amdgcn_readfirstlane(
+            (ygrad_grid_desc_o0_m_o1.GetLength(I0) * ygrad_grid_desc_o0_m_o1.GetLength(I2)) /
+            KPerBlock);
+
+        //
+        // set up dV / dK Gemm (type 2 rrr)
+        //
+        using Gemm1 =
+            Gemm1<decltype(s_blockwise_gemm.GetCThreadDescriptor_M0_N0_M1_N1_M2_M3_M4_N2()),
+                  decltype(s_blockwise_gemm.GetCBlockDescriptor_M0_N0_M1_N1_M2_M3_M4_N2())>;
+
+        // Gemm1: VGPR allocation for A and LDS allocation for B
+        auto gemm1_a_thread_buf = make_static_buffer<AddressSpaceEnum::Vgpr, GemmDataType>(
+            Gemm1::a_thread_desc_k0_m_k1.GetElementSpaceSize());
+
+        auto gemm1_b_block_buf = make_dynamic_buffer<AddressSpaceEnum::Lds>(
+            static_cast<GemmDataType*>(p_shared) + SharedMemTrait::b1_block_space_offset,
+            Gemm1::b_block_desc_bk0_n_bk1.GetElementSpaceSize());
+
+        // dV: A matrix blockwise copy
+        auto vgrad_gemm_tile_p_blockwise_copy =
+            typename Gemm1::template ABlockwiseCopy<tensor_operation::element_wise::Relu>{
+                tensor_operation::element_wise::Relu{}}; // relu(P-dropped)
+
+        // dV: B matrix blockwise copy
+        auto vgrad_gemm_tile_ygrad_blockwise_copy =
+            typename Gemm1::template BBlockwiseCopy<decltype(ygrad_grid_desc_m0_o_m1)>(
+                ygrad_grid_desc_m0_o_m1,
+                make_multi_index(MPerBlock / B1K1 * (num_gemm0_m_block_outer_loop - 1), 0, 0),
+                b1_element_op,
+                Gemm1::b_block_desc_bk0_n_bk1, // there n actually is k, k is N, so name can be
+                                               // b_block_desc_bn0_k_bn1
+                make_multi_index(0, 0, 0),
+                tensor_operation::element_wise::PassThrough{});
+
+        const auto vgrad_gemm_tile_ygrad_block_next_copy_step =
+            make_multi_index(-2 * MPerBlock / B1K1, 0, 0);
+
+        // dV: blockwise gemm
+        auto vgrad_blockwise_gemm =
+            typename Gemm1::BlockwiseGemm{make_tuple(0, 0, 0, 0)}; // A_origin
+
+        auto vgrad_thread_buf = vgrad_blockwise_gemm.GetCThreadBuffer();
+
+        // dV: transform input and output tensor descriptors
+        auto vgrad_grid_desc_nblock_nperblock_oblock_operblock =
+            MakeVGradGridDesc_NBlock_NPerBlock_OBlock_OPerBlock(v_grid_desc_n0_o_n1);
+
+        // dK: transform input and output tensor descriptors
+        const auto q_grid_desc_m0_k_m1 =
+            KGradGemmTile_N_K_M::MakeQGridDesc_M0_K_M1(q_grid_desc_k0_m_k1);
+
+        // dK: A matrix blockwise copy
+        auto kgrad_gemm_tile_sgrad_blockwise_copy =
+            typename Gemm1::template ABlockwiseCopy<tensor_operation::element_wise::PassThrough>{
+                tensor_operation::element_wise::PassThrough{}};
+
+        // dK: B matrix blockwise copy
+        auto kgrad_gemm_tile_q_blockwise_copy =
+            typename Gemm1::template BBlockwiseCopy<decltype(q_grid_desc_m0_k_m1)>(
+                q_grid_desc_m0_k_m1,
+                make_multi_index(MPerBlock / B1K1 * (num_gemm0_m_block_outer_loop - 1), 0, 0),
+                b1_element_op,
+                Gemm1::b_block_desc_bk0_n_bk1, // there n actually is k, k is N, so name can be
+                                               // b_block_desc_bn0_k_bn1
+                make_multi_index(0, 0, 0),
+                tensor_operation::element_wise::PassThrough{});
+
+        const auto kgrad_gemm_tile_q_block_next_copy_step =
+            make_multi_index(-2 * MPerBlock / B1K1, 0, 0);
+
+        // dK: blockwise gemm
+        auto kgrad_blockwise_gemm =
+            typename Gemm1::BlockwiseGemm{make_tuple(0, 0, 0, 0)}; // A_origin
+
+        auto kgrad_thread_buf = kgrad_blockwise_gemm.GetCThreadBuffer();
+
+        // dK: transform input and output tensor descriptors
+        auto kgrad_grid_desc_nblock_nperblock_oblock_operblock =
+            MakeKGradGridDesc_NBlock_NPerBlock_OBlock_OPerBlock(k_grid_desc_k0_n_k1);
+
+        //
+        // set up dQ Gemm (type 3 crr)
+        //
+        using Gemm2 = Gemm2<Gemm2Params, decltype(pgrad_blockwise_gemm)>;
+
+        // Gemm2: LDS allocation for A and B: be careful of alignment
+        auto gemm2_a_block_buf = make_dynamic_buffer<AddressSpaceEnum::Lds>(
+            static_cast<GemmDataType*>(p_shared) + SharedMemTrait::a2_block_space_offset,
+            Gemm2::a_block_desc_k0_m_k1.GetElementSpaceSize());
+
+        auto gemm2_b_block_buf = make_dynamic_buffer<AddressSpaceEnum::Lds>(
+            static_cast<GemmDataType*>(p_shared) + SharedMemTrait::b2_block_space_offset,
+            Gemm2::b_block_desc_k0_n_k1.GetElementSpaceSize());
+
+        // // dQ: transform input and output tensor descriptors
+        // const auto vgrad_grid_desc_n0_o0_n1_o1_n2_o2_o3_o4 =
+        //     Gemm2::MakeCGridDesc_N0_O0_N1_O1_N2_O2_O3_O4(vgrad_grid_desc_n_o);
+        // dQ: transform input and output tensor descriptors
+        const auto k_grid_desc_n0_k_n1 =
+            QGradGemmTile_M_K_N::MakeKGridDesc_N0_K_N1(k_grid_desc_k0_n_k1);
+
+        // dQ: A matrix VGPR-to-LDS blockwise copy
+        auto qgrad_gemm_tile_sgrad_thread_copy_vgpr_to_lds =
+            typename Gemm2::template ABlockwiseCopy<tensor_operation::element_wise::PassThrough>{
+                Gemm2::a_block_desc_m0_k0_m1_k1_m2_m3_m4_k2,
+                Gemm2::MakeAThreadOriginOnBlock_M0_K0_M1_K1_M2_M3_M4_K2(),
+                tensor_operation::element_wise::PassThrough{}};
+
+        // dQ: B matrix global-to-LDS blockwise copy
+        auto qgrad_gemm_tile_k_blockwise_copy =
+            typename Gemm2::template BBlockwiseCopy<decltype(k_grid_desc_n0_k_n1)>(
+                k_grid_desc_n0_k_n1,
+                make_multi_index(n_block_data_idx_on_grid / Gemm2Params::B_K1, 0, 0),
+                tensor_operation::element_wise::PassThrough{},
+                Gemm2::b_block_desc_k0_n_k1,
+                make_multi_index(0, 0, 0),
+                tensor_operation::element_wise::PassThrough{});
+
+        // dQ: blockwise gemm
+        auto qgrad_blockwise_gemm = typename Gemm2::BlockwiseGemm{};
+
+        auto qgrad_thread_buf = qgrad_blockwise_gemm.GetCThreadBuffer();
+
+        // dQ: transform output tensor descriptors
+        const auto qgrad_grid_desc_m_k = MakeQGradGridDesc_M_K(q_grid_desc_k0_m_k1);
+        const auto qgrad_grid_desc_m0_o0_m1_o1_m2_o2_o3_o4 =
+            Gemm2::MakeCGridDesc_M0_N0_M1_N1_M2_N2_N3_N4(qgrad_grid_desc_m_k);
+
+        // dQ: C VGPR-to-global copy
+        const auto qgrad_thread_origin_on_grid_m0_o0_m1_o1_m2_o2_o3_o4 =
+            Gemm2::GetCThreadOriginOnBlock_M0_N0_M1_N1_M2_N2_N3_N4() +
+            make_multi_index((num_gemm0_m_block_outer_loop - 1) * Gemm2Params::GemmMRepeat,
+                             I0,
+                             I0,
+                             I0,
+                             I0,
+                             I0,
+                             I0,
+                             I0);
+        ;
+
+        auto qgrad_thread_copy_vgpr_to_global = typename Gemm2::template CBlockwiseCopy<
+            decltype(qgrad_grid_desc_m0_o0_m1_o1_m2_o2_o3_o4),
+            decltype(scale_rp_dropout)>(qgrad_grid_desc_m0_o0_m1_o1_m2_o2_o3_o4,
+                                        qgrad_thread_origin_on_grid_m0_o0_m1_o1_m2_o2_o3_o4,
+                                        scale_rp_dropout);
+
+        //
+        // Blockwise softmax
+        //
+        // get acc0 8D thread cluster
+        constexpr auto thread_cluster_m0_n0_m1_n1_m2_m3_m4_n2 =
