Bwd Data NHWC (#22)

* fix buffer_store bug
* remove obsolete kernels
* add bwd-data-v5r1-nhwc 

composable_kernel/include/kernel_algorithm/gridwise_convolution_backward_data_implicit_gemm_v2r1_nchw_kcyx_nkhw.hpp

-#ifndef CK_GRIDWISE_CONVOLUTION_BACKWARD_DATA_IMPLICIT_GEMM_V2R1_NCHW_KCYX_NKHW_HPP
-#define CK_GRIDWISE_CONVOLUTION_BACKWARD_DATA_IMPLICIT_GEMM_V2R1_NCHW_KCYX_NKHW_HPP
-
-#include "common_header.hpp"
-#include "tensor_descriptor.hpp"
-#include "tensor_descriptor_helper.hpp"
-#include "gridwise_gemm.hpp"
-
-namespace ck {
-
-// GemmM = C * YTilda * XTilda;
-// GemmN = N * HTildaSlice * WTildaSlice;
-// GemmK = K * YDot * XDot;
-template <index_t GridSize,
-          index_t BlockSize,
-          typename Float,
-          typename AccFloat,
-          typename InGlobalDesc,
-          typename WeiGlobalDesc,
-          typename OutGlobalDesc,
-          typename ConvStrides,
-          typename ConvDilations,
-          typename InLeftPads,
-          typename InRightPads,
-          index_t GemmMPerBlock,
-          index_t GemmNPerBlock,
-          index_t GemmKPerBlock,
-          index_t GemmMPerThread,
-          index_t GemmNPerThread,
-          index_t GemmKPerThread,
-          index_t GemmMLevel0Cluster,
-          index_t GemmNLevel0Cluster,
-          index_t GemmMLevel1Cluster,
-          index_t GemmNLevel1Cluster,
-          index_t GemmThreadGemmDataPerReadM,
-          index_t GemmThreadGemmDataPerReadN,
-          typename GemmABlockCopyThreadSliceLengths_GemmK_GemmM,
-          typename GemmABlockCopyThreadClusterLengths_GemmK_GemmM,
-          index_t GemmABlockCopySrcDataPerRead_GemmM,
-          index_t GemmABlockCopyDstDataPerWrite_GemmM,
-          typename GemmBBlockCopyThreadSliceLengths_GemmK_GemmN,
-          typename GemmBBlockCopyThreadClusterLengths_GemmK_GemmN,
-          index_t GemmBBlockCopySrcDataPerRead_GemmN,
-          index_t GemmBBlockCopyDstDataPerWrite_GemmN,
-          index_t GemmCThreadCopyDstDataPerWrite_GemmN1>
-struct GridwiseConvolutionBackwardDataImplicitGemm_v2r1_nchw_kcyx_nkhw
-{
-    __device__ void Run(Float* __restrict__ p_in_global,
-                        const Float* __restrict__ p_wei_global,
-                        const Float* __restrict__ p_out_global) const
-    {
-        constexpr auto in_n_c_hi_wi_global_desc  = InGlobalDesc{};
-        constexpr auto wei_k_c_y_x_global_desc   = WeiGlobalDesc{};
-        constexpr auto out_n_k_ho_wo_global_desc = OutGlobalDesc{};
-
-        constexpr index_t N  = in_n_c_hi_wi_global_desc.GetLengths()[0];
-        constexpr index_t C  = in_n_c_hi_wi_global_desc.GetLengths()[1];
-        constexpr index_t Hi = in_n_c_hi_wi_global_desc.GetLengths()[2];
-        constexpr index_t Wi = in_n_c_hi_wi_global_desc.GetLengths()[3];
-
-        constexpr index_t K  = out_n_k_ho_wo_global_desc.GetLengths()[1];
-        constexpr index_t Ho = out_n_k_ho_wo_global_desc.GetLengths()[2];
-        constexpr index_t Wo = out_n_k_ho_wo_global_desc.GetLengths()[3];
-
-        constexpr index_t Y = wei_k_c_y_x_global_desc.GetLengths()[2];
-        constexpr index_t X = wei_k_c_y_x_global_desc.GetLengths()[3];
-
-        constexpr index_t ConvStrideH = ConvStrides{}[0];
-        constexpr index_t ConvStrideW = ConvStrides{}[1];
-
-        constexpr index_t ConvDilationH = ConvDilations{}[0];
-        constexpr index_t ConvDilationW = ConvDilations{}[1];
-
-#if 0 // debug
-        // sanity-check for vectorized memory load
-        // TODO: this logic may not be correct for bwd-data
-        static_assert(
-            (Wo == 1 || (ConvStrideW == 1 || GemmCThreadCopyDstDataPerWrite_GemmN1 == 1)) &&
-                (X == 1 || ConvDilationW % GemmCThreadCopyDstDataPerWrite_GemmN1 == 0),
-            "wrong! aligment requirement for vectorized global load of input tensor will "
-            "be violated");
-#endif
-
-        constexpr index_t GcdStrideDilationH = math::gcd(ConvStrideH, ConvDilationH);
-        constexpr index_t GcdStrideDilationW = math::gcd(ConvStrideW, ConvDilationW);
-
-        constexpr index_t YTilda = ConvStrideH / GcdStrideDilationH;
-        constexpr index_t XTilda = ConvStrideW / GcdStrideDilationW;
-
-        constexpr index_t YDot = math::integer_divide_ceil(Y, YTilda);
-        constexpr index_t XDot = math::integer_divide_ceil(X, XTilda);
-
-        constexpr index_t HTilda =
-            Ho + math::integer_divide_ceil(ConvDilationH * (Y - 1), ConvStrideH);
-        constexpr index_t WTilda =
-            Wo + math::integer_divide_ceil(ConvDilationW * (X - 1), ConvStrideW);
-
-        constexpr index_t HTildaLeft = math::integer_divide_floor(
-            math::max(0, InLeftPads{}[0] - ConvDilationH * (YTilda - 1)), ConvStrides{}[0]);
-        constexpr index_t WTildaLeft = math::integer_divide_floor(
-            math::max(0, InLeftPads{}[1] - ConvDilationW * (XTilda - 1)), ConvStrides{}[1]);
-
-        constexpr index_t HTildaRight = math::min(
-            HTilda, math::integer_divide_ceil(InLeftPads{}[0] + Hi - 1, ConvStrides{}[0]) + 1);
-        constexpr index_t WTildaRight = math::min(
-            WTilda, math::integer_divide_ceil(InLeftPads{}[1] + Wi - 1, ConvStrides{}[1]) + 1);
-
-        constexpr index_t HTildaSlice = HTildaRight - HTildaLeft;
-        constexpr index_t WTildaSlice = WTildaRight - WTildaLeft;
-
-        // weight tensor
-        constexpr auto wei_k_c_ydot_ytilda_xdot_xtilda_global_desc = transform_tensor_descriptor(
-            wei_k_c_y_x_global_desc,
-            make_tuple(PassThrough<K>{},
-                       PassThrough<C>{},
-                       Embed<Y,
-                             Sequence<YDot, YTilda>,
-                             Sequence<ConvStrideH / GcdStrideDilationH, 1, 0>>{},
-                       Embed<X,
-                             Sequence<XDot, XTilda>,
-                             Sequence<ConvStrideW / GcdStrideDilationW, 1, 0>>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}, Sequence<4, 5>{}));
-
-        constexpr auto wei_gemmk_gemmm_global_desc = transform_tensor_descriptor(
-            wei_k_c_ydot_ytilda_xdot_xtilda_global_desc,
-            make_tuple(Merge<Sequence<K, YDot, XDot>>{}, Merge<Sequence<C, YTilda, XTilda>>{}),
-            make_tuple(Sequence<0, 2, 4>{}, Sequence<1, 3, 5>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}));
-
-        // output tensor
-        constexpr auto out_n_k_ydot_htilda_xdot_wtilda_global_desc = transform_tensor_descriptor(
-            out_n_k_ho_wo_global_desc,
-            make_tuple(PassThrough<N>{},
-                       PassThrough<K>{},
-                       Embed<Ho,
-                             Sequence<YDot, HTilda>,
-                             Sequence<-ConvDilationH / GcdStrideDilationH, 1, 0>>{},
-                       Embed<Wo,
-                             Sequence<XDot, WTilda>,
-                             Sequence<-ConvDilationW / GcdStrideDilationW, 1, 0>>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}, Sequence<4, 5>{}));
-
-        constexpr auto out_n_k_ydot_htildaslice_xdot_wtildaslice_global_desc =
-            transform_tensor_descriptor(
-                out_n_k_ydot_htilda_xdot_wtilda_global_desc,
-                make_tuple(PassThrough<N>{},
-                           PassThrough<K>{},
-                           PassThrough<YTilda>{},
-                           PassThrough<XTilda>{},
-                           Slice<Sequence<HTilda, WTilda>,
-                                 Sequence<HTildaLeft, WTildaLeft>,
-                                 Sequence<HTildaRight, WTildaRight>>{}),
-                make_tuple(
-                    Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<4>{}, Sequence<3, 5>{}),
-                make_tuple(
-                    Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<4>{}, Sequence<3, 5>{}));
-
-        constexpr auto out_gemmk_gemmn_global_desc =
-            transform_tensor_descriptor(out_n_k_ydot_htildaslice_xdot_wtildaslice_global_desc,
-                                        make_tuple(Merge<Sequence<K, YDot, XDot>>{},
-                                                   Merge<Sequence<N, HTildaSlice, WTildaSlice>>{}),
-                                        make_tuple(Sequence<1, 2, 4>{}, Sequence<0, 3, 5>{}),
-                                        make_tuple(Sequence<0>{}, Sequence<1>{}));
-
-#if 1 // debug
-        constexpr bool in_skip_all_out_of_bound_check = false;
-#else
-        constexpr bool in_skip_all_out_of_bound_check = true;
-#endif
-
-        // input tensor
-        constexpr auto in_n_c_hip_wip_global_desc = transform_tensor_descriptor(
-            in_n_c_hi_wi_global_desc,
-            make_tuple(
-                PassThrough<N>{},
-                PassThrough<C>{},
-                Pad<Sequence<Hi, Wi>, InLeftPads, InRightPads, in_skip_all_out_of_bound_check>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}));
-
-        constexpr index_t Hip = in_n_c_hip_wip_global_desc.GetLengths()[2];
-        constexpr index_t Wip = in_n_c_hip_wip_global_desc.GetLengths()[3];
-
-        constexpr auto in_n_c_ytilda_htilda_xtilda_wtilda_global_desc = transform_tensor_descriptor(
-            in_n_c_hip_wip_global_desc,
-            make_tuple(PassThrough<N>{},
-                       PassThrough<C>{},
-                       Embed<Hip,
-                             Sequence<YTilda, HTilda>,
-                             Sequence<ConvDilationH, ConvStrideH, 0>,
-                             in_skip_all_out_of_bound_check>{},
-                       Embed<Wip,
-                             Sequence<XTilda, WTilda>,
-                             Sequence<ConvDilationW, ConvStrideW, 0>,
-                             in_skip_all_out_of_bound_check>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}, Sequence<4, 5>{}));
-
-        constexpr auto in_n_c_ytilda_htildaslice_xtilda_wtildaslice_global_desc =
-            transform_tensor_descriptor(
-                in_n_c_ytilda_htilda_xtilda_wtilda_global_desc,
-                make_tuple(PassThrough<N>{},
-                           PassThrough<C>{},
-                           PassThrough<YTilda>{},
-                           PassThrough<XTilda>{},
-                           Slice<Sequence<HTilda, WTilda>,
-                                 Sequence<HTildaLeft, WTildaLeft>,
-                                 Sequence<HTildaRight, WTildaRight>>{}),
-                make_tuple(
-                    Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<4>{}, Sequence<3, 5>{}),
-                make_tuple(
-                    Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<4>{}, Sequence<3, 5>{}));
-
-        constexpr auto in_gemmm_gemmn_global_desc =
-            transform_tensor_descriptor(in_n_c_ytilda_htildaslice_xtilda_wtildaslice_global_desc,
-                                        make_tuple(Merge<Sequence<C, YTilda, XTilda>>{},
-                                                   Merge<Sequence<N, HTildaSlice, WTildaSlice>>{}),
-                                        make_tuple(Sequence<1, 2, 4>{}, Sequence<0, 3, 5>{}),
-                                        make_tuple(Sequence<0>{}, Sequence<1>{}));
-
-        // GEMM
-        constexpr auto gridwise_gemm =
-            GridwiseGemmTransposedANormalBNormalC_v1<GridSize,
-                                                     BlockSize,
-                                                     Float,
-                                                     AccFloat,
-                                                     decltype(wei_gemmk_gemmm_global_desc),
-                                                     decltype(out_gemmk_gemmn_global_desc),
-                                                     decltype(in_gemmm_gemmn_global_desc),
-                                                     InMemoryDataOperation::Set,
-                                                     GemmMPerBlock,
-                                                     GemmNPerBlock,
-                                                     GemmKPerBlock,
-                                                     GemmMPerThread,
-                                                     GemmNPerThread,
-                                                     GemmKPerThread,
-                                                     GemmMLevel0Cluster,
-                                                     GemmNLevel0Cluster,
-                                                     GemmMLevel1Cluster,
-                                                     GemmNLevel1Cluster,
-                                                     GemmThreadGemmDataPerReadM,
-                                                     GemmThreadGemmDataPerReadN,
-                                                     GemmABlockCopyThreadSliceLengths_GemmK_GemmM,
-                                                     GemmABlockCopyThreadClusterLengths_GemmK_GemmM,
-                                                     Sequence<0, 1>,
-                                                     Sequence<0, 1>,
-                                                     1,
-                                                     GemmABlockCopySrcDataPerRead_GemmM,
-                                                     GemmABlockCopyDstDataPerWrite_GemmM,
-                                                     GemmBBlockCopyThreadSliceLengths_GemmK_GemmN,
-                                                     GemmBBlockCopyThreadClusterLengths_GemmK_GemmN,
-                                                     Sequence<0, 1>,
-                                                     Sequence<0, 1>,
-                                                     1,
-                                                     GemmBBlockCopySrcDataPerRead_GemmN,
-                                                     GemmBBlockCopyDstDataPerWrite_GemmN,
-                                                     Sequence<0, 1, 2, 3>,
-                                                     3,
-                                                     GemmCThreadCopyDstDataPerWrite_GemmN1>{};
-
-        gridwise_gemm.Run(p_wei_global, p_out_global, p_in_global);
-    }
-};
-
-} // namespace ck
-#endif

composable_kernel/include/kernel_algorithm/gridwise_convolution_backward_data_implicit_gemm_v3r1_nchw_kcyx_nkhw.hpp

