adding conv multiple d

example/09_convnd_fwd/convnd_fwd_xdl_fp16.cpp

@@ -4,6 +4,7 @@
 #include "convnd_fwd_common.hpp"
 
 #include "ck/tensor_operation/gpu/device/device_convnd_fwd_nwc_kxc_nwk_xdl.hpp"
+#include "ck/tensor_operation/gpu/device/device_convnd_fwd_multiple_d_nwc_kxc_nwk_xdl_cshuffle.hpp"
 
 using InDataType  = ck::half_t;
 using WeiDataType = ck::half_t;
@@ -20,6 +21,7 @@ using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
 static constexpr auto ConvFwdDefault =
     ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
 
+#if 0
 template <ck::index_t NDimSpatial>
 using DeviceConvNDFwdInstance = ck::tensor_operation::device::DeviceConvNdFwdNwcKxcNwk_Xdl<
     NDimSpatial,    //
@@ -56,6 +58,49 @@ using DeviceConvNDFwdInstance = ck::tensor_operation::device::DeviceConvNdFwdNwc
     true,           // BBlockLdsAddExtraN
     7,              // CThreadTransferSrcDstVectorDim
     1>;             // CThreadTransferDstScalarPerVector
+#else
+using CShuffleDataType = float;
+
+template <ck::index_t NDimSpatial>
+using DeviceConvNDFwdInstance =
+    ck::tensor_operation::device::DeviceConvNdFwdMultipleD_NwcKxcNwk_Xdl_CShuffle<
+        NDimSpatial,      //
+        InDataType,       //
+        WeiDataType,      //
+        AccDataType,      //
+        CShuffleDataType, //
+        ck::Tuple<>,
+        OutDataType,    //
+        InElementOp,    // Input Elementwise Operation
+        WeiElementOp,   // Weights Elementwise Operation
+        OutElementOp,   // Output Elementwise Operation
+        ConvFwdDefault, // ConvForwardSpecialization
+        256,            // BlockSize
+        128,            // MPerBlock
+        256,            // NPerBlock
+        4,              // K0PerBlock
+        8,              // K1
+        32,             // MPerXdl
+        32,             // NPerXdl
+        2,              // MXdlPerWave
+        4,              // NXdlPerWave
+        S<4, 64, 1>,    // ABlockTransferThreadClusterLengths_K0_M_K1
+        S<1, 0, 2>,     // ABlockTransferThreadClusterArrangeOrder
+        S<1, 0, 2>,     // ABlockTransferSrcAccessOrder
+        2,              // ABlockTransferSrcVectorDim
+        8,              // ABlockTransferSrcScalarPerVector
+        8,              // ABlockTransferDstScalarPerVector_K1
+        true,           // ABlockLdsAddExtraM
+        S<4, 64, 1>,    // BBlockTransferThreadClusterLengths_K0_N_K1
+        S<1, 0, 2>,     // BBlockTransferThreadClusterArrangeOrder
+        S<1, 0, 2>,     // BBlockTransferSrcAccessOrder
+        2,              // BBlockTransferSrcVectorDim
+        8,              // BBlockTransferSrcScalarPerVector
+        8,              // BBlockTransferDstScalarPerVector_K1
+        true,           // BBlockLdsAddExtraN
+        7,              // CThreadTransferSrcDstVectorDim
+        1>;             // CThreadTransferDstScalarPerVector
+#endif
 