+            s_blockwise_gemm.GetCBlockDescriptor_M0_N0_M1_N1_M2_M3_M4_N2().GetLengths() /
+            s_blockwise_gemm.GetCThreadDescriptor_M0_N0_M1_N1_M2_M3_M4_N2().GetLengths();
+        constexpr auto tm0 = thread_cluster_m0_n0_m1_n1_m2_m3_m4_n2.At(I0);
+        constexpr auto tn0 = thread_cluster_m0_n0_m1_n1_m2_m3_m4_n2.At(I1);
+        constexpr auto tm1 = thread_cluster_m0_n0_m1_n1_m2_m3_m4_n2.At(I2);
+        constexpr auto tn1 = thread_cluster_m0_n0_m1_n1_m2_m3_m4_n2.At(I3);
+        constexpr auto tm2 = thread_cluster_m0_n0_m1_n1_m2_m3_m4_n2.At(I4);
+        constexpr auto tm3 = thread_cluster_m0_n0_m1_n1_m2_m3_m4_n2.At(I5);
+        constexpr auto tm4 = thread_cluster_m0_n0_m1_n1_m2_m3_m4_n2.At(I6);
+        constexpr auto tn2 = thread_cluster_m0_n0_m1_n1_m2_m3_m4_n2.At(I7);
+
+        // get acc0 thread map
+        constexpr auto n0_m_n1_to_m_n_adaptor = make_single_stage_tensor_adaptor(
+            make_tuple(make_unmerge_transform(make_tuple(tn0 * tn1, tn2)),
+                       make_pass_through_transform(I1)),
+            make_tuple(Sequence<1>{}, Sequence<0>{}),
+            make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
+        constexpr auto threadid_to_n0_m_n1_adaptor = make_single_stage_tensor_adaptor(
+            make_tuple(
+                make_merge_transform(make_tuple(tn0 * tn1, tm0 * tm1 * tm2 * tm3 * tm4, tn2))),
+            make_tuple(Sequence<0, 1, 2>{}),
+            make_tuple(Sequence<0>{}));
+        const auto threadid_to_m_n_thread_cluster_adaptor =
+            chain_tensor_adaptors(n0_m_n1_to_m_n_adaptor, threadid_to_n0_m_n1_adaptor);
+
+        // get acc0 2D thread cluster & 2D thread slice
+        constexpr auto thread_desc_m0_n0_m1_n1_m2_m3_m4_n2 =
+            s_blockwise_gemm.GetCThreadDescriptor_M0_N0_M1_N1_M2_M3_M4_N2();
+        constexpr auto m0 = thread_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I0);
+        constexpr auto n0 = thread_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I1);
+        constexpr auto m1 = thread_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I2);
+        constexpr auto n1 = thread_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I3);
+        constexpr auto m2 = thread_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I4);
+        constexpr auto m3 = thread_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I5);
+        constexpr auto m4 = thread_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I6);
+        constexpr auto n2 = thread_desc_m0_n0_m1_n1_m2_m3_m4_n2.GetLength(I7);
+
+        constexpr auto thread_cluster_desc_m_n = make_naive_tensor_descriptor_packed(
+            make_tuple(tm0 * tm1 * tm2 * tm3 * tm4, tn0 * tn1 * tn2));
+        constexpr auto thread_slice_desc_m_n =
+            make_naive_tensor_descriptor_packed(make_tuple(m0 * m1 * m2 * m3 * m4, n0 * n1 * n2));
+
+        auto blockwise_softmax = BlockwiseSoftmax<BlockSize,
+                                                  FloatGemmAcc,
+                                                  decltype(threadid_to_m_n_thread_cluster_adaptor),
+                                                  decltype(thread_cluster_desc_m_n),
+                                                  decltype(thread_slice_desc_m_n)>{};
+
+        auto blockwise_dropout = BlockwiseDropout<FloatGemmAcc, decltype(thread_slice_desc_m_n)>{
+            p_dropout_in_16bits, rp_dropout};
+
+        auto lse_grid_desc_mb_m0_m1_m2_m3_m4 =
+            MakeLSEGridDescriptor_MB_M0_M1_M2_M3_M4<decltype(s_blockwise_gemm)>(lse_grid_desc_m);
+
+        constexpr auto lse_thread_desc_mb_m0_m1_m2_m3_m4 =
+            make_naive_tensor_descriptor_packed(make_tuple(I1, m0, m1, m2, m3, m4));
+
+        auto lse_thread_buf = make_static_buffer<AddressSpaceEnum::Vgpr, FloatLSE>(
+            lse_thread_desc_mb_m0_m1_m2_m3_m4.GetElementSpaceSize());
+
+        auto acc0_thread_origin = s_blockwise_gemm.CalculateCThreadOriginDataIndex8D(
+            Number<0>{}, Number<0>{}, Number<0>{}, Number<0>{});
+
+        auto lse_thread_copy_global_to_vgpr =
+            ThreadwiseTensorSliceTransfer_v2<FloatLSE,
+                                             FloatLSE,
+                                             decltype(lse_grid_desc_mb_m0_m1_m2_m3_m4),
+                                             decltype(lse_thread_desc_mb_m0_m1_m2_m3_m4),
+                                             Sequence<1, m0, m1, m2, m3, m4>,
+                                             Sequence<0, 1, 2, 3, 4, 5>,
+                                             5,
+                                             1,
+                                             1,
+                                             true /* ResetCoordAfterRun */>{
+                lse_grid_desc_mb_m0_m1_m2_m3_m4,
+                make_multi_index(num_gemm0_m_block_outer_loop - 1, // mblock
+                                 acc0_thread_origin[I0],           // mrepeat
+                                 acc0_thread_origin[I2],           // mwave
+                                 acc0_thread_origin[I4],           // mperxdl
+                                 acc0_thread_origin[I5],
+                                 acc0_thread_origin[I6])};
+
+        //
+        // z vgpr copy to global
+        //
+        // z matrix threadwise desc
+        constexpr auto z_thread_desc_m0_n0_m1_n1_m2_n2_m3_n3_n4_n5 =
+            make_naive_tensor_descriptor_packed(make_tuple(I1,   // MBlockId
+                                                           I1,   // NBlockID
+                                                           m0,   // MRepeat
+                                                           I1,   // NRepeat
+                                                           m1,   // MWaveId
+                                                           n1,   // NWaveId
+                                                           m2,   // MPerXdl
+                                                           m3,   // NGroupNum
+                                                           m4,   // NInputNum
+                                                           n2)); // registerNum
+
+        StaticBuffer<AddressSpaceEnum::Vgpr,
+                     unsigned short,
+                     z_thread_desc_m0_n0_m1_n1_m2_n2_m3_n3_n4_n5.GetElementSpaceSize(),
+                     true>
+            z_tenor_buffer;
+        z_tenor_buffer.Clear();
+        // z matrix global desc
+        /*const auto M = q_grid_desc_k0_m_k1.GetLength(I1);
+        const auto N = k_grid_desc_k0_n_k1.GetLength(I1);
+
+        auto z_grid_desc_m0_n0_m1_n1_m2_n2_m3_n3_n4_n5 =
+            MakeZGridDescriptor_M0_N0_M1_N1_M2_N2_M3_N3_N4_N5(M, N);*/
+
+        auto z_grid_buf = make_dynamic_buffer<AddressSpaceEnum::Global>(
+            p_z_grid, z_grid_desc_m0_n0_m1_n1_m2_n2_m3_n3_n4_n5.GetElementSpaceSize());
+
+        const auto wave_id     = GetGemm0WaveIdx();
+        const auto wave_m_n_id = GetGemm0WaveMNIdx(wave_id[I2]); // I2: 0~63
+
+        auto z_thread_copy_vgpr_to_global = ThreadwiseTensorSliceTransfer_v1r3<
+            ushort,
+            ZDataType,
+            decltype(z_thread_desc_m0_n0_m1_n1_m2_n2_m3_n3_n4_n5),
+            decltype(z_grid_desc_m0_n0_m1_n1_m2_n2_m3_n3_n4_n5),
+            tensor_operation::element_wise::PassThrough,
+            Sequence<I1, // MBlockId
+                     I1, // NBlockID
+                     m0, // MRepeat
+                     I1, // NRepeat
+                     m1, // MWaveId
+                     n1, // NWaveId
+                     m2, // MPerXdl
