Merge branch 'backward_weight_v4r4r4_xdlops' into wrw_nchw_ksplit

composable_kernel/include/problem_transform/transform_backward_weight_convolution_into_gemm_v4r4r4_nhwc_kyxc_nhwk.hpp

+#ifndef CK_TRANSFORM_BACKWARD_WEIGHT_CONVOLUTION_INTO_GEMM_V4R4R4_NHWC_KYXC_NHWK_HPP
+#define CK_TRANSFORM_BACKWARD_WEIGHT_CONVOLUTION_INTO_GEMM_V4R4R4_NHWC_KYXC_NHWK_HPP
+
+#include "common_header.hpp"
+#include "tensor_descriptor.hpp"
+#include "tensor_descriptor_helper.hpp"
+
+namespace ck {
+
+// A: in
+// B: wei
+// C: out
+// GemmM = N * Ho * Wo
+// GemmN = K
+// GemmK = Y * X * C
+template <typename... In,
+          typename... Wei,
+          typename... Out,
+          typename ConvStrides,
+          typename ConvDilations,
+          typename InLeftPads,
+          typename InRightPads,
+          index_t GemmK1Value>
+__host__ __device__ constexpr auto
+transform_backward_weight_convolution_into_gemm_v4r4r4_nhwc_kyxc_nhwk_pad(
+    const TensorDescriptor<In...>& in_n_hi_wi_c_grid_desc,
+    const TensorDescriptor<Wei...>& wei_k_y_x_c_grid_desc,
+    const TensorDescriptor<Out...>& out_n_ho_wo_k_grid_desc,
+    const ConvStrides& conv_strides,
+    const ConvDilations& conv_dilations,
+    const InLeftPads& in_left_pads,
+    const InRightPads& in_right_pads,
+    Number<GemmK1Value>)
+{
+    constexpr auto I0 = Number<0>{};
+    constexpr auto I1 = Number<1>{};
+    constexpr auto I2 = Number<2>{};
+    constexpr auto I3 = Number<3>{};
+
+    constexpr auto GemmK1 = Number<GemmK1Value>{};
+
+    const auto N = in_n_hi_wi_c_grid_desc.GetLength(I0);
+    const auto C = in_n_hi_wi_c_grid_desc.GetLength(I3);
+    const auto K = out_n_ho_wo_k_grid_desc.GetLength(I3);
+
+    const auto Hi = in_n_hi_wi_c_grid_desc.GetLength(I1);
+    const auto Wi = in_n_hi_wi_c_grid_desc.GetLength(I2);
+
+    const auto Ho = out_n_ho_wo_k_grid_desc.GetLength(I1);
+    const auto Wo = out_n_ho_wo_k_grid_desc.GetLength(I2);
+
+    const auto Y = wei_k_y_x_c_grid_desc.GetLength(I1);
+    const auto X = wei_k_y_x_c_grid_desc.GetLength(I2);
+
+    const auto ConvStrideH = conv_strides[I0];
+    const auto ConvStrideW = conv_strides[I1];
+
+    const auto ConvDilationH = conv_dilations[I0];
+    const auto ConvDilationW = conv_dilations[I1];
+
+    const auto InLeftPadH = in_left_pads[I0];
+    const auto InLeftPadW = in_left_pads[I1];
+
+    const auto InRightPadH = in_right_pads[I0];
+    const auto InRightPadW = in_right_pads[I1];
+
+    const auto GemmM  = Y * X * C;
+    const auto GemmN  = K;
+    const auto GemmK  = N * Ho * Wo;
+    const auto GemmK0 = GemmK / GemmK1;
+
+    // A: input tensor
+    const auto in_n_hip_wip_c_grid_desc = transform_tensor_descriptor(
+        in_n_hi_wi_c_grid_desc,
+        make_tuple(make_pass_through_transform(N),
+                   make_pad_transform(Hi, InLeftPadH, InRightPadH),
+                   make_pad_transform(Wi, InLeftPadW, InRightPadW),
+                   make_pass_through_transform(C)),
+        make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