-#ifndef CK_GRIDWISE_CONVOLUTION_BACKWARD_DATA_IMPLICIT_GEMM_V3R1_NCHW_KCYX_NKHW_HPP
-#define CK_GRIDWISE_CONVOLUTION_BACKWARD_DATA_IMPLICIT_GEMM_V3R1_NCHW_KCYX_NKHW_HPP
-
-#include "common_header.hpp"
-#include "tensor_descriptor.hpp"
-#include "tensor_descriptor_helper.hpp"
-#include "gridwise_gemm.hpp"
-
-namespace ck {
-
-// Number of GEMMs: YTilda * XTilda
-// GemmM = C
-// GemmN = N * HTildaSlice * WTildaSlice
-// GemmK = K * YDotSlice * XDotSlice
-template <index_t GridSize,
-          index_t BlockSize,
-          typename Float,
-          typename AccFloat,
-          typename InGlobalDesc,
-          typename WeiGlobalDesc,
-          typename OutGlobalDesc,
-          typename ConvStrides,
-          typename ConvDilations,
-          typename InLeftPads,
-          typename InRightPads,
-          index_t GemmMPerBlock,
-          index_t GemmNPerBlock,
-          index_t GemmKPerBlock,
-          index_t GemmMPerThread,
-          index_t GemmNPerThread,
-          index_t GemmKPerThread,
-          index_t GemmMLevel0Cluster,
-          index_t GemmNLevel0Cluster,
-          index_t GemmMLevel1Cluster,
-          index_t GemmNLevel1Cluster,
-          index_t GemmThreadGemmDataPerReadM,
-          index_t GemmThreadGemmDataPerReadN,
-          typename GemmABlockCopyThreadSliceLengths_GemmK_GemmM,
-          typename GemmABlockCopyThreadClusterLengths_GemmK_GemmM,
-          index_t GemmABlockCopySrcDataPerRead_GemmM,
-          index_t GemmABlockCopyDstDataPerWrite_GemmM,
-          typename GemmBBlockCopyThreadSliceLengths_GemmK_GemmN,
-          typename GemmBBlockCopyThreadClusterLengths_GemmK_GemmN,
-          index_t GemmBBlockCopySrcDataPerRead_GemmN,
-          index_t GemmBBlockCopyDstDataPerWrite_GemmN,
-          index_t GemmCThreadCopyDstDataPerWrite_GemmN1>
-struct GridwiseConvolutionBackwardDataImplicitGemm_v3r1_nchw_kcyx_nkhw
-{
-    // this is a hack, should query this info from gridwise_gemm instead of duplicate its logic
-    __host__ __device__ static constexpr index_t GetSharedMemoryNumberOfByte()
-    {
-        constexpr index_t max_lds_align = math::lcm(GemmABlockCopyDstDataPerWrite_GemmM,
-                                                    GemmBBlockCopyDstDataPerWrite_GemmN,
-                                                    GemmThreadGemmDataPerReadM,
-                                                    GemmThreadGemmDataPerReadN);
-
-        // A matrix in LDS memory, dst of blockwise copy
-        //   be careful of LDS alignment
-        constexpr auto a_gemmk_gemmm_block_desc = make_native_tensor_descriptor_aligned(
-            Sequence<GemmKPerBlock, GemmMPerBlock>{}, Number<max_lds_align>{});
-
-        // B matrix in LDS memory, dst of blockwise copy
-        //   be careful of LDS alignment
-        constexpr auto b_gemmk_gemmn_block_desc = make_native_tensor_descriptor_aligned(
-            Sequence<GemmKPerBlock, GemmNPerBlock>{}, Number<max_lds_align>{});
-
-        // LDS allocation for A and B: be careful of alignment
-        constexpr index_t a_block_space =
-            math::integer_least_multiple(a_gemmk_gemmm_block_desc.GetElementSpace(), max_lds_align);
-
-        constexpr index_t b_block_space =
-            math::integer_least_multiple(b_gemmk_gemmn_block_desc.GetElementSpace(), max_lds_align);
-
-        return 2 * (a_block_space + b_block_space) * sizeof(Float);
-    }
-
-    __device__ void Run(Float* __restrict__ p_in_global,
-                        const Float* __restrict__ p_wei_global,
-                        const Float* __restrict__ p_out_global) const
-    {
-        constexpr auto in_n_c_hi_wi_global_desc  = InGlobalDesc{};
-        constexpr auto wei_k_c_y_x_global_desc   = WeiGlobalDesc{};
-        constexpr auto out_n_k_ho_wo_global_desc = OutGlobalDesc{};
-
-        constexpr index_t N  = in_n_c_hi_wi_global_desc.GetLengths()[0];
-        constexpr index_t C  = in_n_c_hi_wi_global_desc.GetLengths()[1];
-        constexpr index_t Hi = in_n_c_hi_wi_global_desc.GetLengths()[2];
-        constexpr index_t Wi = in_n_c_hi_wi_global_desc.GetLengths()[3];
-
-        constexpr index_t K  = out_n_k_ho_wo_global_desc.GetLengths()[1];
-        constexpr index_t Ho = out_n_k_ho_wo_global_desc.GetLengths()[2];
-        constexpr index_t Wo = out_n_k_ho_wo_global_desc.GetLengths()[3];
-
-        constexpr index_t Y = wei_k_c_y_x_global_desc.GetLengths()[2];
-        constexpr index_t X = wei_k_c_y_x_global_desc.GetLengths()[3];
-
-        constexpr index_t ConvStrideH = ConvStrides{}[0];
-        constexpr index_t ConvStrideW = ConvStrides{}[1];
-
-        constexpr index_t ConvDilationH = ConvDilations{}[0];
-        constexpr index_t ConvDilationW = ConvDilations{}[1];
-
-#if 0 // debug
-        // sanity-check for vectorized memory load
-        // TODO: this logic may not be correct for bwd-data
-        static_assert(
-            (Wo == 1 || (ConvStrideW == 1 || GemmCThreadCopyDstDataPerWrite_GemmN1 == 1)) &&
-                (X == 1 || ConvDilationW % GemmCThreadCopyDstDataPerWrite_GemmN1 == 0),
-            "wrong! aligment requirement for vectorized global load of input tensor will "
-            "be violated");
-#endif
-
-        constexpr index_t GcdStrideDilationH = math::gcd(ConvStrideH, ConvDilationH);
-        constexpr index_t GcdStrideDilationW = math::gcd(ConvStrideW, ConvDilationW);
-
-        constexpr index_t YTilda = ConvStrideH / GcdStrideDilationH;
-        constexpr index_t XTilda = ConvStrideW / GcdStrideDilationW;
-
-        constexpr index_t YDot = math::integer_divide_ceil(Y, YTilda);
-        constexpr index_t XDot = math::integer_divide_ceil(X, XTilda);
-
-        constexpr index_t HTilda =
-            Ho + math::integer_divide_ceil(ConvDilationH * (Y - 1), ConvStrideH);
-        constexpr index_t WTilda =
-            Wo + math::integer_divide_ceil(ConvDilationW * (X - 1), ConvStrideW);
-
-        constexpr index_t HTildaLeft = math::integer_divide_floor(
-            math::max(0, InLeftPads{}[0] - ConvDilationH * (YTilda - 1)), ConvStrides{}[0]);
-        constexpr index_t WTildaLeft = math::integer_divide_floor(
-            math::max(0, InLeftPads{}[1] - ConvDilationW * (XTilda - 1)), ConvStrides{}[1]);
-
-        constexpr index_t HTildaRight = math::min(
-            HTilda, math::integer_divide_ceil(InLeftPads{}[0] + Hi - 1, ConvStrides{}[0]) + 1);
-        constexpr index_t WTildaRight = math::min(
-            WTilda, math::integer_divide_ceil(InLeftPads{}[1] + Wi - 1, ConvStrides{}[1]) + 1);
-
-        constexpr index_t HTildaSlice = HTildaRight - HTildaLeft;
-        constexpr index_t WTildaSlice = WTildaRight - WTildaLeft;
-
-        constexpr bool wei_skip_all_out_of_bound_check = true;
-
-        // weight tensor
-        constexpr auto wei_k_c_ydot_ytilda_xdot_xtilda_global_desc = transform_tensor_descriptor(
-            wei_k_c_y_x_global_desc,
-            make_tuple(PassThrough<K>{},
-                       PassThrough<C>{},
-                       Embed<Y,
-                             Sequence<YDot, YTilda>,
-                             Sequence<ConvStrideH / GcdStrideDilationH, 1, 0>,
-                             wei_skip_all_out_of_bound_check>{},
-                       Embed<X,
-                             Sequence<XDot, XTilda>,
-                             Sequence<ConvStrideW / GcdStrideDilationW, 1, 0>,
-                             wei_skip_all_out_of_bound_check>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}, Sequence<4, 5>{}));
-
-#if 1 // debug
-        constexpr bool out_skip_all_out_of_bound_check = false;
-#else
-        constexpr bool out_skip_all_out_of_bound_check = true;
-#endif
-
-        // output tensor
-        constexpr auto out_n_k_ydot_htilda_xdot_wtilda_global_desc = transform_tensor_descriptor(
-            out_n_k_ho_wo_global_desc,
-            make_tuple(PassThrough<N>{},
-                       PassThrough<K>{},
-                       Embed<Ho,
-                             Sequence<YDot, HTilda>,
-                             Sequence<-ConvDilationH / GcdStrideDilationH, 1, 0>,
-                             out_skip_all_out_of_bound_check>{},
-                       Embed<Wo,
-                             Sequence<XDot, WTilda>,
-                             Sequence<-ConvDilationW / GcdStrideDilationW, 1, 0>,
-                             out_skip_all_out_of_bound_check>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}, Sequence<4, 5>{}));
-
-        constexpr auto out_n_k_ydot_htildaslice_xdot_wtildaslice_global_desc =
-            transform_tensor_descriptor(
-                out_n_k_ydot_htilda_xdot_wtilda_global_desc,
-                make_tuple(PassThrough<N>{},
-                           PassThrough<K>{},
-                           PassThrough<YTilda>{},
-                           PassThrough<XTilda>{},
-                           Slice<Sequence<HTilda, WTilda>,
-                                 Sequence<HTildaLeft, WTildaLeft>,
-                                 Sequence<HTildaRight, WTildaRight>>{}),
-                make_tuple(
-                    Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<4>{}, Sequence<3, 5>{}),
-                make_tuple(
-                    Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<4>{}, Sequence<3, 5>{}));
-
-#if 1 // debug
-        constexpr bool in_skip_all_out_of_bound_check = false;
-#else
-        constexpr bool in_skip_all_out_of_bound_check  = true;
-#endif
-
-        // input tensor
-        constexpr auto in_n_c_hip_wip_global_desc = transform_tensor_descriptor(
-            in_n_c_hi_wi_global_desc,
-            make_tuple(
-                PassThrough<N>{},
-                PassThrough<C>{},
-                Pad<Sequence<Hi, Wi>, InLeftPads, InRightPads, in_skip_all_out_of_bound_check>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}));
-
-        constexpr index_t Hip = in_n_c_hip_wip_global_desc.GetLengths()[2];
-        constexpr index_t Wip = in_n_c_hip_wip_global_desc.GetLengths()[3];
-
-        constexpr auto in_n_c_ytilda_htilda_xtilda_wtilda_global_desc = transform_tensor_descriptor(
-            in_n_c_hip_wip_global_desc,
-            make_tuple(PassThrough<N>{},
-                       PassThrough<C>{},
-                       Embed<Hip,
-                             Sequence<YTilda, HTilda>,
-                             Sequence<ConvDilationH, ConvStrideH, 0>,
-                             in_skip_all_out_of_bound_check>{},
-                       Embed<Wip,
-                             Sequence<XTilda, WTilda>,
-                             Sequence<ConvDilationW, ConvStrideW, 0>,
-                             in_skip_all_out_of_bound_check>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}, Sequence<4, 5>{}));
-
-        constexpr auto in_n_c_ytilda_htildaslice_xtilda_wtildaslice_global_desc =
-            transform_tensor_descriptor(
-                in_n_c_ytilda_htilda_xtilda_wtilda_global_desc,
-                make_tuple(PassThrough<N>{},
-                           PassThrough<C>{},
-                           PassThrough<YTilda>{},
-                           PassThrough<XTilda>{},
-                           Slice<Sequence<HTilda, WTilda>,
-                                 Sequence<HTildaLeft, WTildaLeft>,
-                                 Sequence<HTildaRight, WTildaRight>>{}),
-                make_tuple(
-                    Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<4>{}, Sequence<3, 5>{}),
-                make_tuple(
-                    Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<4>{}, Sequence<3, 5>{}));
-
-        // GEMMs
-        constexpr index_t shared_block_size = GetSharedMemoryNumberOfByte() / sizeof(Float);
-
-        __shared__ Float p_shared_block[shared_block_size];
-
-        static_for<0, YTilda, 1>{}([&](auto iYTilda_) {
-            static_for<0, XTilda, 1>{}([&](auto iXTilda_) {
-                constexpr index_t iYTilda = decltype(iYTilda_){};
-                constexpr index_t iXTilda = decltype(iXTilda_){};
-
-                constexpr index_t YDotSlice = (iYTilda + 1) * YDot <= Y ? YDot : Y % YDot;
-                constexpr index_t XDotSlice = (iXTilda + 1) * XDot <= X ? XDot : X % XDot;
-
-                // A matrix
-                constexpr auto wei_k_c_ydotslice_ytidaslice_xdotslice_xtildaslice_global_desc =
-                    transform_tensor_descriptor(
-                        wei_k_c_ydot_ytilda_xdot_xtilda_global_desc,
-                        make_tuple(PassThrough<K>{},
-                                   PassThrough<C>{},
-                                   Slice<Sequence<YDot, XDot>,
-                                         Sequence<0, 0>,
-                                         Sequence<YDotSlice, XDotSlice>>{},
-                                   Slice<Sequence<YTilda, XTilda>,
-                                         Sequence<iYTilda, iXTilda>,
-                                         Sequence<iYTilda + 1, iXTilda + 1>>{}),
-                        make_tuple(
-                            Sequence<0>{}, Sequence<1>{}, Sequence<2, 4>{}, Sequence<3, 5>{}),
-                        make_tuple(
-                            Sequence<0>{}, Sequence<1>{}, Sequence<2, 4>{}, Sequence<3, 5>{}));
-
-                constexpr auto wei_gemmk_gemmm_global_desc = transform_tensor_descriptor(
-                    wei_k_c_ydotslice_ytidaslice_xdotslice_xtildaslice_global_desc,
-                    make_tuple(Merge<Sequence<K, YDotSlice, XDotSlice>>{},
-                               Merge<Sequence<C, 1, 1>>{}),
-                    make_tuple(Sequence<0, 2, 4>{}, Sequence<1, 3, 5>{}),
-                    make_tuple(Sequence<0>{}, Sequence<1>{}));
-
-                // B matrix
-                constexpr auto out_n_k_ydotslice_htildaslice_xdotslice_wtildaslice_global_desc =
-                    transform_tensor_descriptor(
-                        out_n_k_ydot_htildaslice_xdot_wtildaslice_global_desc,
-                        make_tuple(PassThrough<N>{},
-                                   PassThrough<K>{},
-                                   PassThrough<HTildaSlice>{},
-                                   PassThrough<WTildaSlice>{},
-                                   Slice<Sequence<YDot, XDot>,
-                                         Sequence<0, 0>,
-                                         Sequence<YDotSlice, XDotSlice>>{}),
-                        make_tuple(Sequence<0>{},
-                                   Sequence<1>{},
-                                   Sequence<3>{},
-                                   Sequence<5>{},
-                                   Sequence<2, 4>{}),
-                        make_tuple(Sequence<0>{},
-                                   Sequence<1>{},
-                                   Sequence<3>{},
-                                   Sequence<5>{},
-                                   Sequence<2, 4>{}));
-
-                constexpr auto out_gemmk_gemmn_global_desc = transform_tensor_descriptor(
-                    out_n_k_ydotslice_htildaslice_xdotslice_wtildaslice_global_desc,
-                    make_tuple(Merge<Sequence<K, YDotSlice, XDotSlice>>{},
-                               Merge<Sequence<N, HTildaSlice, WTildaSlice>>{}),
-                    make_tuple(Sequence<1, 2, 4>{}, Sequence<0, 3, 5>{}),
-                    make_tuple(Sequence<0>{}, Sequence<1>{}));
-
-                // C matrix
-                constexpr auto in_n_c_ytildaslice_htildaslice_xtildaslice_wtildaslice_global_desc =
-                    transform_tensor_descriptor(
-                        in_n_c_ytilda_htildaslice_xtilda_wtildaslice_global_desc,
-                        make_tuple(PassThrough<N>{},
-                                   PassThrough<C>{},
-                                   PassThrough<HTildaSlice>{},
-                                   PassThrough<WTildaSlice>{},
-                                   Slice<Sequence<YTilda, XTilda>,
-                                         Sequence<iYTilda, iXTilda>,
-                                         Sequence<iYTilda + 1, iXTilda + 1>>{}),
-                        make_tuple(Sequence<0>{},
-                                   Sequence<1>{},
-                                   Sequence<3>{},
-                                   Sequence<5>{},
-                                   Sequence<2, 4>{}),
-                        make_tuple(Sequence<0>{},
-                                   Sequence<1>{},
-                                   Sequence<3>{},
-                                   Sequence<5>{},
-                                   Sequence<2, 4>{}));
-
-                constexpr auto in_gemmm_gemmn_global_desc = transform_tensor_descriptor(
-                    in_n_c_ytildaslice_htildaslice_xtildaslice_wtildaslice_global_desc,
-                    make_tuple(Merge<Sequence<C, 1, 1>>{},
-                               Merge<Sequence<N, HTildaSlice, WTildaSlice>>{}),
-                    make_tuple(Sequence<1, 2, 4>{}, Sequence<0, 3, 5>{}),
-                    make_tuple(Sequence<0>{}, Sequence<1>{}));
-
-                constexpr auto gridwise_gemm = GridwiseGemmTransposedANormalBNormalC_v1<
-                    GridSize,
-                    BlockSize,
-                    Float,
-                    AccFloat,
-                    decltype(wei_gemmk_gemmm_global_desc),
-                    decltype(out_gemmk_gemmn_global_desc),
-                    decltype(in_gemmm_gemmn_global_desc),
-                    InMemoryDataOperation::Set,
-                    GemmMPerBlock,
-                    GemmNPerBlock,
-                    GemmKPerBlock,
-                    GemmMPerThread,
-                    GemmNPerThread,
-                    GemmKPerThread,
-                    GemmMLevel0Cluster,
-                    GemmNLevel0Cluster,
-                    GemmMLevel1Cluster,
-                    GemmNLevel1Cluster,
-                    GemmThreadGemmDataPerReadM,
-                    GemmThreadGemmDataPerReadN,
-                    GemmABlockCopyThreadSliceLengths_GemmK_GemmM,
-                    GemmABlockCopyThreadClusterLengths_GemmK_GemmM,
-                    Sequence<0, 1>,
-                    Sequence<0, 1>,
-                    1,
-                    GemmABlockCopySrcDataPerRead_GemmM,
-                    GemmABlockCopyDstDataPerWrite_GemmM,
-                    GemmBBlockCopyThreadSliceLengths_GemmK_GemmN,
-                    GemmBBlockCopyThreadClusterLengths_GemmK_GemmN,
-                    Sequence<0, 1>,
-                    Sequence<0, 1>,
-                    1,
-                    GemmBBlockCopySrcDataPerRead_GemmN,
-                    GemmBBlockCopyDstDataPerWrite_GemmN,
-                    Sequence<0, 1, 2, 3>,
-                    3,
-                    GemmCThreadCopyDstDataPerWrite_GemmN1>{};
-
-                gridwise_gemm.Run(p_wei_global, p_out_global, p_in_global, p_shared_block);
-
-                // is synchronization necessary?
-                __syncthreads();
-            });
-        });
-    }
-};
-
-} // namespace ck
-#endif

composable_kernel/include/kernel_algorithm/gridwise_convolution_backward_data_implicit_gemm_v4r1_nchw_kcyx_nkhw.hpp