+                     m3, // NGroupNum
+                     m4, // NInputNum
+                     n2>,
+            Sequence<0, 1, 2, 3, 4, 5, 6, 7, 8, 9>,
+            9, // DstVectorDim
+            1, // DstScalarPerVector
+            InMemoryDataOperationEnum::Set,
+            1, // DstScalarStrideInVector
+            true>{z_grid_desc_m0_n0_m1_n1_m2_n2_m3_n3_n4_n5,
+                  make_multi_index(block_work_idx_n, // MBlockId
+                                   0,                // NBlockId
+                                   0,                // mrepeat
+                                   0,                // nrepeat
+                                   wave_id[I0],      // MWaveId
+                                   wave_id[I1],      // NWaveId
+                                   wave_m_n_id[I1],  // MPerXdl
+                                   0,                // group
+                                   wave_m_n_id[I0],  // NInputIndex
+                                   0),
+                  tensor_operation::element_wise::PassThrough{}};
+
+        //
+        // set up Y dot dY
+        //
+
+        // m0, n0 are m/n repeat per wave
+        // m1, n1 are number of waves
+        constexpr auto p_block_lengths =
+            s_blockwise_gemm.GetCBlockDescriptor_M0_N0_M1_N1_M2_M3_M4_N2().GetLengths();
+        constexpr auto P_M0 = p_block_lengths[I0]; // repeats
+        constexpr auto P_M1 = p_block_lengths[I2]; // waves
+        constexpr auto P_M2 = p_block_lengths[I4]; // xdl
+        constexpr auto P_M3 = p_block_lengths[I5];
+        constexpr auto P_M4 = p_block_lengths[I6];
+
+        constexpr auto y_thread_desc_m0_m1_o0_o1 = make_naive_tensor_descriptor_packed(make_tuple(
+            I1, YDotYGrad_M_O::ThreadSliceLength_M, I1, YDotYGrad_M_O::ThreadSliceLength_O));
+        constexpr auto y_thread_cluster_desc =
+            make_cluster_descriptor(Sequence<I1,
+                                             YDotYGrad_M_O::ThreadClusterLength_M,
+                                             I1,
+                                             YDotYGrad_M_O::ThreadClusterLength_O>{},
+                                    Sequence<0, 1, 2, 3>{});
+        const auto y_thread_cluster_idx =
+            y_thread_cluster_desc.CalculateBottomIndex(make_multi_index(get_thread_local_1d_id()));
+
+        const auto y_thread_data_on_block_idx =
+            y_thread_cluster_idx * y_thread_desc_m0_m1_o0_o1.GetLengths();
+        const auto y_thread_data_on_grid_idx =
+            make_multi_index(num_gemm0_m_block_outer_loop - 1, I0, I0, I0) +
+            y_thread_data_on_block_idx;
+
+        // performs double duty for both y and ygrad
+        auto yygrad_threadwise_copy = ThreadwiseTensorSliceTransfer_v2<
+            InputDataType,
+            FloatGemmAcc,
+            YGridDescriptor_MBlock_MPerBlock_OBlock_OPerBlock,
+            decltype(y_thread_desc_m0_m1_o0_o1),
+            decltype(y_thread_desc_m0_m1_o0_o1.GetLengths()),
+            Sequence<0, 1, 2, 3>,
+            3,                                 // SrcVectorDim
+            YDotYGrad_M_O::SrcScalarPerVector, // SrcScalarPerVector
+            1,                                 // SrcScalarStrideInVector
+            true /* ResetCoordAfterRun */,
+            false /* InvalidElementAsNaN */>(y_grid_desc_mblock_mperblock_oblock_operblock,
+                                             y_thread_data_on_grid_idx);
+
+        auto y_thread_buf                 = typename YDotYGrad_M_O::SrcBufType{};
+        auto ygrad_thread_buf             = typename YDotYGrad_M_O::SrcBufType{};
+        auto y_dot_ygrad_thread_accum_buf = typename YDotYGrad_M_O::DstBufType{};
+        auto y_dot_ygrad_block_accum_buf  = make_dynamic_buffer<AddressSpaceEnum::Lds>(
+            static_cast<FloatGemmAcc*>(p_shared), MPerBlock);
+
+        constexpr auto y_dot_ygrad_block_desc_mb_m0_m1_m2_m3_m4 =
+            make_naive_tensor_descriptor_packed(make_tuple(I1, P_M0, P_M1, P_M2, P_M3, P_M4));
+        constexpr auto y_dot_ygrad_thread_desc_mb_m0_m1_m2_m3_m4 =
+            lse_thread_desc_mb_m0_m1_m2_m3_m4; // reuse LSE thread descriptor because
+                                               // per-thread LSE data and y_dot_ygrad is
+                                               // tiled the same way
+
+        auto y_dot_ygrad_thread_copy_lds_to_vgpr =
+            ThreadwiseTensorSliceTransfer_v2<FloatGemmAcc,
+                                             FloatGemmAcc,
+                                             decltype(y_dot_ygrad_block_desc_mb_m0_m1_m2_m3_m4),
+                                             decltype(y_dot_ygrad_thread_desc_mb_m0_m1_m2_m3_m4),
+                                             Sequence<1, m0, m1, m2, m3, m4>,
+                                             Sequence<0, 1, 2, 3, 4, 5>,
+                                             5,
+                                             1,
+                                             1,
+                                             true /* ResetCoordAfterRun */>{
+                y_dot_ygrad_block_desc_mb_m0_m1_m2_m3_m4,
+                make_multi_index(I0,                     // mblock
+                                 acc0_thread_origin[I0], // mrepeat
+                                 acc0_thread_origin[I2], // mwave
+                                 acc0_thread_origin[I4], // mperxdl
+                                 acc0_thread_origin[I5],
+                                 acc0_thread_origin[I6])};
+
+        auto y_dot_ygrad_thread_buf = make_static_buffer<AddressSpaceEnum::Vgpr, FloatGemmAcc>(
+            y_dot_ygrad_thread_desc_mb_m0_m1_m2_m3_m4.GetElementSpaceSize());
+
+        if constexpr(Deterministic)
+        {
+            block_sync_lds();
+        }
+
+        // Initialize dK&dV
+        kgrad_thread_buf.Clear();
+        vgrad_thread_buf.Clear();
+
+        // gemm0 M loop
+        index_t gemm0_m_block_outer_index = num_gemm0_m_block_outer_loop - 1;
+        do
+        {
+            auto m_block_data_idx_on_grid =
+                __builtin_amdgcn_readfirstlane(gemm0_m_block_outer_index * MPerBlock);
+            if(c0_matrix_mask.IsTileSkippable(
+                   m_block_data_idx_on_grid, n_block_data_idx_on_grid, MPerBlock, NPerBlock))
+            {
+                continue;
+            }
+
+            //
+            // calculate Y dot dY
+            //
+
+            // clear accum buffers
+            y_dot_ygrad_thread_accum_buf.Clear();
+            y_dot_ygrad_block_accum_buf.Clear();
+
+            yygrad_threadwise_copy.Run(y_grid_desc_mblock_mperblock_oblock_operblock,
+                                       y_grid_buf,
+                                       y_thread_desc_m0_m1_o0_o1,
+                                       make_tuple(I0, I0, I0, I0),
+                                       y_thread_buf);
+            yygrad_threadwise_copy.Run(y_grid_desc_mblock_mperblock_oblock_operblock,
+                                       ygrad_grid_buf,
+                                       y_thread_desc_m0_m1_o0_o1,
+                                       make_tuple(I0, I0, I0, I0),
+                                       ygrad_thread_buf);
+
+            static_for<0, YDotYGrad_M_O::ThreadSliceLength_M, 1>{}([&](auto iM) {
+                static_for<0, YDotYGrad_M_O::ThreadSliceLength_O, 1>{}([&](auto iO) {
+                    constexpr auto offset =
+                        y_thread_desc_m0_m1_o0_o1.CalculateOffset(make_multi_index(I0, iM, I0, iO));