+        make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}));
+
+    const auto in_n_y_ho_x_wo_c_grid_desc = transform_tensor_descriptor(
+        in_n_hip_wip_c_grid_desc,
+        make_tuple(make_pass_through_transform(N),
+                   make_embed_transform(make_tuple(Y, Ho), make_tuple(ConvDilationH, ConvStrideH)),
+                   make_embed_transform(make_tuple(X, Wo), make_tuple(ConvDilationW, ConvStrideW)),
+                   make_pass_through_transform(C)),
+        make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}),
+        make_tuple(Sequence<0>{}, Sequence<1, 2>{}, Sequence<3, 4>{}, Sequence<5>{}));
+
+    const auto in_gemmk_gemmm_grid_desc =
+        transform_tensor_descriptor(in_n_y_ho_x_wo_c_grid_desc,
+                                    make_tuple(make_merge_transform(make_tuple(Y, X, C)),
+                                               make_merge_transform(make_tuple(N, Ho, Wo))),
+                                    make_tuple(Sequence<1, 3, 5>{}, Sequence<0, 2, 4>{}),
+                                    make_tuple(Sequence<1>{}, Sequence<0>{}));
+
+    const auto in_gemmk0_gemmm_gemmk1_grid_desc =
+        transform_tensor_descriptor(in_gemmk_gemmm_grid_desc,
+                                    make_tuple(make_unmerge_transform(make_tuple(GemmK0, GemmK1)),
+                                               make_pass_through_transform(GemmM)),
+                                    make_tuple(Sequence<0>{}, Sequence<1>{}),
+                                    make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
+
+    // B: output tensor
+    const auto out_gemmk_gemmn_grid_desc = transform_tensor_descriptor(
+        make_naive_tensor_descriptor_packed(make_tuple(N * Ho * Wo, K)),
+        make_tuple(make_pass_through_transform(N * Ho * Wo), make_pass_through_transform(K)),
+        make_tuple(Sequence<0>{}, Sequence<1>{}),
+        make_tuple(Sequence<0>{}, Sequence<1>{}));
+
+    const auto out_gemmk0_gemmn_gemmk1_grid_desc =
+        transform_tensor_descriptor(out_gemmk_gemmn_grid_desc,
+                                    make_tuple(make_unmerge_transform(make_tuple(GemmK0, GemmK1)),
+                                               make_pass_through_transform(GemmN)),
+                                    make_tuple(Sequence<0>{}, Sequence<1>{}),
+                                    make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
+
+    // C: weight tensor
+    const auto wei_gemmm_gemmn_grid_desc = transform_tensor_descriptor(
+        make_naive_tensor_descriptor_packed(make_tuple(K, Y * X * C)),
+        make_tuple(make_pass_through_transform(K), make_pass_through_transform(Y * X * C)),
+        make_tuple(Sequence<0>{}, Sequence<1>{}),
+        make_tuple(Sequence<1>{}, Sequence<0>{}));
+
+    return make_tuple(in_gemmk0_gemmm_gemmk1_grid_desc,
+                      out_gemmk0_gemmn_gemmk1_grid_desc,
+                      wei_gemmm_gemmn_grid_desc);
+}
+
+} // namespace ck
+#endif