 int main(int argc, char* argv[])
 {

include/ck/tensor_operation/gpu/device/device_convnd_fwd_multiple_d_nwc_kxc_nwk_xdl_cshuffle.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include <functional>
+#include <iostream>
+#include <iterator>
+#include <numeric>
+#include <sstream>
+
+#include "ck/utility/common_header.hpp"
+#include "ck/tensor_description/tensor_descriptor.hpp"
+#include "ck/tensor_description/tensor_descriptor_helper.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_conv_fwd.hpp"
+#include "ck/tensor_operation/gpu/device/convolution_forward_specialization.hpp"
+#include "ck/tensor_operation/gpu/grid/gridwise_gemm_xdlops_v2r3.hpp"
+#include "ck/device_utility/device_prop.hpp"
+#include "ck/device_utility/kernel_launch.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+
+//
+// @brief      Device Convolution operation.
+//
+// Supports:
+//  @li         Forward convolution with up to 3 spatial dimentions
+//  @li         Input tensor in NWC data format
+//  @li         Weight tensor in KXC data format
+//  @li         Output tensor in NWK data format
+//
+// 1D:
+// out[N, Wo, K] = in[N, Wi, C] * wei[K, X, C]
+// 2D:
+// out[N, Ho, Wo, K] = in[N, Hi, Wi, C] * wei[K, Y, X, C]
+// 3D:
+// out[N, Do, Ho, Wo, K] = in[N, Di, Hi, Wi, C] * wei[K, Z, Y, X, C]
+//
+template <ck::index_t NDimSpatial,
+          typename ADataType,
+          typename BDataType,
+          typename AccDataType,
+          typename CShuffleDataType,
+          typename DsDataType,
+          typename EDataType,
+          typename AElementwiseOperation,
+          typename BElementwiseOperation,
+          typename CDEElementwiseOperation,
+          ConvolutionForwardSpecialization ConvForwardSpecialization,
+          ck::index_t BlockSize,
+          ck::index_t MPerBlock,
+          ck::index_t NPerBlock,
+          ck::index_t K0PerBlock,
+          ck::index_t K1,
+          ck::index_t MPerXDL,
+          ck::index_t NPerXDL,
+          ck::index_t MXdlPerWave,
+          ck::index_t NXdlPerWave,
+          typename ABlockTransferThreadClusterLengths_K0_M_K1,
+          typename ABlockTransferThreadClusterArrangeOrder,
+          typename ABlockTransferSrcAccessOrder,
+          ck::index_t ABlockTransferSrcVectorDim,
+          ck::index_t ABlockTransferSrcScalarPerVector,
+          ck::index_t ABlockTransferDstScalarPerVector_K1,
+          bool ABlockLdsAddExtraM,
+          typename BBlockTransferThreadClusterLengths_K0_N_K1,
+          typename BBlockTransferThreadClusterArrangeOrder,
+          typename BBlockTransferSrcAccessOrder,
+          ck::index_t BBlockTransferSrcVectorDim,
+          ck::index_t BBlockTransferSrcScalarPerVector,
+          ck::index_t BBlockTransferDstScalarPerVector_K1,
+          bool BBlockLdsAddExtraN,
+          ck::index_t CThreadTransferSrcDstVectorDim,
+          ck::index_t CThreadTransferDstScalarPerVector>
+struct DeviceConvNdFwdMultipleD_NwcKxcNwk_Xdl_CShuffle
+    : public DeviceConvFwd<NDimSpatial,
+                           ck::tuple_element_t<NDimSpatial - 1,
+                                               ck::Tuple<ck::tensor_layout::convolution::NWC,
+                                                         ck::tensor_layout::convolution::NHWC,
+                                                         ck::tensor_layout::convolution::NDHWC>>,
+                           ck::tuple_element_t<NDimSpatial - 1,
+                                               ck::Tuple<ck::tensor_layout::convolution::KXC,
+                                                         ck::tensor_layout::convolution::KYXC,
+                                                         ck::tensor_layout::convolution::KZYXC>>,
+                           ck::tuple_element_t<NDimSpatial - 1,
+                                               ck::Tuple<ck::tensor_layout::convolution::NWK,
+                                                         ck::tensor_layout::convolution::NHWK,
+                                                         ck::tensor_layout::convolution::NDHWK>>,
+                           ADataType,
+                           BDataType,
+                           EDataType,
+                           AElementwiseOperation,
+                           BElementwiseOperation,
+                           CDEElementwiseOperation>
+{
+    using DeviceOp = DeviceConvNdFwdMultipleD_NwcKxcNwk_Xdl_CShuffle;
+
+    static constexpr auto I0 = Number<0>{};
+    static constexpr auto I1 = Number<1>{};
+    static constexpr auto I2 = Number<2>{};
+    static constexpr auto I3 = Number<3>{};
+
+    static constexpr auto K1Number     = Number<K1>{};
+    static constexpr auto GemmK1Number = K1Number;
+
+    static auto GetWeightTensorDescriptor(ck::index_t gemm_n, ck::index_t gemm_k)
+    {
+        const ck::index_t gemm_k0 = gemm_k / GemmK1Number;
+        const auto wei_k_yxc_grid_desc =
+            make_naive_tensor_descriptor_packed(make_tuple(gemm_n, gemm_k));
+
+        // wei_gemmk0_gemmn_gemmk1_grid_desc
+        return transform_tensor_descriptor(
+            wei_k_yxc_grid_desc,
+            make_tuple(make_unmerge_transform(make_tuple(gemm_k0, GemmK1Number)),
+                       make_pass_through_transform(gemm_n)),
+            make_tuple(Sequence<1>{}, Sequence<0>{}),
+            make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
+    }
+
+    static auto
+    GetOutputTensorDescriptor(ck::index_t gemm_m, ck::index_t gemm_n, ck::index_t gemm_m_pad)
+    {
+        const auto out_gemmmraw_gemmn_grid_desc =