+                    y_dot_ygrad_thread_accum_buf(iM) +=
+                        y_thread_buf[Number<offset>{}] * ygrad_thread_buf[Number<offset>{}];
+                });
+            });
+
+            // blockwise reduction using atomic_add
+            block_sync_lds();
+            static_for<0, YDotYGrad_M_O::ThreadSliceLength_M, 1>{}([&](auto iM) {
+                const auto idx_on_block = y_thread_data_on_block_idx[I1] + iM;
+                y_dot_ygrad_block_accum_buf.AtomicAdd(idx_on_block,
+                                                      true,
+                                                      y_dot_ygrad_thread_accum_buf[iM] *
+                                                          p_dropout); // p_dropoutD1
+            });
+            block_sync_lds();
+
+            // distribute y_dot_ygrad to threads;
+            // LDS accum buffer can be safely reused after barrier
+            y_dot_ygrad_thread_copy_lds_to_vgpr.Run(y_dot_ygrad_block_desc_mb_m0_m1_m2_m3_m4,
+                                                    y_dot_ygrad_block_accum_buf,
+                                                    y_dot_ygrad_thread_desc_mb_m0_m1_m2_m3_m4,
+                                                    make_tuple(I0, I0, I0, I0, I0, I0),
+                                                    y_dot_ygrad_thread_buf);
+
+            lse_thread_copy_global_to_vgpr.Run(lse_grid_desc_mb_m0_m1_m2_m3_m4,
+                                               lse_grid_buf,
+                                               lse_thread_desc_mb_m0_m1_m2_m3_m4,
+                                               make_tuple(I0, I0, I0, I0, I0, I0),
+                                               lse_thread_buf);
+
+            // S = Q * K^T
+            gemm0_gridwise_gemm_pipeline.template Run<HasMainKBlockLoop>(
+                q_grid_desc_k0_m_k1,
+                Gemm0::a_block_desc_ak0_m_ak1,
+                s_gemm_tile_q_blockwise_copy,
+                q_grid_buf,
+                gemm0_a_block_buf,
+                Gemm0::a_block_slice_copy_step,
+                k_grid_desc_k0_n_k1,
+                Gemm0::b_block_desc_bk0_n_bk1,
+                s_gemm_tile_k_blockwise_copy,
+                k_grid_buf,
+                gemm0_b_block_buf,
+                Gemm0::b_block_slice_copy_step,
+                s_blockwise_gemm,
+                s_slash_p_thread_buf,
+                num_k_block_main_loop);
+
+            // do MNK padding or upper triangular masking
+            if constexpr(MaskOutUpperTriangle || PadN)
+            {
+                // 8d thread_desc in thread scope
+                constexpr auto c_thread_lengths =
+                    s_blockwise_gemm.GetCThreadDescriptor_M0_N0_M1_N1_M2_M3_M4_N2().GetLengths();
+
+                // 8d block_desc in block scope
+                constexpr auto c_block_lengths =
+                    s_blockwise_gemm.GetCBlockDescriptor_M0_N0_M1_N1_M2_M3_M4_N2().GetLengths();
+
+                constexpr auto M0 = c_block_lengths[I0];
+                constexpr auto N0 = c_block_lengths[I1];
+                constexpr auto M1 = c_block_lengths[I2];
+                constexpr auto N1 = c_block_lengths[I3];
+                constexpr auto M2 = c_block_lengths[I4];
+                constexpr auto M3 = c_block_lengths[I5];
+                constexpr auto M4 = c_block_lengths[I6];
+                constexpr auto N2 = c_block_lengths[I7];
+
+                // works like multi-dimension static_for (static_ford), but provides both the linear
+                // index as well as n-d index
+                using Acc0TileIterator = SpaceFillingCurve<
+                    decltype(c_thread_lengths),
+                    typename arithmetic_sequence_gen<0, c_thread_lengths.Size(), 1>::type,
+                    typename uniform_sequence_gen<c_thread_lengths.Size(), 1>::type,
+                    false>; // SnakeCurved
+
+                constexpr auto block_idx_to_m_n_adaptor = make_single_stage_tensor_adaptor(
+                    make_tuple(make_unmerge_transform(make_tuple(M0, M1, M2, M3, M4)),
+                               make_unmerge_transform(make_tuple(N0, N1, N2))),
+                    make_tuple(Sequence<0>{}, Sequence<1>{}),
+                    make_tuple(Sequence<0, 2, 4, 5, 6>{}, Sequence<1, 3, 7>{}));
+
+                static_for<0, Acc0TileIterator::GetNumOfAccess(), 1>{}([&](auto i) {
+                    auto acc0_thread_idx = Acc0TileIterator::GetIndex(i) + acc0_thread_origin;
+                    auto m_local =
+                        block_idx_to_m_n_adaptor.CalculateBottomIndex(acc0_thread_idx)[I0];
+                    auto n_local =
+                        block_idx_to_m_n_adaptor.CalculateBottomIndex(acc0_thread_idx)[I1];
+                    auto m_global = m_local + m_block_data_idx_on_grid;
+                    auto n_global = n_local + n_block_data_idx_on_grid;
+                    if(c0_matrix_mask.IsMaskedElement(m_global, n_global))
+                    {
+                        s_slash_p_thread_buf(i) = -ck::NumericLimits<float>::Infinity();
+                    }
+                    else
+                    {
+                        s_element_op(s_slash_p_thread_buf(i), s_slash_p_thread_buf[i]);
+                    }
+                    // bool masked_flag = c0_matrix_mask.IsMaskedElement(m_global, n_global);
+                    // s_element_op(s_slash_p_thread_buf(i),
+                    //              masked_flag ? -ck::NumericLimits<float>::Infinity()
+                    //
+                });
+            }
+            else
+            {
+                static_for<0, s_slash_p_thread_buf.Size(), 1>{}([&](auto i) {
+                    s_element_op(s_slash_p_thread_buf(i), s_slash_p_thread_buf[i]);
+                });
+            }
+
+            block_sync_lds(); // wait for lds read in gemm0 blockwise gemm
+
+            // P_i: = softmax(scalar * S_i:)
+            // scaling is already performed in the preceding statements with s_element_op
+            blockwise_softmax.RunWithPreCalcStats(s_slash_p_thread_buf, lse_thread_buf);
+
+            // save z to global
+            if(p_z_grid)
+            {
+                // P_dropped
+                static_for<0, n0, 1>{}([&](auto i) {
+                    blockwise_dropout.template ApplyDropout<decltype(s_slash_p_thread_buf),
+                                                            decltype(z_tenor_buffer),
+                                                            true,
+                                                            decltype(n0),
+                                                            decltype(i)>(
+                        s_slash_p_thread_buf, ph, z_tenor_buffer);
+
+                    z_thread_copy_vgpr_to_global.Run(
+                        z_thread_desc_m0_n0_m1_n1_m2_n2_m3_n3_n4_n5,
+                        make_tuple(I0, I0, I0, I0, I0, I0, I0, I0, I0, I0),
+                        z_tenor_buffer,
+                        z_grid_desc_m0_n0_m1_n1_m2_n2_m3_n3_n4_n5,
+                        z_grid_buf);
+                    z_thread_copy_vgpr_to_global.MoveDstSliceWindow(
+                        z_grid_desc_m0_n0_m1_n1_m2_n2_m3_n3_n4_n5,
+                        make_multi_index(0, 0, 0, 1, 0, 0, 0, 0, 0, 0));
+                });
+                z_thread_copy_vgpr_to_global.MoveDstSliceWindow(
+                    z_grid_desc_m0_n0_m1_n1_m2_n2_m3_n3_n4_n5,
+                    make_multi_index(0, 0, 0, -n0.value, 0, 0, 0, 0, 0, 0));
+            }