host/driver_offline/include/device_convolution_backward_weight_implicit_gemm_v4r4r4_xdlops_nhwc_kyxc_nhwk.hpp

+#include <unistd.h>
+#include "device.hpp"
+#include "host_tensor.hpp"
+#include "transform_backward_weight_convolution_into_gemm_v4r4r4_nhwc_kyxc_nhwk.hpp"
+#include "driver_gemm_xdlops_v2r3.hpp"
+
+template <typename TInWei,
+          typename TAcc,
+          typename TOut,
+          typename InLengths,
+          typename WeiLengths,
+          typename OutLengths,
+          typename ConvStrides,
+          typename ConvDilations,
+          typename InLeftPads,
+          typename InRightPads>
+void device_convolution_backward_weight_implicit_gemm_v4r4r4_xdlops_nhwc_kyxc_nhwk(
+    const InLengths& in_n_hi_wi_c_lengths,
+    const WeiLengths& wei_k_y_x_c_lengths,
+    const OutLengths& out_n_ho_wo_k_lengths,
+    const ConvStrides& conv_strides,
+    const ConvDilations& conv_dilations,
+    const InLeftPads& in_left_pads,
+    const InRightPads& in_right_pads,
+    const Tensor<TInWei>& in_n_hi_wi_c,
+    Tensor<TInWei>& wei_k_y_x_c,
+    const Tensor<TOut>& out_n_ho_wo_k,
+    ck::index_t nrepeat)
+{
+    using namespace ck;
+
+    std::cout << __func__ << std::endl;
+
+    constexpr auto I0 = Number<0>{};
+    constexpr auto I1 = Number<1>{};
+    constexpr auto I2 = Number<2>{};
+    constexpr auto I3 = Number<3>{};
+
+    DeviceMem in_n_hi_wi_c_device_buf(sizeof(TInWei) * in_n_hi_wi_c.mDesc.GetElementSpace());
+    DeviceMem wei_k_y_x_c_device_buf(sizeof(TInWei) * wei_k_y_x_c.mDesc.GetElementSpace());
+    DeviceMem out_n_ho_wo_k_device_buf(sizeof(TOut) * out_n_ho_wo_k.mDesc.GetElementSpace());
+
+    in_n_hi_wi_c_device_buf.ToDevice(in_n_hi_wi_c.mData.data());
+    wei_k_y_x_c_device_buf.ToDevice(wei_k_y_x_c.mData.data());
+    out_n_ho_wo_k_device_buf.ToDevice(out_n_ho_wo_k.mData.data());
+
+    const auto in_n_hi_wi_c_desc  = make_naive_tensor_descriptor_packed(in_n_hi_wi_c_lengths);
+    const auto wei_k_y_x_c_desc   = make_naive_tensor_descriptor_packed(wei_k_y_x_c_lengths);
+    const auto out_n_ho_wo_k_desc = make_naive_tensor_descriptor_packed(out_n_ho_wo_k_lengths);
+
+#if 0
+    // [M, N, K0, K1] = [256, 128, 4, 4] for fp32
+    constexpr index_t BlockSize = 256;
+
+    constexpr index_t GemmMPerBlock = 256;
+    constexpr index_t GemmNPerBlock = 128;
+    constexpr index_t GemmKPerBlock = 4;
+
+    constexpr index_t GemmMPerXDL = 32;
+    constexpr index_t GemmNPerXDL = 32;
+    constexpr index_t GemmK1       = 4;
+
+    constexpr index_t MRepeat = 4;
+    constexpr index_t NRepeat = 2;
+
+    using GemmABlockTransferThreadSliceLengths_GemmK0_GemmM_GemmK1   = Sequence<1, 4, 4>;
+    using GemmABlockTransferThreadClusterLengths_GemmK0_GemmM_GemmK1 = Sequence<4, 64, 1>;
+
+    constexpr index_t GemmABlockTransferSrcScalarPerVector_GemmM = 2;
+    constexpr index_t GemmABlockTransferDstScalarPerVector_GemmK1 = 4;
+
+    using GemmBBlockTransferThreadSliceLengths_GemmK0_GemmN_GemmK1   = Sequence<1, 2, 4>;
+    using GemmBBlockTransferThreadClusterLengths_GemmK0_GemmN_GemmK1 = Sequence<4, 64, 1>;
+
+    constexpr index_t GemmBBlockTransferSrcScalarPerVector_GemmN = 2;
+    constexpr index_t GemmBBlockTransferDstScalarPerVector_GemmK1 = 4;
+
+    constexpr index_t GemmCThreadTransferDstScalarPerVector = 1;
+#elif 1
+    // [M, N, K0, K1] = [128, 128, 4, 4] for fp32
+    constexpr index_t BlockSize = 256;
+
+    constexpr index_t GemmMPerBlock = 128;
+    constexpr index_t GemmNPerBlock = 128;
+    constexpr index_t GemmKPerBlock = 4;
+
+    constexpr index_t GemmMPerXDL = 32;
+    constexpr index_t GemmNPerXDL = 32;
+    constexpr index_t GemmK1      = 4;
+
+    constexpr index_t MRepeat = 2;
+    constexpr index_t NRepeat = 2;
+
+    using GemmABlockTransferThreadSliceLengths_GemmK0_GemmM_GemmK1   = Sequence<1, 4, 2>;
+    using GemmABlockTransferThreadClusterLengths_GemmK0_GemmM_GemmK1 = Sequence<4, 32, 2>;
+
+    constexpr index_t GemmABlockTransferSrcScalarPerVector_GemmM  = 4;
+    constexpr index_t GemmABlockTransferDstScalarPerVector_GemmK1 = 2;
+
+    using GemmBBlockTransferThreadSliceLengths_GemmK0_GemmN_GemmK1   = Sequence<1, 4, 2>;
+    using GemmBBlockTransferThreadClusterLengths_GemmK0_GemmN_GemmK1 = Sequence<4, 32, 2>;
+
+    constexpr index_t GemmBBlockTransferSrcScalarPerVector_GemmN  = 4;