@@ -167,9 +167,6 @@ struct GridwiseConvolutionBackwardDataImplicitGemm_v4r1_nchw_kcyx_nkhw
         constexpr index_t ConvDilationH = ConvDilations{}[0];
         constexpr index_t ConvDilationW = ConvDilations{}[1];
 
-        //\todo static_assert for global vector load/store
-        // statc_assert();
-
         constexpr index_t GcdStrideDilationH = math::gcd(ConvStrideH, ConvDilationH);
         constexpr index_t GcdStrideDilationW = math::gcd(ConvStrideW, ConvDilationW);
 
@@ -179,6 +176,9 @@ struct GridwiseConvolutionBackwardDataImplicitGemm_v4r1_nchw_kcyx_nkhw
         constexpr index_t YDot = math::integer_divide_ceil(Y, YTilda);
         constexpr index_t XDot = math::integer_divide_ceil(X, XTilda);
 
+        constexpr index_t YDotSlice = (iYTilda + 1) * YDot <= Y ? YDot : Y % YDot;
+        constexpr index_t XDotSlice = (iXTilda + 1) * XDot <= X ? XDot : X % XDot;
+
         constexpr index_t HTilda =
             Ho + math::integer_divide_ceil(ConvDilationH * (Y - 1), ConvStrideH);
         constexpr index_t WTilda =
@@ -198,10 +198,10 @@ struct GridwiseConvolutionBackwardDataImplicitGemm_v4r1_nchw_kcyx_nkhw
         constexpr index_t HTildaSlice = iHTildaRight - iHTildaLeft;
         constexpr index_t WTildaSlice = iWTildaRight - iWTildaLeft;
 
+        // A matrix: weight
         // weight out-of-bound check can be skipped
         constexpr bool wei_skip_out_of_bound_check = true;
 
-        // weight tensor
         constexpr auto wei_k_c_ydot_ytilda_xdot_xtilda_global_desc = transform_tensor_descriptor(
             wei_k_c_y_x_global_desc,
             make_tuple(PassThrough<K>{},
@@ -217,15 +217,31 @@ struct GridwiseConvolutionBackwardDataImplicitGemm_v4r1_nchw_kcyx_nkhw
             make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
             make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}, Sequence<4, 5>{}));
 
+        constexpr auto wei_k_c_ydotslice_xdotslice_global_desc = transform_tensor_descriptor(
+            wei_k_c_ydot_ytilda_xdot_xtilda_global_desc,
+            make_tuple(
+                PassThrough<K>{},
+                PassThrough<C>{},
+                Slice<Sequence<YDot, XDot>, Sequence<0, 0>, Sequence<YDotSlice, XDotSlice>>{},
+                Freeze<Sequence<YTilda, XTilda>, Sequence<iYTilda, iXTilda>>{}),
+            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 4>{}, Sequence<3, 5>{}),
+            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}, Sequence<>{}));
+
+        constexpr auto wei_gemmk_gemmm_global_desc = transform_tensor_descriptor(
+            wei_k_c_ydotslice_xdotslice_global_desc,
+            make_tuple(Merge<Sequence<K, YDotSlice, XDotSlice>>{}, PassThrough<C>{}),
+            make_tuple(Sequence<0, 2, 3>{}, Sequence<1>{}),
+            make_tuple(Sequence<0>{}, Sequence<1>{}));
+
+// B matrix: output tensor
+// TODO sometimes output tensor out-of-bound check can be skipped, find out all such
+// situations
 #if !CK_EXPERIMENTAL_IMPLICIT_GEMM_BACKWARD_DATA_V4R1_OUTPUT_SKIP_OUT_OF_BOUND_CHECK
         constexpr bool out_skip_out_of_bound_check = false;
 #else
-        //\todo sometimes output tensor out-of-bound check can be skipped, find out all such
-        // situations
         constexpr bool out_skip_out_of_bound_check = true;
 #endif
 
-        // output tensor
         constexpr auto out_n_k_ydot_htilda_xdot_wtilda_global_desc = transform_tensor_descriptor(
             out_n_k_ho_wo_global_desc,
             make_tuple(PassThrough<N>{},
@@ -246,8 +262,8 @@ struct GridwiseConvolutionBackwardDataImplicitGemm_v4r1_nchw_kcyx_nkhw
                 out_n_k_ydot_htilda_xdot_wtilda_global_desc,
                 make_tuple(PassThrough<N>{},
                            PassThrough<K>{},
-                           PassThrough<YTilda>{},
-                           PassThrough<XTilda>{},
+                           PassThrough<YDot>{},
+                           PassThrough<XDot>{},
                            Slice<Sequence<HTilda, WTilda>,
                                  Sequence<iHTildaLeft, iWTildaLeft>,
                                  Sequence<iHTildaRight, iWTildaRight>>{}),
@@ -256,14 +272,35 @@ struct GridwiseConvolutionBackwardDataImplicitGemm_v4r1_nchw_kcyx_nkhw
                 make_tuple(
                     Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<4>{}, Sequence<3, 5>{}));
 
+        constexpr auto out_n_k_ydotslice_htildaslice_xdotslice_wtildaslice_global_desc =
+            transform_tensor_descriptor(
+                out_n_k_ydot_htildaslice_xdot_wtildaslice_global_desc,
+                make_tuple(
+                    PassThrough<N>{},
+                    PassThrough<K>{},
+                    PassThrough<HTildaSlice>{},
+                    PassThrough<WTildaSlice>{},
+                    Slice<Sequence<YDot, XDot>, Sequence<0, 0>, Sequence<YDotSlice, XDotSlice>>{}),
+                make_tuple(
+                    Sequence<0>{}, Sequence<1>{}, Sequence<3>{}, Sequence<5>{}, Sequence<2, 4>{}),
+                make_tuple(
+                    Sequence<0>{}, Sequence<1>{}, Sequence<3>{}, Sequence<5>{}, Sequence<2, 4>{}));
+
+        constexpr auto out_gemmk_gemmn_global_desc = transform_tensor_descriptor(
+            out_n_k_ydotslice_htildaslice_xdotslice_wtildaslice_global_desc,
+            make_tuple(Merge<Sequence<K, YDotSlice, XDotSlice>>{},
+                       Merge<Sequence<N, HTildaSlice, WTildaSlice>>{}),
+            make_tuple(Sequence<1, 2, 4>{}, Sequence<0, 3, 5>{}),
+            make_tuple(Sequence<0>{}, Sequence<1>{}));
+
+// C matrix: input tensor
+// TODO sometimes input out-of-bound check can be skipped, find out all such situations
 #if !CK_EXPERIMENTAL_IMPLICIT_GEMM_BACKWARD_DATA_V4R1_INPUT_SKIP_OUT_OF_BOUND_CHECK
         constexpr bool in_skip_out_of_bound_check = false;
 #else
-        //\todo sometimes input out-of-bound check can be skipped, find out all such situations
-        constexpr bool in_skip_out_of_bound_check = true;
+        constexpr bool in_skip_out_of_bound_check  = true;
 #endif
 
-        // input tensor
         constexpr auto in_n_c_hip_wip_global_desc = transform_tensor_descriptor(
             in_n_c_hi_wi_global_desc,
             make_tuple(
@@ -291,87 +328,21 @@ struct GridwiseConvolutionBackwardDataImplicitGemm_v4r1_nchw_kcyx_nkhw
             make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
             make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 3>{}, Sequence<4, 5>{}));
 
-        constexpr auto in_n_c_ytilda_htildaslice_xtilda_wtildaslice_global_desc =
-            transform_tensor_descriptor(
-                in_n_c_ytilda_htilda_xtilda_wtilda_global_desc,
-                make_tuple(PassThrough<N>{},
-                           PassThrough<C>{},
-                           PassThrough<YTilda>{},
-                           PassThrough<XTilda>{},
-                           Slice<Sequence<HTilda, WTilda>,
-                                 Sequence<iHTildaLeft, iWTildaLeft>,
-                                 Sequence<iHTildaRight, iWTildaRight>>{}),
-                make_tuple(
-                    Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<4>{}, Sequence<3, 5>{}),
-                make_tuple(
-                    Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<4>{}, Sequence<3, 5>{}));
-
-        // GEMM
-        constexpr index_t YDotSlice = (iYTilda + 1) * YDot <= Y ? YDot : Y % YDot;
-        constexpr index_t XDotSlice = (iXTilda + 1) * XDot <= X ? XDot : X % XDot;
-
-        // A matrix
-        constexpr auto wei_k_c_ydotslice_ytidaslice_xdotslice_xtildaslice_global_desc =
-            transform_tensor_descriptor(
-                wei_k_c_ydot_ytilda_xdot_xtilda_global_desc,
-                make_tuple(
-                    PassThrough<K>{},
-                    PassThrough<C>{},
-                    Slice<Sequence<YDot, XDot>, Sequence<0, 0>, Sequence<YDotSlice, XDotSlice>>{},
-                    Slice<Sequence<YTilda, XTilda>,
-                          Sequence<iYTilda, iXTilda>,
-                          Sequence<iYTilda + 1, iXTilda + 1>>{}),
-                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 4>{}, Sequence<3, 5>{}),
-                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 4>{}, Sequence<3, 5>{}));
-
-        constexpr auto wei_gemmk_gemmm_global_desc = transform_tensor_descriptor(
-            wei_k_c_ydotslice_ytidaslice_xdotslice_xtildaslice_global_desc,
-            make_tuple(Merge<Sequence<K, YDotSlice, XDotSlice>>{}, Merge<Sequence<C, 1, 1>>{}),
-            make_tuple(Sequence<0, 2, 4>{}, Sequence<1, 3, 5>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}));
-
-        // B matrix
-        constexpr auto out_n_k_ydotslice_htildaslice_xdotslice_wtildaslice_global_desc =
-            transform_tensor_descriptor(
-                out_n_k_ydot_htildaslice_xdot_wtildaslice_global_desc,
-                make_tuple(
-                    PassThrough<N>{},
-                    PassThrough<K>{},
-                    PassThrough<HTildaSlice>{},
-                    PassThrough<WTildaSlice>{},
-                    Slice<Sequence<YDot, XDot>, Sequence<0, 0>, Sequence<YDotSlice, XDotSlice>>{}),
-                make_tuple(
-                    Sequence<0>{}, Sequence<1>{}, Sequence<3>{}, Sequence<5>{}, Sequence<2, 4>{}),
-                make_tuple(
-                    Sequence<0>{}, Sequence<1>{}, Sequence<3>{}, Sequence<5>{}, Sequence<2, 4>{}));
-
-        constexpr auto out_gemmk_gemmn_global_desc = transform_tensor_descriptor(
-            out_n_k_ydotslice_htildaslice_xdotslice_wtildaslice_global_desc,
-            make_tuple(Merge<Sequence<K, YDotSlice, XDotSlice>>{},
-                       Merge<Sequence<N, HTildaSlice, WTildaSlice>>{}),
-            make_tuple(Sequence<1, 2, 4>{}, Sequence<0, 3, 5>{}),
-            make_tuple(Sequence<0>{}, Sequence<1>{}));
-
-        // C matrix
-        constexpr auto in_n_c_ytildaslice_htildaslice_xtildaslice_wtildaslice_global_desc =
-            transform_tensor_descriptor(
-                in_n_c_ytilda_htildaslice_xtilda_wtildaslice_global_desc,
-                make_tuple(PassThrough<N>{},
-                           PassThrough<C>{},
-                           PassThrough<HTildaSlice>{},
-                           PassThrough<WTildaSlice>{},
-                           Slice<Sequence<YTilda, XTilda>,
-                                 Sequence<iYTilda, iXTilda>,
-                                 Sequence<iYTilda + 1, iXTilda + 1>>{}),
-                make_tuple(
-                    Sequence<0>{}, Sequence<1>{}, Sequence<3>{}, Sequence<5>{}, Sequence<2, 4>{}),
-                make_tuple(
-                    Sequence<0>{}, Sequence<1>{}, Sequence<3>{}, Sequence<5>{}, Sequence<2, 4>{}));
+        constexpr auto in_n_c_htildaslice_wtildaslice_global_desc = transform_tensor_descriptor(
+            in_n_c_ytilda_htilda_xtilda_wtilda_global_desc,
+            make_tuple(PassThrough<N>{},
+                       PassThrough<C>{},
+                       Freeze<Sequence<YTilda, XTilda>, Sequence<iYTilda, iXTilda>>{},
+                       Slice<Sequence<HTilda, WTilda>,
+                             Sequence<iHTildaLeft, iWTildaLeft>,
+                             Sequence<iHTildaRight, iWTildaRight>>{}),
+            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2, 4>{}, Sequence<3, 5>{}),
+            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<>{}, Sequence<2, 3>{}));
 
         constexpr auto in_gemmm_gemmn_global_desc = transform_tensor_descriptor(
-            in_n_c_ytildaslice_htildaslice_xtildaslice_wtildaslice_global_desc,
-            make_tuple(Merge<Sequence<C, 1, 1>>{}, Merge<Sequence<N, HTildaSlice, WTildaSlice>>{}),
-            make_tuple(Sequence<1, 2, 4>{}, Sequence<0, 3, 5>{}),
+            in_n_c_htildaslice_wtildaslice_global_desc,
+            make_tuple(PassThrough<C>{}, Merge<Sequence<N, HTildaSlice, WTildaSlice>>{}),
+            make_tuple(Sequence<1>{}, Sequence<0, 2, 3>{}),
             make_tuple(Sequence<0>{}, Sequence<1>{}));
 
         constexpr auto gridwise_gemm =

composable_kernel/include/kernel_algorithm/gridwise_convolution_backward_data_implicit_gemm_v5r1_nhwc_kyxc_nhwk.hpp