+            else
+            {
+                ignore = z_grid_buf;
+                // P_dropped
+                blockwise_dropout.template ApplyDropout<decltype(s_slash_p_thread_buf), true>(
+                    s_slash_p_thread_buf, ph);
+            }
+
+            block_sync_lds(); // wait for gemm1 LDS read
+
+            // gemm dV
+            // dV = P_drop^T * dY
+            {
+                // TODO: explore using dynamic buffer for a1 thread buffer
+                // For a1_blockwise_copy, the goal is to satisfy pipeline requirements RunRead(),
+                // RunWrite(), and MoveSliceWindow(). But it is impossible to implement given that
+                // the A1 source buffer is static buffer holding the output of first GEMM and
+                // requires constexpr offset by design. Therefore, we pass tensor coordinate offset
+                // explicitly in Run() below.
+
+                // preload data into LDS
+                vgrad_gemm_tile_ygrad_blockwise_copy.RunRead(ygrad_grid_desc_m0_o_m1,
+                                                             ygrad_grid_buf);
+
+                vgrad_gemm_tile_ygrad_blockwise_copy.MoveSrcSliceWindow(
+                    ygrad_grid_desc_m0_o_m1, Gemm1::b_block_slice_copy_step);
+
+                block_sync_lds(); // wait for previous LDS read
+
+                vgrad_gemm_tile_ygrad_blockwise_copy.RunWrite(Gemm1::b_block_desc_bk0_n_bk1,
+                                                              gemm1_b_block_buf);
+
+                // main body
+                if constexpr(num_gemm1_k_block_inner_loop > 1)
+                {
+                    static_for<0, num_gemm1_k_block_inner_loop - 1, 1>{}([&](auto i) {
+                        vgrad_gemm_tile_p_blockwise_copy.Run(Gemm1::a_src_thread_desc_k0_m_k1,
+                                                             Gemm1::a_block_slice_copy_step * i,
+                                                             s_slash_p_thread_buf,
+                                                             Gemm1::a_thread_desc_k0_m_k1,
+                                                             make_tuple(I0, I0, I0),
+                                                             gemm1_a_thread_buf);
+                        vgrad_gemm_tile_ygrad_blockwise_copy.RunRead(ygrad_grid_desc_m0_o_m1,
+                                                                     ygrad_grid_buf);
+
+                        block_sync_lds();
+
+                        vgrad_blockwise_gemm.Run(
+                            gemm1_a_thread_buf, gemm1_b_block_buf, vgrad_thread_buf);
+
+                        block_sync_lds();
+
+                        vgrad_gemm_tile_ygrad_blockwise_copy.MoveSrcSliceWindow(
+                            ygrad_grid_desc_m0_o_m1, Gemm1::b_block_slice_copy_step);
+
+                        vgrad_gemm_tile_ygrad_blockwise_copy.RunWrite(Gemm1::b_block_desc_bk0_n_bk1,
+                                                                      gemm1_b_block_buf);
+                    });
+                }
+                // tail
+                {
+                    vgrad_gemm_tile_p_blockwise_copy.Run(
+                        Gemm1::a_src_thread_desc_k0_m_k1,
+                        Gemm1::a_block_slice_copy_step * Number<num_gemm1_k_block_inner_loop - 1>{},
+                        s_slash_p_thread_buf,
+                        Gemm1::a_thread_desc_k0_m_k1,
+                        make_tuple(I0, I0, I0),
+                        gemm1_a_thread_buf);
+
+                    block_sync_lds();
+
+                    vgrad_blockwise_gemm.Run(
+                        gemm1_a_thread_buf, gemm1_b_block_buf, vgrad_thread_buf);
+                }
+            } // end gemm dV
+
+            // gemm dP
+            block_sync_lds();
+            // dP = dY * V^T
+            // assume size K == size O so HasMainKBlockLoop is the same
+            gemm0_gridwise_gemm_pipeline.template Run<HasMainKBlockLoop>(
+                ygrad_grid_desc_o0_m_o1,
+                Gemm0::a_block_desc_ak0_m_ak1, // reuse
+                pgrad_gemm_tile_ygrad_blockwise_copy,
+                ygrad_grid_buf,
+                gemm0_a_block_buf,              // reuse
+                Gemm0::a_block_slice_copy_step, // reuse
+                v_grid_desc_o0_n_o1,
+                Gemm0::b_block_desc_bk0_n_bk1, // reuse
+                pgrad_gemm_tile_v_blockwise_copy,
+                v_grid_buf,
+                gemm0_b_block_buf,              // reuse
+                Gemm0::b_block_slice_copy_step, // reuse
+                pgrad_blockwise_gemm,
+                pgrad_thread_buf,
+                num_o_block_main_loop);
+
+            // dS = P * (dP - Y_dot_dY)
+            auto& sgrad_thread_buf = pgrad_thread_buf;
+            constexpr auto pgrad_thread_tile_iterator =
+                pgrad_blockwise_gemm.MakeCThreadTileIterator();
+            constexpr auto pgrad_thread_idx_to_m_n_adaptor =
+                pgrad_blockwise_gemm.MakeCThreadIndexAdaptor8DTo2D();
+            static_for<0, pgrad_thread_tile_iterator.GetNumOfAccess(), 1>{}([&](auto i) {
+                constexpr auto pgrad_thread_idx = pgrad_thread_tile_iterator.GetIndex(i);
+                constexpr auto m =
+                    pgrad_thread_idx_to_m_n_adaptor.CalculateBottomIndex(pgrad_thread_idx)[I0];
+                // dS and P has same thread buf layout
+                if(s_slash_p_thread_buf[i] >= 0)
+                {
+                    sgrad_thread_buf(i) =
+                        s_slash_p_thread_buf[i] *
+                        (pgrad_thread_buf[i] - y_dot_ygrad_thread_buf[Number<m>{}]);
+                }
+                else
+                {
+                    sgrad_thread_buf(i) =
+                        s_slash_p_thread_buf[i] * y_dot_ygrad_thread_buf[Number<m>{}];
+                }
+                // bool undropped_flag = s_slash_p_thread_buf[i] >= 0;
+                // sgrad_thread_buf(i) =
+                //     s_slash_p_thread_buf[i] *
+                //     (undropped_flag ? (pgrad_thread_buf[i] - y_dot_ygrad_thread_buf[Number<m>{}])
+                //                     : y_dot_ygrad_thread_buf[Number<m>{}]);
+            });
+
+            SubThreadBlock<BlockSize> gemm2_a_copy_subgroup(s_blockwise_gemm.GetWaveIdx()[I0],
+                                                            s_blockwise_gemm.GetWaveIdx()[I1]);
+
+            constexpr index_t num_gemm2_loop = NPerBlock / Gemm2Params::Sum_K;
+            static_assert(Gemm2::ASrcBlockSliceWindowIterator::GetNumOfAccess() == num_gemm2_loop,
+                          "");
+
+            // TODO: tune gemm2 pipeline
+            // gemm dQ
+            // dQ = scalar * dS * K
+            qgrad_thread_buf.Clear();
+            static_for<0, num_gemm2_loop, 1>{}([&](auto gemm2_loop_idx) { // gemm dQ
+                // load QGrad Gemm B
+                qgrad_gemm_tile_k_blockwise_copy.RunRead(k_grid_desc_n0_k_n1, k_grid_buf);
+
+                // load QGrad Gemm A
+                const auto sgrad_slice_idx =
+                    Gemm2::ASrcBlockSliceWindowIterator::GetIndexTupleOfNumber(gemm2_loop_idx);
+                constexpr auto mwave_range = make_tuple(
+                    sgrad_slice_idx[I2],
+                    sgrad_slice_idx[I2] + Gemm2Params::ABlockSliceLengths_M0_K0_M1_K1::At(I2));
+                constexpr auto nwave_range = make_tuple(
+                    sgrad_slice_idx[I3],
+                    sgrad_slice_idx[I3] + Gemm2Params::ABlockSliceLengths_M0_K0_M1_K1::At(I3));