+    constexpr index_t GemmBBlockTransferDstScalarPerVector_GemmK1 = 2;
+
+    constexpr index_t GemmCThreadTransferDstScalarPerVector = 1;
+
+#elif 0
+    // [M, N, K0, K1] = [128, 128, 4, 8] for fp16
+    constexpr index_t BlockSize = 256;
+
+    constexpr index_t GemmMPerBlock = 128;
+    constexpr index_t GemmNPerBlock = 128;
+    constexpr index_t GemmKPerBlock = 4;
+
+    constexpr index_t GemmMPerXDL = 32;
+    constexpr index_t GemmNPerXDL = 32;
+    constexpr index_t GemmK1      = 8;
+
+    constexpr index_t MRepeat = 2;
+    constexpr index_t NRepeat = 2;
+
+    using GemmABlockTransferThreadSliceLengths_GemmK0_GemmM_GemmK1   = Sequence<1, 4, 4>;
+    using GemmABlockTransferThreadClusterLengths_GemmK0_GemmM_GemmK1 = Sequence<4, 32, 2>;
+
+    constexpr index_t GemmABlockTransferSrcScalarPerVector_GemmM  = 4;
+    constexpr index_t GemmABlockTransferDstScalarPerVector_GemmK1 = 4;
+
+    using GemmBBlockTransferThreadSliceLengths_GemmK0_GemmN_GemmK1   = Sequence<1, 4, 4>;
+    using GemmBBlockTransferThreadClusterLengths_GemmK0_GemmN_GemmK1 = Sequence<4, 32, 2>;
+
+    constexpr index_t GemmBBlockTransferSrcScalarPerVector_GemmN  = 4;
+    constexpr index_t GemmBBlockTransferDstScalarPerVector_GemmK1 = 4;
+
+    constexpr index_t GemmCThreadTransferDstScalarPerVector = 1;
+#endif
+
+    const auto descs = transform_backward_weight_convolution_into_gemm_v4r4r4_nhwc_kyxc_nhwk_pad(
+        in_n_hi_wi_c_desc,
+        wei_k_y_x_c_desc,
+        out_n_ho_wo_k_desc,
+        conv_strides,
+        conv_dilations,
+        in_left_pads,
+        in_right_pads,
+        Number<GemmK1>{});
+
+    const auto in_gemmk0_gemmm_gemmk1_grid_desc  = descs[I0];
+    const auto out_gemmk0_gemmn_gemmk1_grid_desc = descs[I1];
+    const auto wei_gemmm_gemmn_grid_desc         = descs[I2];
+
+    // HACK: hacks that control index calculation when iterating over A, B, C matrix
+    constexpr auto in_gemmk0_gemmm_gemmk1_grid_step_hacks =
+        make_tuple(make_tuple(Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0>{},   // 0+: GemmK0
+                              Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0>{},   // 1+: GemmM
+                              Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0>{}),  // 2+: GemmK1
+                   make_tuple(Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0>{},   // 0-: GemmK0
+                              Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0>{},   // 1-: GemmM
+                              Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0>{})); // 2-: GemmK1
+
+    constexpr auto out_gemmk0_gemmn_gemmk1_grid_step_hacks =
+        make_tuple(make_tuple(Sequence<0, 0, 0, 0, 0>{},   // 0+: GemmK0
+                              Sequence<0, 0, 0, 0, 0>{},   // 1+: GemmN
+                              Sequence<0, 0, 0, 0, 0>{}),  // 2+: GemmK1
+                   make_tuple(Sequence<0, 0, 0, 0, 0>{},   // 0-: GemmK0
+                              Sequence<0, 0, 0, 0, 0>{},   // 1-: GemmN
+                              Sequence<0, 0, 0, 0, 0>{})); // 2-: GemmK1
+
+    constexpr auto wei_m0_n0_m1_n1_m2_m3_m4_n2_grid_step_hacks =
+        make_tuple(make_tuple(Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{},   // 0+: M0
+                              Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{},   // 1+: N0
+                              Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{},   // 2+: M1
+                              Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{},   // 3+: N1
+                              Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{},   // 4+: M2
+                              Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{},   // 5+: M3
+                              Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{},   // 6+: M4
+                              Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{}),  // 7+: N2
+                   make_tuple(Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{},   // 0-: M0
+                              Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{},   // 1-: N0
+                              Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{},   // 2-: M1