+#ifndef CK_GRIDWISE_CONVOLUTION_BACKWARD_DATA_IMPLICIT_GEMM_V5R1_NHWC_KYXC_NHWK_HPP
+#define CK_GRIDWISE_CONVOLUTION_BACKWARD_DATA_IMPLICIT_GEMM_V5R1_NHWC_KYXC_NHWK_HPP
+
+#include "common_header.hpp"
+#include "tensor_descriptor.hpp"
+#include "tensor_descriptor_helper.hpp"
+#include "gridwise_gemm.hpp"
+
+namespace ck {
+
+// Number of GEMMs = YTilda * XTilda
+// GemmM  = C
+// GemmN  = N * HTildaSlice * WTildaSlice
+// GemmK0 = YDotSlice
+// GemmK1 = XDotSlice
+// GemmK2 = K
+template <index_t GridSize,
+          index_t BlockSize,
+          typename Float,
+          typename AccFloat,
+          typename InGlobalDesc,
+          typename WeiGlobalDesc,
+          typename OutGlobalDesc,
+          typename ConvStrides,
+          typename ConvDilations,
+          typename InLeftPads,
+          typename InRightPads,
+          index_t GemmMPerBlock,
+          index_t GemmNPerBlock,
+          index_t GemmKPerBlock,
+          index_t GemmMPerThread,
+          index_t GemmNPerThread,
+          index_t GemmKPerThread,
+          index_t GemmMLevel0Cluster,
+          index_t GemmNLevel0Cluster,
+          index_t GemmMLevel1Cluster,
+          index_t GemmNLevel1Cluster,
+          index_t ThreadGemmDataPerRead_GemmM,
+          index_t ThreadGemmDataPerRead_GemmN,
+          typename GemmABlockCopyThreadSliceLengths_GemmK0_GemmK1_GemmK2_GemmM,
+          typename GemmABlockCopyThreadClusterLengths_GemmK0_GemmK1_GemmK2_GemmM,
+          index_t GemmABlockCopySrcDataPerRead_GemmM,
+          index_t GemmABlockCopyDstDataPerWrite_GemmM,
+          typename GemmBBlockCopyThreadSliceLengths_GemmK0_GemmK1_GemmK2_GemmN,
+          typename GemmBBlockCopyThreadClusterLengths_GemmK0_GemmK1_GemmK2_GemmN,
+          index_t GemmBBlockCopySrcDataPerRead_GemmK2,
+          index_t GemmBBlockCopyDstDataPerWrite_GemmN,
+          index_t GemmCThreadCopyDstDataPerWrite_GemmN1>
+struct GridwiseConvolutionBackwardDataImplicitGemm_v5r1_nhwc_kyxc_nhwk
+{
+    __host__ __device__ static constexpr index_t GetNumberOfGemm()
+    {
+        constexpr index_t ConvStrideH = ConvStrides{}[0];
+        constexpr index_t ConvStrideW = ConvStrides{}[1];
+
+        constexpr index_t ConvDilationH = ConvDilations{}[0];
+        constexpr index_t ConvDilationW = ConvDilations{}[1];
+
+        constexpr index_t GcdStrideDilationH = math::gcd(ConvStrideH, ConvDilationH);
+        constexpr index_t GcdStrideDilationW = math::gcd(ConvStrideW, ConvDilationW);
+
+        constexpr index_t YTilda = ConvStrideH / GcdStrideDilationH;
+        constexpr index_t XTilda = ConvStrideW / GcdStrideDilationW;
+
+        return YTilda * XTilda;
+    }
+
+    __host__ __device__ static constexpr auto GetGemmSizeImpl(index_t iYTilda, index_t iXTilda)
+    {
+        constexpr index_t N  = InGlobalDesc::GetLengths()[0];
+        constexpr index_t Hi = InGlobalDesc::GetLengths()[1];
+        constexpr index_t Wi = InGlobalDesc::GetLengths()[2];
+        constexpr index_t C  = InGlobalDesc::GetLengths()[3];
+
+        constexpr index_t Ho = OutGlobalDesc::GetLengths()[1];
+        constexpr index_t Wo = OutGlobalDesc::GetLengths()[2];
+        constexpr index_t K  = OutGlobalDesc::GetLengths()[3];
+
+        constexpr index_t Y = WeiGlobalDesc::GetLengths()[1];
+        constexpr index_t X = WeiGlobalDesc::GetLengths()[2];
+
+        constexpr index_t ConvStrideH = ConvStrides{}[0];
+        constexpr index_t ConvStrideW = ConvStrides{}[1];
+
+        constexpr index_t ConvDilationH = ConvDilations{}[0];
+        constexpr index_t ConvDilationW = ConvDilations{}[1];
+
+        constexpr index_t GcdStrideDilationH = math::gcd(ConvStrideH, ConvDilationH);
+        constexpr index_t GcdStrideDilationW = math::gcd(ConvStrideW, ConvDilationW);
+
+        constexpr index_t YTilda = ConvStrideH / GcdStrideDilationH;
+        constexpr index_t XTilda = ConvStrideW / GcdStrideDilationW;
+
+        constexpr index_t YDot = math::integer_divide_ceil(Y, YTilda);
+        constexpr index_t XDot = math::integer_divide_ceil(X, XTilda);
+
+        constexpr index_t HTilda =
+            Ho + math::integer_divide_ceil(ConvDilationH * (Y - 1), ConvStrideH);
+        constexpr index_t WTilda =
+            Wo + math::integer_divide_ceil(ConvDilationW * (X - 1), ConvStrideW);
+
+        // only work on HTilda and WTilda that contribute to non-padding area of input tensor
+        constexpr index_t iHTildaLeft = math::integer_divide_floor(
+            math::max(0, InLeftPads{}[0] - ConvDilationH * (YTilda - 1)), ConvStrides{}[0]);
+        constexpr index_t iWTildaLeft = math::integer_divide_floor(
+            math::max(0, InLeftPads{}[1] - ConvDilationW * (XTilda - 1)), ConvStrides{}[1]);
+
+        constexpr index_t iHTildaRight = math::min(
+            HTilda, math::integer_divide_ceil(InLeftPads{}[0] + Hi - 1, ConvStrides{}[0]) + 1);
+        constexpr index_t iWTildaRight = math::min(
+            WTilda, math::integer_divide_ceil(InLeftPads{}[1] + Wi - 1, ConvStrides{}[1]) + 1);
+
+        constexpr index_t HTildaSlice = iHTildaRight - iHTildaLeft;
+        constexpr index_t WTildaSlice = iWTildaRight - iWTildaLeft;
+
+        // GemmM and GemmN
+        constexpr index_t GemmM = C;
+        constexpr index_t GemmN = N * HTildaSlice * WTildaSlice;
+
+        // GemmK is different for each GEMM
+        index_t YDotSlice = (iYTilda + 1) * YDot <= Y ? YDot : Y % YDot;
+        index_t XDotSlice = (iXTilda + 1) * XDot <= X ? XDot : X % XDot;
+
+        index_t GemmK0 = YDotSlice;
+        index_t GemmK1 = XDotSlice;
+        index_t GemmK2 = K;
+
+        return Array<index_t, 5>{GemmM, GemmN, GemmK0, GemmK1, GemmK2};
+    }
+
+    __host__ __device__ static constexpr auto GetGemmSize(index_t gemm_id)
+    {
+        constexpr index_t ConvStrideW = ConvStrides{}[1];
+
+        constexpr index_t ConvDilationW = ConvDilations{}[1];
+
+        constexpr index_t GcdStrideDilationW = math::gcd(ConvStrideW, ConvDilationW);
+
+        constexpr index_t XTilda = ConvStrideW / GcdStrideDilationW;
+
+        index_t iYTilda = gemm_id / XTilda;
+        index_t iXTilda = gemm_id % XTilda;
+
+        return GetGemmSizeImpl(iYTilda, iXTilda);
+    }
+
+    template <index_t iYTilda, index_t iXTilda>
+    __device__ static void RunImpl(Float* __restrict__ p_in_global,
+                                   const Float* __restrict__ p_wei_global,
+                                   const Float* __restrict__ p_out_global)
+    {
+        constexpr auto in_n_hi_wi_c_global_desc  = InGlobalDesc{};
+        constexpr auto wei_k_y_x_c_global_desc   = WeiGlobalDesc{};
+        constexpr auto out_n_ho_wo_k_global_desc = OutGlobalDesc{};
+
+        constexpr index_t N  = in_n_hi_wi_c_global_desc.GetLengths()[0];
+        constexpr index_t Hi = in_n_hi_wi_c_global_desc.GetLengths()[1];
+        constexpr index_t Wi = in_n_hi_wi_c_global_desc.GetLengths()[2];
+        constexpr index_t C  = in_n_hi_wi_c_global_desc.GetLengths()[3];
+
+        constexpr index_t Ho = out_n_ho_wo_k_global_desc.GetLengths()[1];
+        constexpr index_t Wo = out_n_ho_wo_k_global_desc.GetLengths()[2];
+        constexpr index_t K  = out_n_ho_wo_k_global_desc.GetLengths()[3];
+
+        constexpr index_t Y = wei_k_y_x_c_global_desc.GetLengths()[1];
+        constexpr index_t X = wei_k_y_x_c_global_desc.GetLengths()[2];
+
+        constexpr index_t ConvStrideH = ConvStrides{}[0];
+        constexpr index_t ConvStrideW = ConvStrides{}[1];
+
+        constexpr index_t ConvDilationH = ConvDilations{}[0];
+        constexpr index_t ConvDilationW = ConvDilations{}[1];
+
+        constexpr index_t GcdStrideDilationH = math::gcd(ConvStrideH, ConvDilationH);
+        constexpr index_t GcdStrideDilationW = math::gcd(ConvStrideW, ConvDilationW);
+
+        constexpr index_t YTilda = ConvStrideH / GcdStrideDilationH;
+        constexpr index_t XTilda = ConvStrideW / GcdStrideDilationW;
+
+        constexpr index_t YDot = math::integer_divide_ceil(Y, YTilda);
+        constexpr index_t XDot = math::integer_divide_ceil(X, XTilda);
+
+        constexpr index_t YDotSlice = (iYTilda + 1) * YDot <= Y ? YDot : Y % YDot;
+        constexpr index_t XDotSlice = (iXTilda + 1) * XDot <= X ? XDot : X % XDot;
+
+        constexpr index_t HTilda =
+            Ho + math::integer_divide_ceil(ConvDilationH * (Y - 1), ConvStrideH);
+        constexpr index_t WTilda =
+            Wo + math::integer_divide_ceil(ConvDilationW * (X - 1), ConvStrideW);
+
+        // only work on HTilda and WTilda that contribute to non-padding area of input tensor
+        constexpr index_t iHTildaLeft = math::integer_divide_floor(
+            math::max(0, InLeftPads{}[0] - ConvDilationH * (YTilda - 1)), ConvStrides{}[0]);
+        constexpr index_t iWTildaLeft = math::integer_divide_floor(
+            math::max(0, InLeftPads{}[1] - ConvDilationW * (XTilda - 1)), ConvStrides{}[1]);
+
+        constexpr index_t iHTildaRight = math::min(
+            HTilda, math::integer_divide_ceil(InLeftPads{}[0] + Hi - 1, ConvStrides{}[0]) + 1);
+        constexpr index_t iWTildaRight = math::min(
+            WTilda, math::integer_divide_ceil(InLeftPads{}[1] + Wi - 1, ConvStrides{}[1]) + 1);
+
+        constexpr index_t HTildaSlice = iHTildaRight - iHTildaLeft;
+        constexpr index_t WTildaSlice = iWTildaRight - iWTildaLeft;
+
+        // A matrix: weight
+        // weight out-of-bound check can be skipped
+        constexpr bool wei_skip_out_of_bound_check = true;
+
+        constexpr auto wei_k_ydot_ytilda_xdot_xtilda_c_global_desc = transform_tensor_descriptor(
+            wei_k_y_x_c_global_desc,
+            make_tuple(PassThrough<K>{},
+                       Embed<Y,
+                             Sequence<YDot, YTilda>,
+                             Sequence<ConvStrideH / GcdStrideDilationH, 1, 0>,
+                             wei_skip_out_of_bound_check>{},
+                       Embed<X,
+                             Sequence<XDot, XTilda>,
+                             Sequence<ConvStrideW / GcdStrideDilationW, 1, 0>,
+                             wei_skip_out_of_bound_check>{},
+                       PassThrough<C>{}),
+            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
+            make_tuple(Sequence<0>{}, Sequence<1, 2>{}, Sequence<3, 4>{}, Sequence<5>{}));
+
+        constexpr auto wei_k_ydotslice_xdotslice_c_global_desc = transform_tensor_descriptor(
+            wei_k_ydot_ytilda_xdot_xtilda_c_global_desc,
+            make_tuple(
+                PassThrough<K>{},
+                Slice<Sequence<YDot, XDot>, Sequence<0, 0>, Sequence<YDotSlice, XDotSlice>>{},
+                Freeze<Sequence<YTilda, XTilda>, Sequence<iYTilda, iXTilda>>{},
+                PassThrough<C>{}),
+            make_tuple(Sequence<0>{}, Sequence<1, 3>{}, Sequence<2, 4>{}, Sequence<5>{}),
+            make_tuple(Sequence<0>{}, Sequence<1, 2>{}, Sequence<>{}, Sequence<3>{}));
+
+        constexpr auto wei_gemmk0_gemmk1_gemmk2_gemmm_global_desc =
+            reorder_tensor_descriptor_given_lower2upper(wei_k_ydotslice_xdotslice_c_global_desc,
+                                                        Sequence<2, 0, 1, 3>{});
+
+// B matrix: output tensor
+// TODO sometimes output tensor out-of-bound check can be skipped, find out all such
+// situations
+#if !CK_EXPERIMENTAL_IMPLICIT_GEMM_BACKWARD_DATA_V4R1_OUTPUT_SKIP_OUT_OF_BOUND_CHECK
+        constexpr bool out_skip_out_of_bound_check = false;
+#else
+        constexpr bool out_skip_out_of_bound_check = true;
+#endif
+
+        constexpr auto out_n_ydot_htilda_xdot_wtilda_k_global_desc = transform_tensor_descriptor(
+            out_n_ho_wo_k_global_desc,
+            make_tuple(PassThrough<N>{},
+                       Embed<Ho,
+                             Sequence<YDot, HTilda>,
+                             Sequence<-ConvDilationH / GcdStrideDilationH, 1, 0>,
+                             out_skip_out_of_bound_check>{},
+                       Embed<Wo,
+                             Sequence<XDot, WTilda>,
+                             Sequence<-ConvDilationW / GcdStrideDilationW, 1, 0>,
+                             out_skip_out_of_bound_check>{},
+                       PassThrough<K>{}),
+            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
+            make_tuple(Sequence<0>{}, Sequence<1, 2>{}, Sequence<3, 4>{}, Sequence<5>{}));
+
+        constexpr auto out_n_ydotslice_htildaslice_xdotslice_wtildaslice_k_global_desc =
+            transform_tensor_descriptor(
+                out_n_ydot_htilda_xdot_wtilda_k_global_desc,
+                make_tuple(
+                    PassThrough<N>{},
+                    Slice<Sequence<YDot, XDot>, Sequence<0, 0>, Sequence<YDotSlice, XDotSlice>>{},
+                    Slice<Sequence<HTilda, WTilda>,
+                          Sequence<iHTildaLeft, iWTildaLeft>,
+                          Sequence<iHTildaRight, iWTildaRight>>{},
+                    PassThrough<K>{}),
+                make_tuple(Sequence<0>{}, Sequence<1, 3>{}, Sequence<2, 4>{}, Sequence<5>{}),
+                make_tuple(Sequence<0>{}, Sequence<1, 3>{}, Sequence<2, 4>{}, Sequence<5>{}));
+
+        constexpr auto out_gemmk0_gemmk1_gemmk2_gemmn_global_desc = transform_tensor_descriptor(
+            out_n_ydotslice_htildaslice_xdotslice_wtildaslice_k_global_desc,
+            make_tuple(PassThrough<YDotSlice>{},
+                       PassThrough<XDotSlice>{},
+                       PassThrough<K>{},
+                       Merge<Sequence<N, HTildaSlice, WTildaSlice>>{}),
+            make_tuple(Sequence<1>{}, Sequence<3>{}, Sequence<5>{}, Sequence<0, 2, 4>{}),
+            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}));
+
+// C matrix: input tensor
+// TODO sometimes input out-of-bound check can be skipped, find out all such situations
+#if !CK_EXPERIMENTAL_IMPLICIT_GEMM_BACKWARD_DATA_V4R1_INPUT_SKIP_OUT_OF_BOUND_CHECK
+        constexpr bool in_skip_out_of_bound_check = false;
+#else
+        constexpr bool in_skip_out_of_bound_check  = true;
+#endif
+
+        constexpr auto in_n_hip_wip_c_global_desc = transform_tensor_descriptor(
+            in_n_hi_wi_c_global_desc,
+            make_tuple(PassThrough<N>{},
+                       Pad<Sequence<Hi, Wi>, InLeftPads, InRightPads, in_skip_out_of_bound_check>{},
+                       PassThrough<C>{}),
+            make_tuple(Sequence<0>{}, Sequence<1, 2>{}, Sequence<3>{}),
+            make_tuple(Sequence<0>{}, Sequence<1, 2>{}, Sequence<3>{}));
+
+        constexpr index_t Hip = in_n_hip_wip_c_global_desc.GetLengths()[1];
+        constexpr index_t Wip = in_n_hip_wip_c_global_desc.GetLengths()[2];
+
+        constexpr auto in_n_ytilda_htilda_xtilda_wtilda_c_global_desc = transform_tensor_descriptor(
+            in_n_hip_wip_c_global_desc,
+            make_tuple(PassThrough<N>{},
+                       Embed<Hip,
+                             Sequence<YTilda, HTilda>,
+                             Sequence<ConvDilationH, ConvStrideH, 0>,
+                             in_skip_out_of_bound_check>{},
+                       Embed<Wip,
+                             Sequence<XTilda, WTilda>,
+                             Sequence<ConvDilationW, ConvStrideW, 0>,
+                             in_skip_out_of_bound_check>{},
+                       PassThrough<C>{}),
+            make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
+            make_tuple(Sequence<0>{}, Sequence<1, 2>{}, Sequence<3, 4>{}, Sequence<5>{}));
+
+        constexpr auto in_n_htildaslice_wtildaslice_c_global_desc = transform_tensor_descriptor(
+            in_n_ytilda_htilda_xtilda_wtilda_c_global_desc,
+            make_tuple(PassThrough<N>{},
+                       Freeze<Sequence<YTilda, XTilda>, Sequence<iYTilda, iXTilda>>{},
+                       Slice<Sequence<HTilda, WTilda>,
+                             Sequence<iHTildaLeft, iWTildaLeft>,
+                             Sequence<iHTildaRight, iWTildaRight>>{},
+                       PassThrough<C>{}),
+            make_tuple(Sequence<0>{}, Sequence<1, 3>{}, Sequence<2, 4>{}, Sequence<5>{}),
+            make_tuple(Sequence<0>{}, Sequence<>{}, Sequence<1, 2>{}, Sequence<3>{}));
+
+        constexpr auto in_gemmm_gemmn_global_desc = transform_tensor_descriptor(
+            in_n_htildaslice_wtildaslice_c_global_desc,
+            make_tuple(PassThrough<C>{}, Merge<Sequence<N, HTildaSlice, WTildaSlice>>{}),
+            make_tuple(Sequence<3>{}, Sequence<0, 1, 2>{}),
+            make_tuple(Sequence<0>{}, Sequence<1>{}));
+
+        // call GEMM
+        constexpr auto gridwise_gemm = GridwiseGemmTransposedANormalBNormalC_v2<
+            GridSize,
+            BlockSize,
+            Float,
+            AccFloat,
+            decltype(wei_gemmk0_gemmk1_gemmk2_gemmm_global_desc),
+            decltype(out_gemmk0_gemmk1_gemmk2_gemmn_global_desc),
+            decltype(in_gemmm_gemmn_global_desc),
+            InMemoryDataOperation::Set,
+            GemmMPerBlock,
+            GemmNPerBlock,
+            GemmKPerBlock,
+            GemmMPerThread,
+            GemmNPerThread,
+            GemmKPerThread,
+            GemmMLevel0Cluster,
+            GemmNLevel0Cluster,
+            GemmMLevel1Cluster,
+            GemmNLevel1Cluster,
+            ThreadGemmDataPerRead_GemmM,
+            ThreadGemmDataPerRead_GemmN,
+            GemmABlockCopyThreadSliceLengths_GemmK0_GemmK1_GemmK2_GemmM,
+            GemmABlockCopyThreadClusterLengths_GemmK0_GemmK1_GemmK2_GemmM,
+            Sequence<0, 1, 2, 3>,
+            Sequence<0, 1, 2, 3>,
+            3,
+            GemmABlockCopySrcDataPerRead_GemmM,
+            GemmABlockCopyDstDataPerWrite_GemmM,
+            GemmBBlockCopyThreadSliceLengths_GemmK0_GemmK1_GemmK2_GemmN,
+            GemmBBlockCopyThreadClusterLengths_GemmK0_GemmK1_GemmK2_GemmN,
+            Sequence<0, 1, 3, 2>,
+            Sequence<0, 1, 3, 2>,
+            2,
+            GemmBBlockCopySrcDataPerRead_GemmK2,
+            GemmBBlockCopyDstDataPerWrite_GemmN,
+            Sequence<2, 3, 0, 1>,
+            3,
+            GemmCThreadCopyDstDataPerWrite_GemmN1>{};
+
+        gridwise_gemm.Run(p_wei_global, p_out_global, p_in_global);
+    }
+
+    template <index_t GemmId>
+    __device__ static void Run(Float* __restrict__ p_in_global,
+                               const Float* __restrict__ p_wei_global,
+                               const Float* __restrict__ p_out_global,
+                               Number<GemmId>)
+    {
+        constexpr index_t ConvStrideH = ConvStrides{}[0];
+        constexpr index_t ConvStrideW = ConvStrides{}[1];
+
+        constexpr index_t ConvDilationH = ConvDilations{}[0];
+        constexpr index_t ConvDilationW = ConvDilations{}[1];
+
+        constexpr index_t GcdStrideDilationH = math::gcd(ConvStrideH, ConvDilationH);
+        constexpr index_t GcdStrideDilationW = math::gcd(ConvStrideW, ConvDilationW);
+
+        constexpr index_t YTilda = ConvStrideH / GcdStrideDilationH;
+        constexpr index_t XTilda = ConvStrideW / GcdStrideDilationW;
+
+        constexpr index_t iYTilda = GemmId / XTilda;
+        constexpr index_t iXTilda = GemmId % XTilda;
+
+        static_assert(iYTilda < YTilda && iXTilda < XTilda, "wrong! iYtilda, iXtilda");
+
+        RunImpl<iYTilda, iXTilda>(p_in_global, p_wei_global, p_out_global);
+    }
+};
+
+} // namespace ck
+#endif