+
+                if(gemm2_a_copy_subgroup.IsBelong(mwave_range, nwave_range))
+                {
+                    qgrad_gemm_tile_sgrad_thread_copy_vgpr_to_lds.Run(
+                        Gemm2::a_src_thread_desc_m0_n0_m1_n1_m2_m3_m4_n2,
+                        make_tuple(
+                            sgrad_slice_idx[I0], sgrad_slice_idx[I1], I0, I0, I0, I0, I0, I0),
+                        sgrad_thread_buf,
+                        Gemm2::a_block_desc_m0_k0_m1_k1_m2_m3_m4_k2,
+                        gemm2_a_block_buf);
+                }
+
+                // k slice window is moved with MoveSrcSliceWindow() since it is dynamic buffer
+                // sgrad slice window is moved by loop index
+                qgrad_gemm_tile_k_blockwise_copy.MoveSrcSliceWindow(k_grid_desc_n0_k_n1,
+                                                                    Gemm2::b_block_slice_copy_step);
+
+                block_sync_lds(); // sync before write
+                qgrad_gemm_tile_k_blockwise_copy.RunWrite(Gemm2::b_block_desc_k0_n_k1,
+                                                          gemm2_b_block_buf);
+
+                block_sync_lds(); // sync before read
+                qgrad_blockwise_gemm.Run(gemm2_a_block_buf, gemm2_b_block_buf, qgrad_thread_buf);
+            }); // end gemm dQ
+            // atomic_add dQ
+            qgrad_thread_copy_vgpr_to_global.Run(Gemm2::c_thread_desc_m0_n0_m1_n1_m2_n2_n3_n4,
+                                                 make_tuple(I0, I0, I0, I0, I0, I0, I0, I0),
+                                                 qgrad_thread_buf,
+                                                 qgrad_grid_desc_m0_o0_m1_o1_m2_o2_o3_o4,
+                                                 qgrad_grid_buf);
+
+            // gemm dK
+            // dK = scalar * dS^T * Q
+            {
+                // TODO: explore using dynamic buffer for a1 thread buffer
+                // For a1_blockwise_copy, the goal is to satisfy pipeline requirements RunRead(),
+                // RunWrite(), and MoveSliceWindow(). But it is impossible to implement given that
+                // the A1 source buffer is static buffer holding the output of first GEMM and
+                // requires constexpr offset by design. Therefore, we pass tensor coordinate offset
+                // explicitly in Run() below.
+
+                // preload data into LDS
+                kgrad_gemm_tile_q_blockwise_copy.RunRead(q_grid_desc_m0_k_m1, q_grid_buf);
+
+                kgrad_gemm_tile_q_blockwise_copy.MoveSrcSliceWindow(q_grid_desc_m0_k_m1,
+                                                                    Gemm1::b_block_slice_copy_step);
+
+                block_sync_lds(); // wait for previous LDS read
+
+                kgrad_gemm_tile_q_blockwise_copy.RunWrite(Gemm1::b_block_desc_bk0_n_bk1,
+                                                          gemm1_b_block_buf);
+
+                // main body
+                if constexpr(num_gemm1_k_block_inner_loop > 1)
+                {
+                    static_for<0, num_gemm1_k_block_inner_loop - 1, 1>{}([&](auto i) {
+                        kgrad_gemm_tile_sgrad_blockwise_copy.Run(Gemm1::a_src_thread_desc_k0_m_k1,
+                                                                 Gemm1::a_block_slice_copy_step * i,
+                                                                 sgrad_thread_buf,
+                                                                 Gemm1::a_thread_desc_k0_m_k1,
+                                                                 make_tuple(I0, I0, I0),
+                                                                 gemm1_a_thread_buf);
+                        kgrad_gemm_tile_q_blockwise_copy.RunRead(q_grid_desc_m0_k_m1, q_grid_buf);
+
+                        block_sync_lds();
+
+                        kgrad_blockwise_gemm.Run(
+                            gemm1_a_thread_buf, gemm1_b_block_buf, kgrad_thread_buf);
+
+                        block_sync_lds();
+
+                        kgrad_gemm_tile_q_blockwise_copy.MoveSrcSliceWindow(
+                            q_grid_desc_m0_k_m1, Gemm1::b_block_slice_copy_step);
+
+                        kgrad_gemm_tile_q_blockwise_copy.RunWrite(Gemm1::b_block_desc_bk0_n_bk1,
+                                                                  gemm1_b_block_buf);
+                    });
+                }
+                // tail
+                {
+                    kgrad_gemm_tile_sgrad_blockwise_copy.Run(
+                        Gemm1::a_src_thread_desc_k0_m_k1,
+                        Gemm1::a_block_slice_copy_step * Number<num_gemm1_k_block_inner_loop - 1>{},
+                        sgrad_thread_buf,
+                        Gemm1::a_thread_desc_k0_m_k1,
+                        make_tuple(I0, I0, I0),
+                        gemm1_a_thread_buf);
+
+                    block_sync_lds();
+
+                    kgrad_blockwise_gemm.Run(
+                        gemm1_a_thread_buf, gemm1_b_block_buf, kgrad_thread_buf);
+                }
+            } // end gemm dK
+
+            // move slice window
+            s_gemm_tile_q_blockwise_copy.MoveSrcSliceWindow(
+                q_grid_desc_k0_m_k1,
+                s_gemm_tile_q_block_reset_copy_step); // rewind K and step M
+            s_gemm_tile_k_blockwise_copy.MoveSrcSliceWindow(
+                k_grid_desc_k0_n_k1,
+                s_gemm_tile_k_block_reset_copy_step); // rewind K
+            pgrad_gemm_tile_ygrad_blockwise_copy.MoveSrcSliceWindow(
+                ygrad_grid_desc_o0_m_o1,
+                pgrad_gemm_tile_ygrad_block_reset_copy_step); // rewind O and step M
+            pgrad_gemm_tile_v_blockwise_copy.MoveSrcSliceWindow(
+                v_grid_desc_o0_n_o1,
+                pgrad_gemm_tile_v_block_reset_copy_step); // rewind O
+            qgrad_gemm_tile_k_blockwise_copy.MoveSrcSliceWindow(
+                k_grid_desc_n0_k_n1,
+                Gemm2::b_block_reset_copy_step); // rewind N
+            kgrad_gemm_tile_q_blockwise_copy.MoveSrcSliceWindow(
+                q_grid_desc_m0_k_m1, kgrad_gemm_tile_q_block_next_copy_step); // step M
+            vgrad_gemm_tile_ygrad_blockwise_copy.MoveSrcSliceWindow(
+                ygrad_grid_desc_m0_o_m1, vgrad_gemm_tile_ygrad_block_next_copy_step); // step M
+            qgrad_thread_copy_vgpr_to_global.MoveDstSliceWindow(
+                qgrad_grid_desc_m0_o0_m1_o1_m2_o2_o3_o4, Gemm2::c_block_slice_copy_step); // step M
+            lse_thread_copy_global_to_vgpr.MoveSrcSliceWindow(lse_grid_desc_mb_m0_m1_m2_m3_m4,
+                                                              make_multi_index(-1, 0, 0, 0, 0, 0));
+            yygrad_threadwise_copy.MoveSrcSliceWindow(y_grid_desc_mblock_mperblock_oblock_operblock,
+                                                      make_multi_index(-1, 0, 0, 0));
+
+            z_thread_copy_vgpr_to_global.MoveDstSliceWindow(
+                z_grid_desc_m0_n0_m1_n1_m2_n2_m3_n3_n4_n5,
+                make_multi_index(0, 1, 0, 0, 0, 0, 0, 0, 0, 0));
+
+        } while(0 < gemm0_m_block_outer_index--); // end j loop
+
+        // shuffle dK&dV and write
+        {
+            static_assert(NXdlPerWave % CShuffleMXdlPerWavePerShuffle == 0 &&
+                              Gemm1NXdlPerWave % CShuffleNXdlPerWavePerShuffle == 0,
+                          "wrong!");
+
+            constexpr index_t MWave = Gemm0NWaves;
+            constexpr index_t NWave = Gemm0MWaves;
+
+            // TODO: hacky, fix it!