+                              Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{},   // 3-: N1
+                              Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{},   // 4-: M2
+                              Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{},   // 5-: M3
+                              Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{},   // 6-: M4
+                              Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0>{})); // 7-: N2
+
+    constexpr auto in_gemmk0_gemmm_gemmk1_grid_move_slice_window_step_hacks =
+        Sequence<0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 1, 0, 0>{};
+
+    constexpr auto out_gemmk0_gemmn_gemmk1_grid_move_slice_window_step_hacks =
+        Sequence<0, 0, 0, 0, 0>{};
+
+    for(index_t i = 0; i < 5; ++i)
+    {
+        float ave_time = driver_gemm_xdlops_v2r3<
+            BlockSize,
+            TInWei,
+            TAcc,
+            TOut,
+            InMemoryDataOperationEnum_t::Set,
+            decltype(in_gemmk0_gemmm_gemmk1_grid_desc),
+            decltype(out_gemmk0_gemmn_gemmk1_grid_desc),
+            decltype(wei_gemmm_gemmn_grid_desc),
+            GemmMPerBlock,
+            GemmNPerBlock,
+            GemmKPerBlock,
+            GemmMPerXDL,
+            GemmNPerXDL,
+            GemmK1,
+            MRepeat,
+            NRepeat,
+            GemmABlockTransferThreadSliceLengths_GemmK0_GemmM_GemmK1,
+            GemmABlockTransferThreadClusterLengths_GemmK0_GemmM_GemmK1,
+            Sequence<0, 2, 1>,
+            Sequence<0, 2, 1>,
+            1,
+            GemmABlockTransferSrcScalarPerVector_GemmM,
+            GemmABlockTransferDstScalarPerVector_GemmK1,
+            false, // don't move back src coordinate after threadwise copy
+            GemmBBlockTransferThreadSliceLengths_GemmK0_GemmN_GemmK1,
+            GemmBBlockTransferThreadClusterLengths_GemmK0_GemmN_GemmK1,
+            Sequence<0, 2, 1>,
+            Sequence<0, 2, 1>,
+            1,
+            GemmBBlockTransferSrcScalarPerVector_GemmN,
+            GemmBBlockTransferDstScalarPerVector_GemmK1,
+            false, // don't move back src coordinate after threadwise copy
+            Sequence<2, 3, 0, 1, 7, 5, 4, 6>,
+            7,
+            GemmCThreadTransferDstScalarPerVector,
+            decltype(in_gemmk0_gemmm_gemmk1_grid_step_hacks),
+            decltype(out_gemmk0_gemmn_gemmk1_grid_step_hacks),
+            decltype(wei_m0_n0_m1_n1_m2_m3_m4_n2_grid_step_hacks),
+            decltype(in_gemmk0_gemmm_gemmk1_grid_move_slice_window_step_hacks),
+            decltype(out_gemmk0_gemmn_gemmk1_grid_move_slice_window_step_hacks),
+            false // CAccessOrderMRepeatNRepeat
+            >(static_cast<TInWei*>(in_n_hi_wi_c_device_buf.GetDeviceBuffer()),
+              static_cast<TOut*>(out_n_ho_wo_k_device_buf.GetDeviceBuffer()),
+              static_cast<TInWei*>(wei_k_y_x_c_device_buf.GetDeviceBuffer()),
+              in_gemmk0_gemmm_gemmk1_grid_desc,
+              out_gemmk0_gemmn_gemmk1_grid_desc,
+              wei_gemmm_gemmn_grid_desc,
+              in_gemmk0_gemmm_gemmk1_grid_step_hacks,
+              out_gemmk0_gemmn_gemmk1_grid_step_hacks,
+              wei_m0_n0_m1_n1_m2_m3_m4_n2_grid_step_hacks,
+              in_gemmk0_gemmm_gemmk1_grid_move_slice_window_step_hacks,
+              out_gemmk0_gemmn_gemmk1_grid_move_slice_window_step_hacks,
+              nrepeat);
+
+        {
+            const auto N = out_n_ho_wo_k_lengths[I0];
+            const auto K = out_n_ho_wo_k_lengths[I3];
+            const auto C = wei_k_y_x_c_lengths[I3];
+
+            const auto Ho = out_n_ho_wo_k_lengths[I1];
+            const auto Wo = out_n_ho_wo_k_lengths[I2];
+
+            const auto Y = wei_k_y_x_c_lengths[I1];
+            const auto X = wei_k_y_x_c_lengths[I2];
+
+            float perf = static_cast<float>((std::size_t(2) * N * K * Ho * Wo * C * Y * X)) /
+                         (std::size_t(1000) * 1000 * 1000) / ave_time;
+
+            std::cout << "Average time : " << ave_time << " ms, " << perf << " TFlop/s"
+                      << std::endl;
+        }
+    }
+
+    // copy result back to host
+    wei_k_y_x_c_device_buf.FromDevice(wei_k_y_x_c.mData.data());
+}