composable_kernel/include/tensor_description/multi_index_transform.hpp

@@ -488,6 +488,49 @@ struct Embed
     }
 };
 
+// LowerLengths: Sequence<...>
+// LowerFreezePoint: Sequence<...>
+template <typename LowerLengths, typename LowerFreezePoint>
+struct Freeze
+{
+    static constexpr index_t nDimLow = LowerLengths::Size();
+    static constexpr index_t nDimUp  = 0;
+
+    using LowerIndex = MultiIndex<nDimLow>;
+    using UpperIndex = MultiIndex<nDimUp>;
+
+    __host__ __device__ explicit constexpr Freeze()
+    {
+        // TODO: sanity check: LowerFreezePoint should be within range of LowerLengths
+    }
+
+    __host__ __device__ static constexpr auto GetNumOfLowerDimension() { return Number<nDimLow>{}; }
+
+    __host__ __device__ static constexpr auto GetNumOfUpperDimension() { return Number<0>{}; }
+
+    __host__ __device__ static constexpr auto GetUpperLengths() { return Sequence<>{}; }
+
+    __host__ __device__ static constexpr auto CalculateLowerIndex(const UpperIndex& /*idx_up*/)
+    {
+        return to_array(LowerFreezePoint{});
+    }
+
+    __host__ __device__ static constexpr auto
+    CalculateLowerIndexDiff(const UpperIndex& /* idx_up_diff */,
+                            const UpperIndex& /* idx_up_old */,
+                            const LowerIndex& /* idx_low_old */)
+    {
+        return make_zero_array<index_t, nDimLow>();
+    }
+
+    __host__ __device__ static constexpr bool IsLinearTransform() { return true; }
+
+    __host__ __device__ static constexpr bool IsValidUpperIndexAlwaysMappedToValidLowerIndex()
+    {
+        return true;
+    }
+};
+
 template <index_t LowerLength, index_t VectorSize>
 struct Vectorize
 {

composable_kernel/include/tensor_operation/gridwise_gemm.hpp

@@ -376,5 +376,400 @@ struct GridwiseGemmTransposedANormalBNormalC_v1
     }
 };
 