+            // thread desc same with kgrad_blockwise_gemm
+            constexpr auto c_thread_desc_m0_n0_m1_n1_m2_n2_n3_n4 =
+                vgrad_blockwise_gemm.GetCThreadDescriptor_M0_N0_M1_N1_M2_N2_N3_N4();
+
+            // TODO: hacky, fix it!
+            // c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4_tmp is only used to get lengths
+            // block desc same with kgrad_blockwise_gemm
+            constexpr auto c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4_tmp =
+                vgrad_blockwise_gemm.GetCBlockDescriptor_M0_N0_M1_N1_M2_N2_N3_N4();
+
+            constexpr auto M0 = c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4_tmp.GetLength(I0);
+            constexpr auto N0 = c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4_tmp.GetLength(I1);
+            constexpr auto M1 = c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4_tmp.GetLength(I2);
+            constexpr auto N1 = c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4_tmp.GetLength(I3);
+            constexpr auto M2 = c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4_tmp.GetLength(I4);
+            constexpr auto N2 = c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4_tmp.GetLength(I5);
+            constexpr auto N3 = c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4_tmp.GetLength(I6);
+            constexpr auto N4 = c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4_tmp.GetLength(I7);
+
+            constexpr auto c_shuffle_block_desc_mblock_mperblock_nblock_nperblock =
+                GetCShuffleBlockDescriptor_MBlock_MPerBlock_NBlock_NPerBlock();
+
+            auto c_shuffle_block_buf = make_dynamic_buffer<AddressSpaceEnum::Lds>(
+                static_cast<FloatCShuffle*>(p_shared),
+                c_shuffle_block_desc_mblock_mperblock_nblock_nperblock.GetElementSpaceSize());
+
+            constexpr auto c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4 = transform_tensor_descriptor(
+                c_shuffle_block_desc_mblock_mperblock_nblock_nperblock,
+                make_tuple(
+                    make_freeze_transform(I0),
+                    make_unmerge_transform(make_tuple(
+                        Number<CShuffleMXdlPerWavePerShuffle>{}, // M0 (MXdlPerWave) per shuffle
+                        M1,                                      // M1 = MWave
+                        M2)),                                    // M2 = MPerXdl
+                    make_freeze_transform(I0),
+                    make_unmerge_transform(make_tuple(
+                        Number<CShuffleNXdlPerWavePerShuffle>{}, // N0 (NXdlPerWave) per shuffle
+                        N1,                                      // N1 = NWave
+                        N2,                                      // N2 * N3 * N4 = NPerXdl
+                        N3,
+                        N4))),
+                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
+                make_tuple(
+                    Sequence<>{}, Sequence<0, 2, 4>{}, Sequence<>{}, Sequence<1, 3, 5, 6, 7>{}));
+
+            // calculate origin of thread output tensor on global memory
+            //     blockwise GEMM c matrix starting index
+            // index same with kgrad_blockwise_gemm
+            const auto c_thread_mtx_on_block =
+                vgrad_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_adaptor =
+                make_single_stage_tensor_adaptor(
+                    make_tuple(make_merge_transform(make_tuple(M0, M1, M2))),
+                    make_tuple(Sequence<0, 1, 2>{}),
+                    make_tuple(Sequence<0>{}));
+
+            const auto m_thread_data_on_block_idx =
+                m_thread_data_on_block_to_m0_m1_m2_adaptor.CalculateBottomIndex(
+                    make_multi_index(m_thread_data_on_block));
+
+            const auto n_thread_data_on_block_to_n0_n1_n2_n3_n4_adaptor =
+                make_single_stage_tensor_adaptor(
+                    make_tuple(make_merge_transform(make_tuple(N0, N1, N2, N3, N4))),
+                    make_tuple(Sequence<0, 1, 2, 3, 4>{}),
+                    make_tuple(Sequence<0>{}));
+
+            const auto n_thread_data_on_block_idx =
+                n_thread_data_on_block_to_n0_n1_n2_n3_n4_adaptor.CalculateBottomIndex(
+                    make_multi_index(n_thread_data_on_block));
+
+            // shuffle: threadwise copy C from VGPR to LDS
+            auto vgrad_thread_copy_vgpr_to_lds =
+                ThreadwiseTensorSliceTransfer_v1r3<FloatGemmAcc,
+                                                   FloatCShuffle,
+                                                   decltype(c_thread_desc_m0_n0_m1_n1_m2_n2_n3_n4),
+                                                   decltype(c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4),
+                                                   SElementwiseOperation,
+                                                   Sequence<CShuffleMXdlPerWavePerShuffle,
+                                                            CShuffleNXdlPerWavePerShuffle,
+                                                            I1,
+                                                            I1,
+                                                            I1,
+                                                            N2,
+                                                            I1,
+                                                            N4>,
+                                                   Sequence<0, 1, 2, 3, 4, 5, 6, 7>,
+                                                   7,
+                                                   1,
+                                                   InMemoryDataOperationEnum::Set,
+                                                   1,
+                                                   true>{
+                    c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4,
+                    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],
+                                     n_thread_data_on_block_idx[I2],
+                                     n_thread_data_on_block_idx[I3],
+                                     n_thread_data_on_block_idx[I4]),
+                    tensor_operation::element_wise::Scale{rp_dropout}};
+
+            // shuffle: blockwise copy C from LDS to global
+            auto vgrad_shuffle_block_copy_lds_to_global = ThreadGroupTensorSliceTransfer_v6r1<
+                ThisThreadBlock,            // ThreadGroup
+                CElementwiseOperation,      // ElementwiseOperation,
+                CGlobalMemoryDataOperation, // DstInMemOp,
+                Sequence<1,
+                         CShuffleMXdlPerWavePerShuffle * MWave * MPerXdl,
+                         1,
+                         CShuffleNXdlPerWavePerShuffle * NWave * NPerXdl>, // BlockSliceLengths,
+                CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
+                Sequence<0, 1, 2, 3>, // typename ThreadClusterArrangeOrder,
+                FloatCShuffle,        // typename SrcData,
+                OutputDataType,       // typename DstData,
+                decltype(c_shuffle_block_desc_mblock_mperblock_nblock_nperblock),
+                decltype(vgrad_grid_desc_nblock_nperblock_oblock_operblock),
+                Sequence<0, 1, 2, 3>,                           // typename DimAccessOrder,
+                3,                                              // index_t VectorDim,
+                CShuffleBlockTransferScalarPerVector_NPerBlock, // index_t ScalarPerVector,
+                true,  // bool ThreadTransferSrcResetCoordinateAfterRun,
+                false> // bool ThreadTransferDstResetCoordinateAfterRun>
+                {c_shuffle_block_desc_mblock_mperblock_nblock_nperblock,
+                 make_multi_index(0, 0, 0, 0),
+                 vgrad_grid_desc_nblock_nperblock_oblock_operblock,
+                 make_multi_index(block_work_idx_n, 0, block_work_idx[I1], 0),
+                 c_element_op};
+
+            // shuffle: threadwise copy C from VGPR to LDS