host/driver_offline/src/conv_wrw_driver_offline.cpp

@@ -13,15 +13,18 @@
 #include "host_conv_bwd_weight.hpp"
 #include "device_tensor.hpp"
 #include "device_convolution_backward_weight_implicit_gemm_v4r4r2_xdlops_nchw_kcyx_nkhw.hpp"
+#include "device_convolution_backward_weight_implicit_gemm_v4r4r4_xdlops_nhwc_kyxc_nhwk.hpp"
 #include "device_convolution_backward_weight_implicit_gemm_v4r4r2_xdlops_atomic_nchw_kcyx_nkhw.hpp"
 
 #define USE_DYNAMIC_MODE 1
 #define USE_CONV_WRW_V4R4R2_XDL_NCHW 1
+#define USE_CONV_WRW_V4R4R4_XDL_NHWC 1
 #define USE_CONV_WRW_V4R4R2_XDL_ATOMIC_NCHW 1
 
 enum ConvBackwardWeightAlgo
 {
     V4R4R2XDLNCHW,
+    V4R4R4XDLNHWC,
     V4R4R2XDLATOMICNCHW,
 };
 
@@ -233,6 +236,25 @@ int main(int argc, char* argv[])
                           in_right_pads_dev);
     };
 
+    auto f_make_for_device_nhwc = [&]() {
+        const auto in_lengths_dev     = make_tuple(N, Hi, Wi, C);
+        const auto wei_lengths_dev    = make_tuple(K, Y, X, C);
+        const auto out_lengths_dev    = make_tuple(N, Ho, Wo, K);
+        const auto conv_strides_dev   = make_tuple(conv_stride_h, conv_stride_w);
+        const auto conv_dilations_dev = make_tuple(conv_dilation_h, conv_dilation_w);
+        const auto in_left_pads_dev   = make_tuple(in_left_pad_h, in_left_pad_w);
+        const auto in_right_pads_dev  = make_tuple(in_right_pad_h, in_right_pad_w);
+
+        return make_tuple(in_lengths_dev,
+                          wei_lengths_dev,
+                          out_lengths_dev,
+                          conv_strides_dev,
+                          conv_dilations_dev,
+                          in_left_pads_dev,
+                          in_right_pads_dev);
+    };
+    
+    
     // set zero to wei_device
     wei_device.GenerateTensorValue(GeneratorTensor_0{}, num_thread);
 #if USE_CONV_WRW_V4R4R2_XDL_NCHW
@@ -262,6 +284,34 @@ int main(int argc, char* argv[])
     }
 #endif
 
+
+#if USE_CONV_WRW_V4R4R4_XDL_NHWC
+    if(algo == ConvBackwardWeightAlgo::V4R4R4XDLNHWC)
+    {
+        if(layout != ConvTensorLayout::NHWC)
+        {
+            throw std::runtime_error("wrong! layout");
+        }
+
+        const auto tmp = f_make_for_device_nhwc();
+
+        device_convolution_backward_weight_implicit_gemm_v4r4r4_xdlops_nhwc_kyxc_nhwk<in_data_t,
+                                                                                      acc_data_t,
+                                                                                      out_data_t>(
+            tmp[I0],
+            tmp[I1],
+            tmp[I2],
+            tmp[I3],
+            tmp[I4],
+            tmp[I5],
+            tmp[I6],
+            in,
+            wei_device,
+            out,
+            nrepeat);
+    }
+#endif
+
 #if USE_CONV_WRW_V4R4R2_XDL_ATOMIC_NCHW
     if(algo == ConvBackwardWeightAlgo::V4R4R2XDLATOMICNCHW)
     {