+template <index_t GridSize,
+          index_t BlockSize,
+          typename Float,
+          typename AccFloat,
+          typename AGlobalDesc,
+          typename BGlobalDesc,
+          typename CGlobalDesc,
+          InMemoryDataOperation CGlobalMemoryDataOperation,
+          index_t MPerBlock,
+          index_t NPerBlock,
+          index_t KPerBlock,
+          index_t MPerThread,
+          index_t NPerThread,
+          index_t KPerThread,
+          index_t MLevel0Cluster,
+          index_t NLevel0Cluster,
+          index_t MLevel1Cluster,
+          index_t NLevel1Cluster,
+          index_t ThreadGemmAThreadCopySrcDataPerRead_M,
+          index_t ThreadGemmBThreadCopySrcDataPerRead_N,
+          typename ABlockCopyThreadSliceLengths_K0_K1_K2_M,
+          typename ABlockCopyThreadClusterLengths_K0_K1_K2_M,
+          typename ABlockCopyThreadClusterArrangeOrder,
+          typename ABlockCopySrcAccessOrder,
+          index_t ABlockCopySrcVectorReadDim,
+          index_t ABlockCopySrcDataPerRead,
+          index_t ABlockCopyDstDataPerWrite_M,
+          typename BBlockCopyThreadSliceLengths_K0_K1_K2_N,
+          typename BBlockCopyThreadClusterLengths_K0_K1_K2_N,
+          typename BBlockCopyThreadClusterArrangeOrder,
+          typename BBlockCopySrcAccessOrder,
+          index_t BBlockCopySrcVectorReadDim,
+          index_t BBlockCopySrcDataPerRead,
+          index_t BBlockCopyDstDataPerWrite_N,
+          typename CThreadCopySrcDstAccessOrder,
+          index_t CThreadCopySrcDstVectorReadWriteDim,
+          index_t CThreadCopyDstDataPerWrite>
+struct GridwiseGemmTransposedANormalBNormalC_v2
+{
+    __host__ __device__ static constexpr index_t GetSharedMemoryNumberOfByte()
+    {
+        constexpr index_t max_lds_align = math::lcm(ABlockCopyDstDataPerWrite_M,
+                                                    BBlockCopyDstDataPerWrite_N,
+                                                    ThreadGemmAThreadCopySrcDataPerRead_M,
+                                                    ThreadGemmBThreadCopySrcDataPerRead_N);
+
+        // A matrix in LDS memory, dst of blockwise copy
+        //   be careful of LDS alignment
+        constexpr auto a_k_m_block_desc = make_native_tensor_descriptor_aligned(
+            Sequence<KPerBlock, MPerBlock>{}, Number<max_lds_align>{});
+
+        // B matrix in LDS memory, dst of blockwise copy
+        //   be careful of LDS alignment
+        constexpr auto b_k_n_block_desc = make_native_tensor_descriptor_aligned(
+            Sequence<KPerBlock, NPerBlock>{}, Number<max_lds_align>{});
+
+        // LDS allocation for A and B: be careful of alignment
+        constexpr index_t a_block_space =
+            math::integer_least_multiple(a_k_m_block_desc.GetElementSpace(), max_lds_align);
+
+        constexpr index_t b_block_space =
+            math::integer_least_multiple(b_k_n_block_desc.GetElementSpace(), max_lds_align);
+
+        return 2 * (a_block_space + b_block_space) * sizeof(Float);
+    }
+
+    __device__ void Run(const Float* __restrict__ p_a_global,
+                        const Float* __restrict__ p_b_global,
+                        Float* __restrict__ p_c_global,
+                        Float* __restrict__ p_shared_block) const
+    {
+        constexpr auto True  = integral_constant<bool, true>{};
+        constexpr auto False = integral_constant<bool, false>{};
+
+        constexpr auto I0 = Number<0>{};
+        constexpr auto I2 = Number<2>{};
+
+        constexpr auto a_k0_k1_k2_m_global_desc = AGlobalDesc{};
+        constexpr auto b_k0_k1_k2_n_global_desc = BGlobalDesc{};
+        constexpr auto c_m_n_global_desc        = CGlobalDesc{};
+
+        constexpr auto K0 = a_k0_k1_k2_m_global_desc.GetLengths()[0];
+        constexpr auto K1 = a_k0_k1_k2_m_global_desc.GetLengths()[1];
+        constexpr auto K  = a_k0_k1_k2_m_global_desc.GetLengths()[2];
+        constexpr auto M  = c_m_n_global_desc.GetLengths()[0];
+        constexpr auto N  = c_m_n_global_desc.GetLengths()[1];
+
+        // don't do anything if K == 0
+        if(K == 0)
+        {
+            return;
+        }
+
+        // lds max alignment
+        constexpr index_t max_lds_align = math::lcm(ABlockCopyDstDataPerWrite_M,
+                                                    BBlockCopyDstDataPerWrite_N,
+                                                    ThreadGemmAThreadCopySrcDataPerRead_M,
+                                                    ThreadGemmBThreadCopySrcDataPerRead_N);
+
+        // divide block work by [M, N]
+        static_assert(M % MPerBlock == 0 && N % NPerBlock == 0 && K % KPerBlock == 0,
+                      "wrong! cannot divide work evenly among block");
+
+        constexpr index_t MBlockWork = M / MPerBlock;
+        constexpr index_t NBlockWork = N / NPerBlock;
+
+        constexpr auto block_work_desc =
+            make_cluster_descriptor(Sequence<MBlockWork, NBlockWork>{});
+
+        const auto block_work_id = block_work_desc.CalculateClusterIndex(get_block_1d_id());
+
+        const index_t m_block_data_on_global = block_work_id[0] * MPerBlock;
+        const index_t n_block_data_on_global = block_work_id[1] * NPerBlock;
+
+        // A matrix in LDS memory, dst of blockwise copy
+        //   be careful of LDS alignment
+        constexpr auto a_k0_k1_k2_m_block_desc = make_native_tensor_descriptor_aligned(
+            Sequence<1, 1, KPerBlock, MPerBlock>{}, Number<max_lds_align>{});
+
+        // A matrix blockwise copy
+        auto a_blockwise_copy =
+            BlockwiseGenericTensorSliceCopy_v4<BlockSize,
+                                               decltype(a_k0_k1_k2_m_global_desc),
+                                               decltype(a_k0_k1_k2_m_block_desc),
+                                               decltype(a_k0_k1_k2_m_block_desc.GetLengths()),
+                                               ABlockCopyThreadSliceLengths_K0_K1_K2_M,
+                                               ABlockCopyThreadClusterLengths_K0_K1_K2_M,
+                                               ABlockCopyThreadClusterArrangeOrder,
+                                               ABlockCopySrcAccessOrder,
+                                               Sequence<0, 1, 2, 3>,
+                                               ABlockCopySrcVectorReadDim,
+                                               3,
+                                               ABlockCopySrcDataPerRead,
+                                               ABlockCopyDstDataPerWrite_M,
+                                               AddressSpace::Global,
+                                               AddressSpace::Vgpr,
+                                               AddressSpace::Lds,
+                                               InMemoryDataOperation::Set>(
+                {0, 0, 0, m_block_data_on_global}, {0, 0, 0, 0});
+
+        // B matrix in LDS memory, dst of blockwise copy
+        //   be careful of LDS alignment
+        constexpr auto b_k0_k1_k2_n_block_desc = make_native_tensor_descriptor_aligned(
+            Sequence<1, 1, KPerBlock, NPerBlock>{}, Number<max_lds_align>{});
+
+        // B matrix blockwise copy
+        auto b_blockwise_copy =
+            BlockwiseGenericTensorSliceCopy_v4<BlockSize,
+                                               decltype(b_k0_k1_k2_n_global_desc),
+                                               decltype(b_k0_k1_k2_n_block_desc),
+                                               decltype(b_k0_k1_k2_n_block_desc.GetLengths()),
+                                               BBlockCopyThreadSliceLengths_K0_K1_K2_N,
+                                               BBlockCopyThreadClusterLengths_K0_K1_K2_N,
+                                               BBlockCopyThreadClusterArrangeOrder,
+                                               BBlockCopySrcAccessOrder,
+                                               Sequence<0, 1, 2, 3>,
+                                               BBlockCopySrcVectorReadDim,
+                                               3,
+                                               BBlockCopySrcDataPerRead,
+                                               BBlockCopyDstDataPerWrite_N,
+                                               AddressSpace::Global,
+                                               AddressSpace::Vgpr,
+                                               AddressSpace::Lds,
+                                               InMemoryDataOperation::Set>(
+                {0, 0, 0, n_block_data_on_global}, {0, 0, 0, 0});
+
+        // GEMM definition
+        //   c_mtx += transpose(a_mtx) * b_mtx
+        //     a_mtx[KPerBlock, MPerBlock] is in LDS
+        //     b_mtx[KPerBlocl, NPerBlock] is in LDS
+        //     c_mtx[MPerBlock, NPerBlock] is distributed among threads, and saved in
+        //       register
+        constexpr auto a_k_m_block_mtx_desc = make_ConstantMatrixDescriptor(
+            unfold_tensor_descriptor(a_k0_k1_k2_m_block_desc, I0, I2));
+        constexpr auto b_k_n_block_mtx_desc = make_ConstantMatrixDescriptor(
+            unfold_tensor_descriptor(b_k0_k1_k2_n_block_desc, I0, I2));
+
+        // sanity check
+        static_assert(MPerBlock % (MPerThread * MLevel0Cluster * MLevel1Cluster) == 0 &&
+                          NPerBlock % (NPerThread * NLevel0Cluster * NLevel1Cluster) == 0,
+                      "wrong!");
+
+        constexpr index_t GemmMRepeat = MPerBlock / (MPerThread * MLevel0Cluster * MLevel1Cluster);
+        constexpr index_t GemmNRepeat = NPerBlock / (NPerThread * NLevel0Cluster * NLevel1Cluster);
+
+        // c_thread_mtx definition: this is a mess
+        // TODO:: more elegent way of defining c_thread_mtx
+        constexpr auto c_m0m1_n0n1_thread_mtx_desc = make_ConstantMatrixDescriptor_packed(
+            Number<GemmMRepeat * MPerThread>{}, Number<GemmNRepeat * NPerThread>{});
+
+        const auto blockwise_gemm = BlockwiseGemmBlockABlockBThreadCTransANormalBNormalC_v2<
+            BlockSize,
+            decltype(a_k_m_block_mtx_desc),
+            decltype(b_k_n_block_mtx_desc),
+            decltype(c_m0m1_n0n1_thread_mtx_desc),
+            MPerThread,
+            NPerThread,
+            KPerThread,
+            MLevel0Cluster,
+            NLevel0Cluster,
+            MLevel1Cluster,
+            NLevel1Cluster,
+            ThreadGemmAThreadCopySrcDataPerRead_M,
+            ThreadGemmBThreadCopySrcDataPerRead_N>{};
+
+        // LDS allocation for A and B: be careful of alignment
+        constexpr index_t a_block_space =
+            math::integer_least_multiple(a_k0_k1_k2_m_block_desc.GetElementSpace(), max_lds_align);
+
+        constexpr index_t b_block_space =
+            math::integer_least_multiple(b_k0_k1_k2_n_block_desc.GetElementSpace(), max_lds_align);
+
+        Float* p_a_block_double = p_shared_block;
+        Float* p_b_block_double = p_shared_block + 2 * a_block_space;
+
+        // register allocation for output
+        AccFloat p_c_thread[c_m0m1_n0n1_thread_mtx_desc.GetElementSpace()];
+
+        // zero out threadwise output
+        threadwise_matrix_set_zero(c_m0m1_n0n1_thread_mtx_desc, p_c_thread);
+
+        for(index_t k0 = 0; k0 < K0; ++k0)
+        {
+            for(index_t k1 = 0; k1 < K1; ++k1)
+            {
+
+                // LDS double buffer: preload data into LDS
+                {
+                    a_blockwise_copy.Run(p_a_global, p_a_block_double);
+                    b_blockwise_copy.Run(p_b_global, p_b_block_double);
+                }
+
+                constexpr auto a_block_slice_copy_steps = Sequence<0, 0, KPerBlock, 0>{};
+                constexpr auto b_block_slice_copy_steps = Sequence<0, 0, KPerBlock, 0>{};
+
+                // LDS double buffer: main body
+                for(index_t k_block_data_begin = 0; k_block_data_begin + 2 * KPerBlock < K;
+                    k_block_data_begin += 2 * KPerBlock)
+                {
+#pragma unroll
+                    for(index_t iloop = 0; iloop < 2; ++iloop)
+                    {
+                        const bool even_loop = (iloop % 2 == 0);
+
+                        Float* p_a_block_now =
+                            even_loop ? p_a_block_double : p_a_block_double + a_block_space;
+                        Float* p_b_block_now =
+                            even_loop ? p_b_block_double : p_b_block_double + b_block_space;
+
+                        Float* p_a_block_next =
+                            even_loop ? p_a_block_double + a_block_space : p_a_block_double;
+                        Float* p_b_block_next =
+                            even_loop ? p_b_block_double + b_block_space : p_b_block_double;
+
+                        Float p_a_thread_buffer[a_blockwise_copy.GetThreadBufferSize()];
+                        Float p_b_thread_buffer[b_blockwise_copy.GetThreadBufferSize()];
+
+                        a_blockwise_copy.MoveSrcSliceWindow(a_block_slice_copy_steps, True);
+                        b_blockwise_copy.MoveSrcSliceWindow(b_block_slice_copy_steps, True);
+
+                        __syncthreads();
+
+                        // LDS doubel buffer: load next data from device mem
+                        a_blockwise_copy.RunLoadThreadBuffer(p_a_global, p_a_thread_buffer);
+                        b_blockwise_copy.RunLoadThreadBuffer(p_b_global, p_b_thread_buffer);
+
+                        // LDS double buffer: GEMM on current data
+                        blockwise_gemm.Run(p_a_block_now, p_b_block_now, p_c_thread);
+
+                        // LDS double buffer: store next data to LDS
+                        a_blockwise_copy.RunStoreThreadBuffer(p_a_thread_buffer, p_a_block_next);
+                        b_blockwise_copy.RunStoreThreadBuffer(p_b_thread_buffer, p_b_block_next);
+                    }
+                }
+
+                // LDS double buffer: tail
+                {
+                    constexpr bool has_two_iteration_left = (K % (2 * KPerBlock) == 0);
+
+                    if(has_two_iteration_left) // if has 2 iteration left
+                    {
+                        Float p_a_thread_buffer[a_blockwise_copy.GetThreadBufferSize()];
+                        Float p_b_thread_buffer[b_blockwise_copy.GetThreadBufferSize()];
+
+                        a_blockwise_copy.MoveSrcSliceWindow(a_block_slice_copy_steps, True);
+                        b_blockwise_copy.MoveSrcSliceWindow(b_block_slice_copy_steps, True);
+
+                        __syncthreads();
+
+                        // LDS double buffer: load last data from device mem
+                        a_blockwise_copy.RunLoadThreadBuffer(p_a_global, p_a_thread_buffer);
+                        b_blockwise_copy.RunLoadThreadBuffer(p_b_global, p_b_thread_buffer);
+
+                        // LDS double buffer: GEMM on 2nd-last data
+                        blockwise_gemm.Run(p_a_block_double, p_b_block_double, p_c_thread);
+
+                        // LDS double buffer: store last data to LDS
+                        a_blockwise_copy.RunStoreThreadBuffer(p_a_thread_buffer,
+                                                              p_a_block_double + a_block_space);
+                        b_blockwise_copy.RunStoreThreadBuffer(p_b_thread_buffer,
+                                                              p_b_block_double + b_block_space);
+
+                        __syncthreads();
+
+                        // LDS double buffer: GEMM on last data
+                        blockwise_gemm.Run(p_a_block_double + a_block_space,
+                                           p_b_block_double + b_block_space,
+                                           p_c_thread);
+                    }
+                    else // if has 1 iteration left
+                    {
+                        __syncthreads();
+
+                        // LDS double buffer: GEMM on last data
+                        blockwise_gemm.Run(p_a_block_double, p_b_block_double, p_c_thread);
+                    }
+                }
+
+                // reset slice windoww on K2 dimension, then move forward on K1 dimension
+                a_blockwise_copy.MoveSrcSliceWindow(Sequence<0, 0, K - KPerBlock, 0>{}, False);
+                b_blockwise_copy.MoveSrcSliceWindow(Sequence<0, 0, K - KPerBlock, 0>{}, False);
+
+                a_blockwise_copy.MoveSrcSliceWindow(Sequence<0, 1, 0, 0>{}, True);
+                b_blockwise_copy.MoveSrcSliceWindow(Sequence<0, 1, 0, 0>{}, True);
+            }
+
+            // reset slice windoww on K1 dimension, then move forward on K0 dimension
+            a_blockwise_copy.MoveSrcSliceWindow(Sequence<0, K1, 0, 0>{}, False);
+            b_blockwise_copy.MoveSrcSliceWindow(Sequence<0, K1, 0, 0>{}, False);
+
+            a_blockwise_copy.MoveSrcSliceWindow(Sequence<1, 0, 0, 0>{}, True);
+            b_blockwise_copy.MoveSrcSliceWindow(Sequence<1, 0, 0, 0>{}, True);
+        }
+
+        // input: register to global memory
+        {
+            constexpr index_t M1 = MPerThread * MLevel0Cluster * MLevel1Cluster;
+            constexpr index_t M0 = M / M1;
+
+            constexpr index_t N1 = NPerThread * NLevel0Cluster * NLevel1Cluster;
+            constexpr index_t N0 = N / N1;
+
+            // define input tensor descriptor for threadwise copy
+            //     thread input tensor, src of threadwise copy
+            constexpr auto c_m0_m1_n0_n1_thread_desc = make_native_tensor_descriptor_packed(
+                Sequence<GemmMRepeat, MPerThread, GemmNRepeat, NPerThread>{});
+
+            constexpr auto c_m0_m1_n0_n1_global_desc = transform_tensor_descriptor(
+                c_m_n_global_desc,
+                make_tuple(UnMerge<Sequence<M0, M1>>{}, UnMerge<Sequence<N0, N1>>{}),
+                make_tuple(Sequence<0>{}, Sequence<1>{}),
+                make_tuple(Sequence<0, 1>{}, Sequence<2, 3>{}));
+
+            // calculate origin of thread input tensor on global memory
+            //     blockwise GEMM c matrix starting index
+            const auto c_thread_mtx_on_block =
+                blockwise_gemm.GetBeginOfThreadMatrixC(get_thread_local_1d_id());
+
+            const index_t m_thread_data_on_global =
+                m_block_data_on_global + c_thread_mtx_on_block.row;
+
+            const index_t n_thread_data_on_global =
+                n_block_data_on_global + c_thread_mtx_on_block.col;
+
+            ThreadwiseGenericTensorSliceCopy_v4r2<decltype(c_m0_m1_n0_n1_thread_desc),
+                                                  decltype(c_m0_m1_n0_n1_global_desc),
+                                                  decltype(c_m0_m1_n0_n1_thread_desc.GetLengths()),
+                                                  CThreadCopySrcDstAccessOrder,
+                                                  CThreadCopySrcDstVectorReadWriteDim,
+                                                  1,
+                                                  CThreadCopyDstDataPerWrite,
+                                                  AddressSpace::Vgpr,
+                                                  AddressSpace::Global,
+                                                  CGlobalMemoryDataOperation>(
+                {0, 0, 0, 0},
+                {m_thread_data_on_global / M1,
+                 m_thread_data_on_global % M1,
+                 n_thread_data_on_global / N1,
+                 n_thread_data_on_global % N1})
+                .Run(p_c_thread, p_c_global);
+        }
+    }
+
+    __device__ void Run(const Float* __restrict__ p_a_global,
+                        const Float* __restrict__ p_b_global,
+                        Float* __restrict__ p_c_global) const
+    {
+        constexpr index_t shared_block_size = GetSharedMemoryNumberOfByte() / sizeof(Float);
+
+        __shared__ Float p_shared_block[shared_block_size];
+
+        Run(p_a_global, p_b_global, p_c_global, p_shared_block);
+    }
+};
+
 } // namespace ck
 #endif

composable_kernel/include/utility/array.hpp

@@ -12,6 +12,7 @@ struct Array
     using type      = Array<TData, NSize>;
     using data_type = TData;
 
+    // TODO: implement empty Array
     index_t mData[NSize];
 
     __host__ __device__ explicit constexpr Array() {}

composable_kernel/include/utility/common_header.hpp

@@ -24,6 +24,7 @@
 
 #if CK_USE_AMD_XDLOPS
 #include "amd_xdlops.hpp"
+#include "amd_xdlops_inline_asm.hpp"
 #endif
 
 #endif

composable_kernel/include/utility/in_memory_operation.amd.hpp.in

@@ -108,8 +108,12 @@ struct SetData
     {
         const auto zeros = vector_t(0);
 
-        amd_buffer_store<T, DataPerAccess>(
-            src_valid ? &(p_src[src_offset]) : &zeros, p_dst, dst_offset, dst_valid, dst_range);
+        amd_buffer_store<T, DataPerAccess>(src_valid ? &(p_src[src_offset])
+                                                     : reinterpret_cast<const T*>(&zeros),
+                                           p_dst,
+                                           dst_offset,
+                                           dst_valid,
+                                           dst_range);
     }
 #endif
 };
@@ -145,19 +149,17 @@ struct AtomicAddData
     template <>
     __device__ void Run<AddressSpace::Vgpr, AddressSpace::Global>(const T* p_src,
                                                                   index_t src_offset,
+                                                                  bool src_valid,
                                                                   index_t /* src_range */,
-                                                                  bool src_valid T* p_dst,
+                                                                  T* p_dst,
                                                                   index_t dst_offset,
                                                                   bool dst_valid,
                                                                   index_t dst_range) const
     {
         const auto zeros = vector_t(0);
 
-        amd_buffer_atomic_add<T, DataPerAccess>(src_valid ? &(p_src[src_offset]) : &zeros,
-                                                p_dst,
-                                                dst_offset,
-                                                dst_valid,
-                                                index_t dst_range);
+        amd_buffer_atomic_add<T, DataPerAccess>(
+            src_valid ? &(p_src[src_offset]) : &zeros, p_dst, dst_offset, dst_valid, dst_range);
     }
 #endif
 };

driver/CMakeLists.txt

@@ -16,15 +16,14 @@ install(TARGETS host LIBRARY DESTINATION lib)
 
 if(DEVICE_BACKEND STREQUAL "AMD")
     set(CONV_SOURCE src/conv_driver.cpp)
-    set(COL2IM_SOURCE src/col2im_driver.cpp)
     set(CONV_BWD_DATA_SOURCE src/conv_bwd_data_driver.cpp)
 elseif(DEVICE_BACKEND STREQUAL "NVIDIA")
     set(CONV_SOURCE src/conv_driver.cu)
-    set(COL2IM_SOURCE src/col2im_driver.cu)
     set(CONV_BWD_DATA_SOURCE src/conv_bwd_data_driver.cu)
 endif()
 
 add_executable(conv_driver ${CONV_SOURCE}) 
 add_executable(conv_bwd_data_driver ${CONV_BWD_DATA_SOURCE}) 
+
 target_link_libraries(conv_driver PRIVATE host)
 target_link_libraries(conv_bwd_data_driver PRIVATE host)

driver/include/device_convolution_backward_data_implicit_gemm_v3r1_nchw_kcyx_nkhw.hpp