+            auto kgrad_thread_copy_vgpr_to_lds =
+                ThreadwiseTensorSliceTransfer_v1r3<FloatGemmAcc,
+                                                   FloatCShuffle,
+                                                   decltype(c_thread_desc_m0_n0_m1_n1_m2_n2_n3_n4),
+                                                   decltype(c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4),
+                                                   SElementwiseOperation,
+                                                   Sequence<CShuffleMXdlPerWavePerShuffle,
+                                                            CShuffleNXdlPerWavePerShuffle,
+                                                            I1,
+                                                            I1,
+                                                            I1,
+                                                            N2,
+                                                            I1,
+                                                            N4>,
+                                                   Sequence<0, 1, 2, 3, 4, 5, 6, 7>,
+                                                   7,
+                                                   1,
+                                                   InMemoryDataOperationEnum::Set,
+                                                   1,
+                                                   true>{
+                    c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4,
+                    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],
+                                     n_thread_data_on_block_idx[I2],
+                                     n_thread_data_on_block_idx[I3],
+                                     n_thread_data_on_block_idx[I4]),
+                    scale_rp_dropout};
+
+            // shuffle: blockwise copy C from LDS to global
+            auto kgrad_shuffle_block_copy_lds_to_global = ThreadGroupTensorSliceTransfer_v6r1<
+                ThisThreadBlock,            // ThreadGroup
+                CElementwiseOperation,      // ElementwiseOperation,
+                CGlobalMemoryDataOperation, // DstInMemOp,
+                Sequence<1,
+                         CShuffleMXdlPerWavePerShuffle * MWave * MPerXdl,
+                         1,
+                         CShuffleNXdlPerWavePerShuffle * NWave * NPerXdl>, // BlockSliceLengths,
+                CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
+                Sequence<0, 1, 2, 3>, // typename ThreadClusterArrangeOrder,
+                FloatCShuffle,        // typename SrcData,
+                OutputDataType,       // typename DstData,
+                decltype(c_shuffle_block_desc_mblock_mperblock_nblock_nperblock),
+                decltype(kgrad_grid_desc_nblock_nperblock_oblock_operblock),
+                Sequence<0, 1, 2, 3>,                           // typename DimAccessOrder,
+                3,                                              // index_t VectorDim,
+                CShuffleBlockTransferScalarPerVector_NPerBlock, // index_t ScalarPerVector,
+                true,  // bool ThreadTransferSrcResetCoordinateAfterRun,
+                false> // bool ThreadTransferDstResetCoordinateAfterRun>
+                {c_shuffle_block_desc_mblock_mperblock_nblock_nperblock,
+                 make_multi_index(0, 0, 0, 0),
+                 kgrad_grid_desc_nblock_nperblock_oblock_operblock,
+                 make_multi_index(block_work_idx_n, 0, block_work_idx[I1], 0),
+                 c_element_op};
+
+            // space filling curve for threadwise C in VGPR
+            constexpr auto sfc_c_vgpr =
+                SpaceFillingCurve<Sequence<NXdlPerWave, Gemm1NXdlPerWave, 1, 1, 1, N2, 1, N4>,
+                                  Sequence<0, 1, 2, 3, 4, 5, 6, 7>,
+                                  Sequence<CShuffleMXdlPerWavePerShuffle,
+                                           CShuffleNXdlPerWavePerShuffle,
+                                           1,
+                                           1,
+                                           1,
+                                           N2,
+                                           1,
+                                           N4>>{};
+
+            // space filling curve for shuffled blockwise C in global mem
+            constexpr auto sfc_c_global =
+                SpaceFillingCurve<Sequence<1, NPerBlock, 1, Gemm1NPerBlock>,
+                                  Sequence<0, 2, 1, 3>,
+                                  Sequence<1,
+                                           CShuffleMXdlPerWavePerShuffle * MWave * MPerXdl,
+                                           1,
+                                           CShuffleNXdlPerWavePerShuffle * NWave * NPerXdl>>{};
+
+            constexpr index_t num_access = sfc_c_vgpr.GetNumOfAccess();
+
+            static_assert(num_access == sfc_c_global.GetNumOfAccess(), "wrong!");
+
+            // dK
+            static_for<0, num_access, 1>{}([&](auto access_id) {
+                // make sure it's safe to write to LDS
+                block_sync_lds();
+
+                // each thread write its data from VGPR to LDS
+                kgrad_thread_copy_vgpr_to_lds.Run(c_thread_desc_m0_n0_m1_n1_m2_n2_n3_n4,
+                                                  sfc_c_vgpr.GetIndexTupleOfNumber(access_id),
+                                                  kgrad_thread_buf,
+                                                  c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4,
+                                                  c_shuffle_block_buf);
+
+                // make sure it's safe to read from LDS
+                block_sync_lds();
+
+                // each block copy its data from LDS to global
+                kgrad_shuffle_block_copy_lds_to_global.Run(
+                    c_shuffle_block_desc_mblock_mperblock_nblock_nperblock,
+                    c_shuffle_block_buf,
+                    kgrad_grid_desc_nblock_nperblock_oblock_operblock,
+                    kgrad_grid_buf);
+
+                if constexpr(access_id < num_access - 1)
+                {
+                    constexpr auto c_global_step = sfc_c_global.GetForwardStep(access_id);
+
+                    // move on C
+                    kgrad_shuffle_block_copy_lds_to_global.MoveDstSliceWindow(
+                        kgrad_grid_desc_nblock_nperblock_oblock_operblock, c_global_step);
+                }
+            });
+
+            // dV
+            static_for<0, num_access, 1>{}([&](auto access_id) {
+                // make sure it's safe to write to LDS
+                block_sync_lds();
+
+                // each thread write its data from VGPR to LDS
+                vgrad_thread_copy_vgpr_to_lds.Run(c_thread_desc_m0_n0_m1_n1_m2_n2_n3_n4,
+                                                  sfc_c_vgpr.GetIndexTupleOfNumber(access_id),
+                                                  vgrad_thread_buf,
+                                                  c_block_desc_m0_n0_m1_n1_m2_n2_n3_n4,
+                                                  c_shuffle_block_buf);
+
+                // make sure it's safe to read from LDS
+                block_sync_lds();
+
+                // each block copy its data from LDS to global
+                vgrad_shuffle_block_copy_lds_to_global.Run(
+                    c_shuffle_block_desc_mblock_mperblock_nblock_nperblock,
+                    c_shuffle_block_buf,
+                    vgrad_grid_desc_nblock_nperblock_oblock_operblock,
+                    vgrad_grid_buf);
+
+                if constexpr(access_id < num_access - 1)
+                {
+                    constexpr auto c_global_step = sfc_c_global.GetForwardStep(access_id);
+
+                    // move on C
+                    vgrad_shuffle_block_copy_lds_to_global.MoveDstSliceWindow(
+                        vgrad_grid_desc_nblock_nperblock_oblock_operblock, c_global_step);
+                }
+            });
+        }
+    }
+};
+
+} // namespace ck