-#pragma once
-#include <unistd.h>
-#include "device.hpp"
-#include "host_tensor.hpp"
-#include "gridwise_operation_wrapper.hpp"
-#include "gridwise_convolution_backward_data_implicit_gemm_v3r1_nchw_kcyx_nkhw.hpp"
-
-namespace launcher {
-
-using namespace ck;
-
-template <typename T,
-          typename InDesc,
-          typename WeiDesc,
-          typename OutDesc,
-          typename ConvStrides,
-          typename ConvDilations,
-          typename InLeftPads,
-          typename InRightPads>
-void device_convolution_backward_data_implicit_gemm_v3r1_nchw_kcyx_nkhw(InDesc in_nchw_desc,
-                                                                        Tensor<T>& in_nchw,
-                                                                        WeiDesc wei_kcyx_desc,
-                                                                        const Tensor<T>& wei_kcyx,
-                                                                        OutDesc out_nkhw_desc,
-                                                                        const Tensor<T>& out_nkhw,
-                                                                        ConvStrides,
-                                                                        ConvDilations,
-                                                                        InLeftPads,
-                                                                        InRightPads,
-                                                                        std::size_t nrepeat)
-{
-    using namespace ck;
-
-    constexpr index_t N = out_nkhw_desc.GetLengths()[0];
-    constexpr index_t K = out_nkhw_desc.GetLengths()[1];
-    constexpr index_t C = wei_kcyx_desc.GetLengths()[1];
-
-    constexpr index_t Hi = in_nchw_desc.GetLengths()[2];
-    constexpr index_t Wi = in_nchw_desc.GetLengths()[3];
-
-    constexpr index_t Ho = out_nkhw_desc.GetLengths()[2];
-    constexpr index_t Wo = out_nkhw_desc.GetLengths()[3];
-
-    constexpr index_t Y = wei_kcyx_desc.GetLengths()[2];
-    constexpr index_t X = wei_kcyx_desc.GetLengths()[3];
-
-    constexpr index_t ConvStrideH = ConvStrides{}[0];
-    constexpr index_t ConvStrideW = ConvStrides{}[1];
-
-    constexpr index_t ConvDilationH = ConvDilations{}[0];
-    constexpr index_t ConvDilationW = ConvDilations{}[1];
-
-    std::size_t data_sz = sizeof(T);
-    DeviceMem in_nchw_device_buf(data_sz * in_nchw.mDesc.GetElementSpace());
-    DeviceMem wei_kcyx_device_buf(data_sz * wei_kcyx.mDesc.GetElementSpace());
-    DeviceMem out_nkhw_device_buf(data_sz * out_nkhw.mDesc.GetElementSpace());
-
-    in_nchw_device_buf.ToDevice(in_nchw.mData.data());
-    wei_kcyx_device_buf.ToDevice(wei_kcyx.mData.data());
-    out_nkhw_device_buf.ToDevice(out_nkhw.mData.data());
-
-#if 1
-    // BlockSize = 256, each thread hold 64 data
-    constexpr index_t BlockSize = 256;
-
-    constexpr index_t GemmMPerBlock              = 128;
-    constexpr index_t GemmNPerBlock              = 128;
-    constexpr index_t GemmKPerBlock              = 8;
-    constexpr index_t GemmMPerThread             = 4;
-    constexpr index_t GemmNPerThread             = 4;
-    constexpr index_t GemmKPerThread             = 1;
-    constexpr index_t GemmMLevel0Cluster         = 4;
-    constexpr index_t GemmNLevel0Cluster         = 4;
-    constexpr index_t GemmMLevel1Cluster         = 4;
-    constexpr index_t GemmNLevel1Cluster         = 4;
-    constexpr index_t GemmThreadGemmDataPerReadM = 4;
-    constexpr index_t GemmThreadGemmDataPerReadN = 4;
-
-    using GemmABlockCopyThreadSliceLengths_GemmK_GemmM   = Sequence<4, 1>;
-    using GemmABlockCopyThreadClusterLengths_GemmK_GemmM = Sequence<2, 128>;
-
-    constexpr index_t GemmABlockCopySrcDataPerRead_GemmM  = 1;
-    constexpr index_t GemmABlockCopyDstDataPerWrite_GemmM = 1;
-
-    using GemmBBlockCopyThreadSliceLengths_GemmK_GemmN   = Sequence<4, 1>;
-    using GemmBBlockCopyThreadClusterLengths_GemmK_GemmN = Sequence<2, 128>;
-
-    constexpr index_t GemmBBlockCopySrcDataPerRead_GemmN  = 1;
-    constexpr index_t GemmBBlockCopyDstDataPerWrite_GemmN = 1;
-
-    constexpr index_t GemmCThreadCopyDstDataPerWrite_GemmN1 = 1;
-#endif
-
-    constexpr index_t GcdStrideDilationH = math::gcd(ConvStrideH, ConvDilationH);
-    constexpr index_t GcdStrideDilationW = math::gcd(ConvStrideW, ConvDilationW);
-
-    constexpr index_t YTilda = ConvStrideH / GcdStrideDilationH;
-    constexpr index_t XTilda = ConvStrideW / GcdStrideDilationW;
-
-    constexpr index_t YDot = math::integer_divide_ceil(Y, YTilda);
-    constexpr index_t XDot = math::integer_divide_ceil(X, XTilda);
-
-    constexpr index_t HTilda = Ho + math::integer_divide_ceil(ConvDilationH * (Y - 1), ConvStrideH);
-    constexpr index_t WTilda = Wo + math::integer_divide_ceil(ConvDilationW * (X - 1), ConvStrideW);
-
-    constexpr index_t HTildaLeft = math::integer_divide_floor(
-        math::max(0, InLeftPads{}[0] - ConvDilationH * (YTilda - 1)), ConvStrides{}[0]);
-    constexpr index_t WTildaLeft = math::integer_divide_floor(
-        math::max(0, InLeftPads{}[1] - ConvDilationW * (XTilda - 1)), ConvStrides{}[1]);
-
-    constexpr index_t HTildaRight = math::min(
-        HTilda, math::integer_divide_ceil(InLeftPads{}[0] + Hi - 1, ConvStrides{}[0]) + 1);
-    constexpr index_t WTildaRight = math::min(
-        WTilda, math::integer_divide_ceil(InLeftPads{}[1] + Wi - 1, ConvStrides{}[1]) + 1);
-
-    constexpr index_t HTildaSlice = HTildaRight - HTildaLeft;
-    constexpr index_t WTildaSlice = WTildaRight - WTildaLeft;
-
-    constexpr index_t GemmM = C;
-    constexpr index_t GemmN = N * HTildaSlice * WTildaSlice;
-
-    constexpr index_t GridSize = math::integer_divide_ceil(GemmM, GemmMPerBlock) *
-                                 math::integer_divide_ceil(GemmN, GemmNPerBlock);
-
-    printf("%s: BlockSize %u, GridSize %u \n", __func__, BlockSize, GridSize);
-
-    using gridwise_conv_bwd_data = GridwiseConvolutionBackwardDataImplicitGemm_v3r1_nchw_kcyx_nkhw<
-        GridSize,
-        BlockSize,
-        T,
-        T,
-        decltype(in_nchw_desc),
-        decltype(wei_kcyx_desc),
-        decltype(out_nkhw_desc),
-        ConvStrides,
-        ConvDilations,
-        InLeftPads,
-        InRightPads,
-        GemmMPerBlock,
-        GemmNPerBlock,
-        GemmKPerBlock,
-        GemmMPerThread,
-        GemmNPerThread,
-        GemmKPerThread,
-        GemmMLevel0Cluster,
-        GemmNLevel0Cluster,
-        GemmMLevel1Cluster,
-        GemmNLevel1Cluster,
-        GemmThreadGemmDataPerReadM,
-        GemmThreadGemmDataPerReadN,
-        GemmABlockCopyThreadSliceLengths_GemmK_GemmM,
-        GemmABlockCopyThreadClusterLengths_GemmK_GemmM,
-        GemmABlockCopySrcDataPerRead_GemmM,
-        GemmABlockCopyDstDataPerWrite_GemmM,
-        GemmBBlockCopyThreadSliceLengths_GemmK_GemmN,
-        GemmBBlockCopyThreadClusterLengths_GemmK_GemmN,
-        GemmBBlockCopySrcDataPerRead_GemmN,
-        GemmBBlockCopyDstDataPerWrite_GemmN,
-        GemmCThreadCopyDstDataPerWrite_GemmN1>;
-
-    for(index_t i = 0; i < 5; ++i)
-    {
-        std::cout << "Start running " << nrepeat << " times..." << std::endl;
-
-        KernelTimer timer;
-        timer.Start();
-
-        for(index_t j = 0; j < nrepeat; ++j)
-        {
-            launch_kernel(run_gridwise_operation<gridwise_conv_bwd_data,
-                                                 T* const __restrict__,
-                                                 const T* const __restrict__,
-                                                 const T* const __restrict__>,
-                          dim3(GridSize),
-                          dim3(BlockSize),
-                          0,
-                          0,
-                          static_cast<T*>(in_nchw_device_buf.GetDeviceBuffer()),
-                          static_cast<T*>(wei_kcyx_device_buf.GetDeviceBuffer()),
-                          static_cast<T*>(out_nkhw_device_buf.GetDeviceBuffer()));
-        }
-
-        timer.End();
-
-        float ave_time = timer.GetElapsedTime() / nrepeat;
-
-        float perf = (float)calculate_convolution_flops(InDesc{}, WeiDesc{}, OutDesc{}) /
-                     (std::size_t(1000) * 1000 * 1000) / ave_time;
-
-        std::cout << "Average time : " << ave_time << " ms, " << perf << " TFlop/s" << std::endl;
-    }
-
-    in_nchw_device_buf.FromDevice(in_nchw.mData.data());
-}
-
-} // namespace launcher

driver/include/device_convolution_backward_data_implicit_gemm_v4r1_nchw_kcyx_nkhw.hpp

@@ -57,8 +57,8 @@ void device_convolution_backward_data_implicit_gemm_v4r1_nchw_kcyx_nkhw(InDesc i
     wei_kcyx_device_buf.ToDevice(wei_kcyx.mData.data());
     out_nkhw_device_buf.ToDevice(out_nkhw.mData.data());
 
-#if 1
-    // BlockSize = 256, each thread hold 64 data
+#if 0
+    // cdata = 64, BlockSize = 256, 128x128x8
     constexpr index_t BlockSize = 256;
 
     constexpr index_t GemmMPerBlock              = 128;
@@ -86,6 +86,36 @@ void device_convolution_backward_data_implicit_gemm_v4r1_nchw_kcyx_nkhw(InDesc i
     constexpr index_t GemmBBlockCopySrcDataPerRead_GemmN  = 1;
     constexpr index_t GemmBBlockCopyDstDataPerWrite_GemmN = 1;
 
+    constexpr index_t GemmCThreadCopyDstDataPerWrite_GemmN1 = 1;
+#elif 1
+    // cdata = 64, BlockSize = 256, 128x128x16
+    constexpr index_t BlockSize = 256;
+
+    constexpr index_t GemmMPerBlock              = 128;
+    constexpr index_t GemmNPerBlock              = 128;
+    constexpr index_t GemmKPerBlock              = 16;
+    constexpr index_t GemmMPerThread             = 4;
+    constexpr index_t GemmNPerThread             = 4;
+    constexpr index_t GemmKPerThread             = 1;
+    constexpr index_t GemmMLevel0Cluster         = 4;
+    constexpr index_t GemmNLevel0Cluster         = 4;
+    constexpr index_t GemmMLevel1Cluster         = 4;
+    constexpr index_t GemmNLevel1Cluster         = 4;
+    constexpr index_t GemmThreadGemmDataPerReadM = 4;
+    constexpr index_t GemmThreadGemmDataPerReadN = 4;
+
+    using GemmABlockCopyThreadSliceLengths_GemmK_GemmM   = Sequence<8, 1>;
+    using GemmABlockCopyThreadClusterLengths_GemmK_GemmM = Sequence<2, 128>;
+
+    constexpr index_t GemmABlockCopySrcDataPerRead_GemmM  = 1;
+    constexpr index_t GemmABlockCopyDstDataPerWrite_GemmM = 1;
+
+    using GemmBBlockCopyThreadSliceLengths_GemmK_GemmN   = Sequence<8, 1>;
+    using GemmBBlockCopyThreadClusterLengths_GemmK_GemmN = Sequence<2, 128>;
+
+    constexpr index_t GemmBBlockCopySrcDataPerRead_GemmN  = 1;
+    constexpr index_t GemmBBlockCopyDstDataPerWrite_GemmN = 1;
+
     constexpr index_t GemmCThreadCopyDstDataPerWrite_GemmN1 = 1;
 #endif
 

driver/include/device_convolution_backward_data_implicit_gemm_v2r1_nchw_kcyx_nkhw.hpp → driver/include/device_convolution_backward_data_implicit_gemm_v5r1_nhwc_kyxc_nhwk.hpp

@@ -3,7 +3,7 @@
 #include "device.hpp"
 #include "host_tensor.hpp"
 #include "gridwise_operation_wrapper.hpp"
-#include "gridwise_convolution_backward_data_implicit_gemm_v2r1_nchw_kcyx_nkhw.hpp"
+#include "gridwise_convolution_backward_data_implicit_gemm_v5r1_nhwc_kyxc_nhwk.hpp"
 
 namespace launcher {
 
@@ -17,7 +17,7 @@ template <typename T,
           typename ConvDilations,
           typename InLeftPads,
           typename InRightPads>
-void device_convolution_backward_data_implicit_gemm_v2r1_nchw_kcyx_nkhw(InDesc in_nchw_desc,
+void device_convolution_backward_data_implicit_gemm_v5r1_nhwc_kyxc_nhwk(InDesc in_nchw_desc,
                                                                         Tensor<T>& in_nchw,
                                                                         WeiDesc wei_kcyx_desc,
                                                                         const Tensor<T>& wei_kcyx,
@@ -29,8 +29,6 @@ void device_convolution_backward_data_implicit_gemm_v2r1_nchw_kcyx_nkhw(InDesc i
                                                                         InRightPads,
                                                                         std::size_t nrepeat)
 {
-    using namespace ck;
-
     constexpr index_t N = out_nkhw_desc.GetLengths()[0];
     constexpr index_t K = out_nkhw_desc.GetLengths()[1];
     constexpr index_t C = wei_kcyx_desc.GetLengths()[1];
@@ -50,47 +48,41 @@ void device_convolution_backward_data_implicit_gemm_v2r1_nchw_kcyx_nkhw(InDesc i
     constexpr index_t ConvDilationH = ConvDilations{}[0];
     constexpr index_t ConvDilationW = ConvDilations{}[1];
 
-    std::size_t data_sz = sizeof(T);
-    DeviceMem in_nchw_device_buf(data_sz * in_nchw.mDesc.GetElementSpace());
-    DeviceMem wei_kcyx_device_buf(data_sz * wei_kcyx.mDesc.GetElementSpace());
-    DeviceMem out_nkhw_device_buf(data_sz * out_nkhw.mDesc.GetElementSpace());
+    constexpr auto in_nhwc_desc  = make_native_tensor_descriptor_packed(Sequence<N, Hi, Wi, C>{});
+    constexpr auto wei_kyxc_desc = make_native_tensor_descriptor_packed(Sequence<K, Y, X, C>{});
+    constexpr auto out_nhwk_desc = make_native_tensor_descriptor_packed(Sequence<N, Ho, Wo, K>{});
 
-    in_nchw_device_buf.ToDevice(in_nchw.mData.data());
-    wei_kcyx_device_buf.ToDevice(wei_kcyx.mData.data());
-    out_nkhw_device_buf.ToDevice(out_nkhw.mData.data());
+    Tensor<float> in_nhwc(make_HostTensorDescriptor(in_nhwc_desc));
+    Tensor<float> wei_kyxc(make_HostTensorDescriptor(wei_kyxc_desc));
+    Tensor<float> out_nhwk(make_HostTensorDescriptor(out_nhwk_desc));
 
-#if 1
-    // BlockSize = 256, each thread hold 64 data
-    constexpr index_t BlockSize = 256;
+    auto f_nchw2nhwc = [&](auto n, auto hi, auto wi, auto c) {
+        in_nhwc(n, hi, wi, c) = in_nchw(n, c, hi, wi);
+    };
 
-    constexpr index_t GemmMPerBlock              = 128;
-    constexpr index_t GemmNPerBlock              = 128;
-    constexpr index_t GemmKPerBlock              = 8;
-    constexpr index_t GemmMPerThread             = 4;
-    constexpr index_t GemmNPerThread             = 4;
-    constexpr index_t GemmKPerThread             = 1;
-    constexpr index_t GemmMLevel0Cluster         = 4;
-    constexpr index_t GemmNLevel0Cluster         = 4;
-    constexpr index_t GemmMLevel1Cluster         = 4;
-    constexpr index_t GemmNLevel1Cluster         = 4;
-    constexpr index_t GemmThreadGemmDataPerReadM = 4;
-    constexpr index_t GemmThreadGemmDataPerReadN = 4;
+    auto f_kcyx2kyxc = [&](auto k, auto y, auto x, auto c) {
+        wei_kyxc(k, y, x, c) = wei_kcyx(k, c, y, x);
+    };
 
-    using GemmABlockCopyThreadSliceLengths_GemmK_GemmM   = Sequence<4, 1>;
-    using GemmABlockCopyThreadClusterLengths_GemmK_GemmM = Sequence<2, 128>;
+    auto f_nkhw2nhwk = [&](auto n, auto ho, auto wo, auto k) {
+        out_nhwk(n, ho, wo, k) = out_nkhw(n, k, ho, wo);
+    };
 
-    constexpr index_t GemmABlockCopySrcDataPerRead_GemmM  = 1;
-    constexpr index_t GemmABlockCopyDstDataPerWrite_GemmM = 1;
+    make_ParallelTensorFunctor(f_nchw2nhwc, N, Hi, Wi, C)(std::thread::hardware_concurrency());
+    make_ParallelTensorFunctor(f_kcyx2kyxc, K, Y, X, C)(std::thread::hardware_concurrency());
+    make_ParallelTensorFunctor(f_nkhw2nhwk, N, Ho, Wo, K)(std::thread::hardware_concurrency());
 
-    using GemmBBlockCopyThreadSliceLengths_GemmK_GemmN   = Sequence<4, 1>;
-    using GemmBBlockCopyThreadClusterLengths_GemmK_GemmN = Sequence<2, 128>;
+    std::size_t data_sz = sizeof(T);
+    DeviceMem in_nhwc_device_buf(data_sz * in_nhwc.mDesc.GetElementSpace());
+    DeviceMem wei_kyxc_device_buf(data_sz * wei_kyxc.mDesc.GetElementSpace());
+    DeviceMem out_nhwk_device_buf(data_sz * out_nhwk.mDesc.GetElementSpace());
 
-    constexpr index_t GemmBBlockCopySrcDataPerRead_GemmN  = 1;
-    constexpr index_t GemmBBlockCopyDstDataPerWrite_GemmN = 1;
+    in_nhwc_device_buf.ToDevice(in_nhwc.mData.data());
+    wei_kyxc_device_buf.ToDevice(wei_kyxc.mData.data());
+    out_nhwk_device_buf.ToDevice(out_nhwk.mData.data());
 
-    constexpr index_t GemmCThreadCopyDstDataPerWrite_GemmN1 = 1;
-#elif 1
-    // BlockSize = 256, each thread hold 64 data
+#if 0
+    // cdata = 64, BlockSize = 256, 128x128x8
     constexpr index_t BlockSize = 256;
 
     constexpr index_t GemmMPerBlock              = 128;
@@ -106,27 +98,26 @@ void device_convolution_backward_data_implicit_gemm_v2r1_nchw_kcyx_nkhw(InDesc i
     constexpr index_t GemmThreadGemmDataPerReadM = 4;
     constexpr index_t GemmThreadGemmDataPerReadN = 4;
 
-    using GemmABlockCopyThreadSliceLengths_GemmK_GemmM   = Sequence<1, 4>;
-    using GemmABlockCopyThreadClusterLengths_GemmK_GemmM = Sequence<8, 32>;
+    using GemmABlockCopyThreadSliceLengths_GemmK0_GemmK1_GemmK2_GemmM   = Sequence<1, 1, 1, 4>;
+    using GemmABlockCopyThreadClusterLengths_GemmK0_GemmK1_GemmK2_GemmM = Sequence<1, 1, 8, 32>;
 
-    constexpr index_t GemmABlockCopySrcDataPerRead_GemmM  = 1;
-    constexpr index_t GemmABlockCopyDstDataPerWrite_GemmM = 1;
+    constexpr index_t GemmABlockCopySrcDataPerRead_GemmM  = 4;
+    constexpr index_t GemmABlockCopyDstDataPerWrite_GemmM = 4;
 
-    using GemmBBlockCopyThreadSliceLengths_GemmK_GemmN   = Sequence<1, 4>;
-    using GemmBBlockCopyThreadClusterLengths_GemmK_GemmN = Sequence<8, 32>;
+    using GemmBBlockCopyThreadSliceLengths_GemmK0_GemmK1_GemmK2_GemmN   = Sequence<1, 1, 4, 1>;
+    using GemmBBlockCopyThreadClusterLengths_GemmK0_GemmK1_GemmK2_GemmN = Sequence<1, 1, 2, 128>;
 
-    constexpr index_t GemmBBlockCopySrcDataPerRead_GemmN  = 1;
+    constexpr index_t GemmBBlockCopySrcDataPerRead_GemmK2 = 4;
     constexpr index_t GemmBBlockCopyDstDataPerWrite_GemmN = 1;
 
     constexpr index_t GemmCThreadCopyDstDataPerWrite_GemmN1 = 1;
 #elif 1
-    // BlockSize = 256, each thread hold 64 data
-    // for 1x1 weight, 8x8 input
+    // cdata = 64, BlockSize = 256, 128x128x16
     constexpr index_t BlockSize = 256;
 
     constexpr index_t GemmMPerBlock              = 128;
     constexpr index_t GemmNPerBlock              = 128;
-    constexpr index_t GemmKPerBlock              = 8;
+    constexpr index_t GemmKPerBlock              = 16;
     constexpr index_t GemmMPerThread             = 4;
     constexpr index_t GemmNPerThread             = 4;
     constexpr index_t GemmKPerThread             = 1;
@@ -137,19 +128,19 @@ void device_convolution_backward_data_implicit_gemm_v2r1_nchw_kcyx_nkhw(InDesc i
     constexpr index_t GemmThreadGemmDataPerReadM = 4;
     constexpr index_t GemmThreadGemmDataPerReadN = 4;
 
-    using GemmABlockCopyThreadSliceLengths_GemmK_GemmM   = Sequence<1, 4>;
-    using GemmABlockCopyThreadClusterLengths_GemmK_GemmM = Sequence<8, 32>;
+    using GemmABlockCopyThreadSliceLengths_GemmK0_GemmK1_GemmK2_GemmM   = Sequence<1, 1, 2, 4>;
+    using GemmABlockCopyThreadClusterLengths_GemmK0_GemmK1_GemmK2_GemmM = Sequence<1, 1, 8, 32>;
 
     constexpr index_t GemmABlockCopySrcDataPerRead_GemmM  = 4;
     constexpr index_t GemmABlockCopyDstDataPerWrite_GemmM = 4;
 
-    using GemmBBlockCopyThreadSliceLengths_GemmK_GemmN   = Sequence<1, 4>;
-    using GemmBBlockCopyThreadClusterLengths_GemmK_GemmN = Sequence<8, 32>;
+    using GemmBBlockCopyThreadSliceLengths_GemmK0_GemmK1_GemmK2_GemmN   = Sequence<1, 1, 8, 1>;
+    using GemmBBlockCopyThreadClusterLengths_GemmK0_GemmK1_GemmK2_GemmN = Sequence<1, 1, 2, 128>;
 
-    constexpr index_t GemmBBlockCopySrcDataPerRead_GemmN  = 4;
-    constexpr index_t GemmBBlockCopyDstDataPerWrite_GemmN = 4;
+    constexpr index_t GemmBBlockCopySrcDataPerRead_GemmK2 = 4;
+    constexpr index_t GemmBBlockCopyDstDataPerWrite_GemmN = 1;
 
-    constexpr index_t GemmCThreadCopyDstDataPerWrite_GemmN1 = 4;
+    constexpr index_t GemmCThreadCopyDstDataPerWrite_GemmN1 = 1;
 #endif
 
     constexpr index_t GcdStrideDilationH = math::gcd(ConvStrideH, ConvDilationH);
@@ -177,7 +168,7 @@ void device_convolution_backward_data_implicit_gemm_v2r1_nchw_kcyx_nkhw(InDesc i
     constexpr index_t HTildaSlice = HTildaRight - HTildaLeft;
     constexpr index_t WTildaSlice = WTildaRight - WTildaLeft;
 
-    constexpr index_t GemmM = C * YTilda * XTilda;
+    constexpr index_t GemmM = C;
     constexpr index_t GemmN = N * HTildaSlice * WTildaSlice;
 
     constexpr index_t GridSize = math::integer_divide_ceil(GemmM, GemmMPerBlock) *
@@ -185,40 +176,6 @@ void device_convolution_backward_data_implicit_gemm_v2r1_nchw_kcyx_nkhw(InDesc i
 
     printf("%s: BlockSize %u, GridSize %u \n", __func__, BlockSize, GridSize);
 
-    using gridwise_conv_bwd_data = GridwiseConvolutionBackwardDataImplicitGemm_v2r1_nchw_kcyx_nkhw<
-        GridSize,
-        BlockSize,
-        T,
-        T,
-        decltype(in_nchw_desc),
-        decltype(wei_kcyx_desc),
-        decltype(out_nkhw_desc),
-        ConvStrides,
-        ConvDilations,
-        InLeftPads,
-        InRightPads,
-        GemmMPerBlock,
-        GemmNPerBlock,
-        GemmKPerBlock,
-        GemmMPerThread,
-        GemmNPerThread,
-        GemmKPerThread,
-        GemmMLevel0Cluster,
-        GemmNLevel0Cluster,
-        GemmMLevel1Cluster,
-        GemmNLevel1Cluster,
-        GemmThreadGemmDataPerReadM,
-        GemmThreadGemmDataPerReadN,
-        GemmABlockCopyThreadSliceLengths_GemmK_GemmM,
-        GemmABlockCopyThreadClusterLengths_GemmK_GemmM,
-        GemmABlockCopySrcDataPerRead_GemmM,
-        GemmABlockCopyDstDataPerWrite_GemmM,
-        GemmBBlockCopyThreadSliceLengths_GemmK_GemmN,
-        GemmBBlockCopyThreadClusterLengths_GemmK_GemmN,
-        GemmBBlockCopySrcDataPerRead_GemmN,
-        GemmBBlockCopyDstDataPerWrite_GemmN,
-        GemmCThreadCopyDstDataPerWrite_GemmN1>;
-
     for(index_t i = 0; i < 5; ++i)
     {
         std::cout << "Start running " << nrepeat << " times..." << std::endl;
@@ -226,19 +183,65 @@ void device_convolution_backward_data_implicit_gemm_v2r1_nchw_kcyx_nkhw(InDesc i
         KernelTimer timer;
         timer.Start();
 
-        for(index_t j = 0; j < nrepeat; ++j)
+        for(index_t i = 0; i < nrepeat; ++i)
         {
-            launch_kernel(run_gridwise_operation<gridwise_conv_bwd_data,
-                                                 T* const __restrict__,
-                                                 const T* const __restrict__,
-                                                 const T* const __restrict__>,
-                          dim3(GridSize),
-                          dim3(BlockSize),
-                          0,
-                          0,
-                          static_cast<T*>(in_nchw_device_buf.GetDeviceBuffer()),
-                          static_cast<T*>(wei_kcyx_device_buf.GetDeviceBuffer()),
-                          static_cast<T*>(out_nkhw_device_buf.GetDeviceBuffer()));
+            using GridwiseConvBwdData =
+                GridwiseConvolutionBackwardDataImplicitGemm_v5r1_nhwc_kyxc_nhwk<
+                    GridSize,
+                    BlockSize,
+                    T,
+                    T,
+                    decltype(in_nhwc_desc),
+                    decltype(wei_kyxc_desc),
+                    decltype(out_nhwk_desc),
+                    ConvStrides,
+                    ConvDilations,
+                    InLeftPads,
+                    InRightPads,
+                    GemmMPerBlock,
+                    GemmNPerBlock,
+                    GemmKPerBlock,
+                    GemmMPerThread,
+                    GemmNPerThread,
+                    GemmKPerThread,
+                    GemmMLevel0Cluster,
+                    GemmNLevel0Cluster,
+                    GemmMLevel1Cluster,
+                    GemmNLevel1Cluster,
+                    GemmThreadGemmDataPerReadM,
+                    GemmThreadGemmDataPerReadN,
+                    GemmABlockCopyThreadSliceLengths_GemmK0_GemmK1_GemmK2_GemmM,
+                    GemmABlockCopyThreadClusterLengths_GemmK0_GemmK1_GemmK2_GemmM,
+                    GemmABlockCopySrcDataPerRead_GemmM,
+                    GemmABlockCopyDstDataPerWrite_GemmM,
+                    GemmBBlockCopyThreadSliceLengths_GemmK0_GemmK1_GemmK2_GemmN,
+                    GemmBBlockCopyThreadClusterLengths_GemmK0_GemmK1_GemmK2_GemmN,
+                    GemmBBlockCopySrcDataPerRead_GemmK2,
+                    GemmBBlockCopyDstDataPerWrite_GemmN,
+                    GemmCThreadCopyDstDataPerWrite_GemmN1>;
+
+            static_for<0, GridwiseConvBwdData::GetNumberOfGemm(), 1>{}([&](auto gemm_id) {
+                constexpr auto gemm_sizes        = GridwiseConvBwdData::GetGemmSize(gemm_id);
+                constexpr index_t gemm_k2        = gemm_sizes.At(4);
+                constexpr bool is_gemm_not_empty = gemm_k2 > 0;
+
+                // only compile and run if GEMM is no empty
+                static_if<is_gemm_not_empty>{}([&](auto fwd) {
+                    launch_kernel(run_gridwise_operation<GridwiseConvBwdData,
+                                                         T* const __restrict__,
+                                                         const T* const __restrict__,
+                                                         const T* const __restrict__,
+                                                         decltype(gemm_id)>,
+                                  dim3(GridSize),
+                                  dim3(BlockSize),
+                                  0,
+                                  0,
+                                  static_cast<T*>(in_nhwc_device_buf.GetDeviceBuffer()),
+                                  static_cast<T*>(wei_kyxc_device_buf.GetDeviceBuffer()),
+                                  static_cast<T*>(out_nhwk_device_buf.GetDeviceBuffer()),
+                                  fwd(gemm_id));
+                });
+            });
         }
 
         timer.End();
@@ -251,7 +254,13 @@ void device_convolution_backward_data_implicit_gemm_v2r1_nchw_kcyx_nkhw(InDesc i
         std::cout << "Average time : " << ave_time << " ms, " << perf << " TFlop/s" << std::endl;
     }
 
-    in_nchw_device_buf.FromDevice(in_nchw.mData.data());
+    in_nhwc_device_buf.FromDevice(in_nhwc.mData.data());
+
+    auto f_nhwc2nchw = [&](auto n, auto c, auto hi, auto wi) {
+        in_nchw(n, c, hi, wi) = in_nhwc(n, hi, wi, c);
+    };
+
+    make_ParallelTensorFunctor(f_nhwc2nchw, N, C, Hi, Wi)(std::thread::hardware_concurrency());
 }
 
 } // namespace launcher

driver/include/device_convolution_implicit_gemm_v4r1_nchw_kcyx_nkhw.hpp

@@ -133,7 +133,7 @@ void device_convolution_implicit_gemm_v4r1_nchw_kcyx_nkhw(InDesc,
 
     constexpr index_t WeiBlockCopySrcDataPerRead_E  = 2;
     constexpr index_t WeiBlockCopyDstDataPerWrite_K = 1;
-#elif 1
+#elif 0
     // cdata = 64, BlockSize = 256, 128x128x8
     constexpr index_t BlockSize = 256;
 
@@ -172,7 +172,7 @@ void device_convolution_implicit_gemm_v4r1_nchw_kcyx_nkhw(InDesc,
 
     constexpr index_t WeiBlockCopySrcDataPerRead_E  = 4;
     constexpr index_t WeiBlockCopyDstDataPerWrite_K = 1;
-#elif 0
+#elif 1
     // cdata = 64, BlockSize = 256, 128x128x16
     constexpr index_t BlockSize = 256;
 

driver/src/conv_bwd_data_driver.cpp

@@ -15,9 +15,8 @@
 #include "host_conv_bwd_data.hpp"
 #include "device_convolution_backward_data_implicit_gemm_v1r1_nchw_kcyx_nkhw.hpp"
 #include "device_convolution_backward_data_implicit_gemm_v1r2_nchw_kcyx_nkhw.hpp"
-#include "device_convolution_backward_data_implicit_gemm_v2r1_nchw_kcyx_nkhw.hpp"
-#include "device_convolution_backward_data_implicit_gemm_v3r1_nchw_kcyx_nkhw.hpp"
 #include "device_convolution_backward_data_implicit_gemm_v4r1_nchw_kcyx_nkhw.hpp"
+#include "device_convolution_backward_data_implicit_gemm_v5r1_nhwc_kyxc_nhwk.hpp"
 
 int main(int argc, char* argv[])
 {
@@ -55,7 +54,7 @@ int main(int argc, char* argv[])
 #elif 0
     // 3x3, 28x28
     constexpr index_t N  = 128;
-    constexpr index_t C  = 1024;
+    constexpr index_t C  = 256;
     constexpr index_t HI = 28;
     constexpr index_t WI = 28;
     constexpr index_t K  = 1024;
@@ -160,7 +159,7 @@ int main(int argc, char* argv[])
 #elif 0
     // 1x7 filter, 0x3 pad, 17x17 input
     constexpr index_t N  = 128;
-    constexpr index_t C  = 1024;
+    constexpr index_t C  = 256;
     constexpr index_t HI = 17;
     constexpr index_t WI = 17;
     constexpr index_t K  = 1024;
@@ -175,7 +174,7 @@ int main(int argc, char* argv[])
 #elif 0
     // 7x1 filter, 3x0 pad, 17x17 input
     constexpr index_t N  = 128;
-    constexpr index_t C  = 1024;
+    constexpr index_t C  = 256;
     constexpr index_t HI = 17;
     constexpr index_t WI = 17;
     constexpr index_t K  = 1024;
@@ -190,10 +189,10 @@ int main(int argc, char* argv[])
 #elif 1
     // 3x3 filter, 2x2 stride, 35x35 input, 17x17 output
     constexpr index_t N  = 128;
-    constexpr index_t C  = 128;
+    constexpr index_t C  = 256;
     constexpr index_t HI = 35;
     constexpr index_t WI = 35;
-    constexpr index_t K  = 1024;
+    constexpr index_t K  = 1280;
     constexpr index_t Y  = 3;
     constexpr index_t X  = 3;
 
@@ -247,14 +246,12 @@ int main(int argc, char* argv[])
 
 #if 0
     device_convolution_backward_data_implicit_gemm_v1r1_nchw_kcyx_nkhw
-#elif 1
-    device_convolution_backward_data_implicit_gemm_v1r2_nchw_kcyx_nkhw
 #elif 0
-    device_convolution_backward_data_implicit_gemm_v2r1_nchw_kcyx_nkhw
+    device_convolution_backward_data_implicit_gemm_v1r2_nchw_kcyx_nkhw
 #elif 0
-    device_convolution_backward_data_implicit_gemm_v3r1_nchw_kcyx_nkhw
-#elif 1
     device_convolution_backward_data_implicit_gemm_v4r1_nchw_kcyx_nkhw
+#elif 1
+    device_convolution_backward_data_implicit_gemm_v5r1_nhwc_kyxc_nhwk
 #endif
     (in_nchw_desc,
      in_nchw_device,