+            make_naive_tensor_descriptor_packed(make_tuple(gemm_m, gemm_n));
+
+        // out_gemmm_gemmn_grid_desc
+        return transform_tensor_descriptor(out_gemmmraw_gemmn_grid_desc,
+                                           make_tuple(make_right_pad_transform(gemm_m, gemm_m_pad),
+                                                      make_pass_through_transform(gemm_n)),
+                                           make_tuple(Sequence<0>{}, Sequence<1>{}),
+                                           make_tuple(Sequence<0>{}, Sequence<1>{}));
+    }
+
+    template <ck::index_t NDim, typename std::enable_if<NDim == 1, bool>::type = false>
+    static auto GetInputTensorDescriptor(ck::index_t N,
+                                         ck::index_t C,
+                                         ck::index_t gemm_m,
+                                         ck::index_t gemm_k,
+                                         ck::index_t gemm_m_pad,
+                                         const std::vector<ck::index_t>& input_spatial_lengths,
+                                         const std::vector<ck::index_t>& filter_spatial_lengths,
+                                         const std::vector<ck::index_t>& output_spatial_lengths,
+                                         const std::vector<ck::index_t>& conv_filter_strides,
+                                         const std::vector<ck::index_t>& conv_filter_dilations,
+                                         const std::vector<ck::index_t>& input_left_pads,
+                                         const std::vector<ck::index_t>& input_right_pads)
+    {
+        const ck::index_t gemm_k0 = gemm_k / GemmK1Number;
+        const index_t Wi          = input_spatial_lengths[0];
+        const index_t Wo          = output_spatial_lengths[0];
+        const index_t ConvStrideW = conv_filter_strides[0];
+
+        if constexpr(ConvForwardSpecialization ==
+                     ConvolutionForwardSpecialization::Filter1x1Stride1Pad0)
+        {
+            const auto in_gemmmraw_gemmk_grid_desc =
+                make_naive_tensor_descriptor_packed(make_tuple(gemm_m, gemm_k));
+
+            // in_gemmk0_gemmm_gemmk1_grid_desc
+            return transform_tensor_descriptor(
+                in_gemmmraw_gemmk_grid_desc,
+                make_tuple(make_unmerge_transform(make_tuple(gemm_k0, GemmK1Number)),
+                           make_right_pad_transform(gemm_m, gemm_m_pad)),
+                make_tuple(Sequence<1>{}, Sequence<0>{}),
+                make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
+        }
+        else if constexpr(ConvForwardSpecialization ==
+                          ConvolutionForwardSpecialization::Filter1x1Pad0)
+        {
+            const auto in_n_wi_c_grid_desc =
+                make_naive_tensor_descriptor_packed(make_tuple(N, Wi, C));
+
+            const auto in_n_wo_c_grid_desc = transform_tensor_descriptor(
+                in_n_wi_c_grid_desc,
+                make_tuple(make_pass_through_transform(N),
+                           make_embed_transform(make_tuple(Wo), make_tuple(ConvStrideW)),
+                           make_pass_through_transform(C)),
+                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}),
+                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}));
+
+            const auto in_gemmk0_gemmmraw_gemmk1_grid_desc = transform_tensor_descriptor(
+                in_n_wo_c_grid_desc,
+                make_tuple(make_unmerge_transform(make_tuple(gemm_k0, GemmK1Number)),
+                           make_merge_transform(make_tuple(N, Wo))),
+                make_tuple(Sequence<2>{}, Sequence<0, 1>{}),
+                make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
+
+            // in_gemmk0_gemmm_gemmk1_grid_desc
+            return transform_tensor_descriptor(
+                in_gemmk0_gemmmraw_gemmk1_grid_desc,
+                make_tuple(make_pass_through_transform(gemm_k0),
+                           make_right_pad_transform(gemm_m, gemm_m_pad),
+                           make_pass_through_transform(GemmK1Number)),
+                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}),
+                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}));
+        }
+        else
+        {
+            const index_t X             = filter_spatial_lengths[0];
+            const index_t ConvDilationW = conv_filter_dilations[0];
+            const index_t InLeftPadW    = input_left_pads[0];
+            const index_t InRightPadW   = input_right_pads[0];
+
+            const auto in_n_wi_c_grid_desc =
+                make_naive_tensor_descriptor_packed(make_tuple(N, Wi, C));
+
+            const auto in_n_wip_c_grid_desc = transform_tensor_descriptor(
+                in_n_wi_c_grid_desc,
+                make_tuple(make_pass_through_transform(N),
+                           make_pad_transform(Wi, InLeftPadW, InRightPadW),
+                           make_pass_through_transform(C)),
+                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}),
+                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}));
+
+            const auto in_n_x_wo_c_grid_desc = transform_tensor_descriptor(
+                in_n_wip_c_grid_desc,
+                make_tuple(
+                    make_pass_through_transform(N),
+                    make_embed_transform(make_tuple(X, Wo), make_tuple(ConvDilationW, ConvStrideW)),
+                    make_pass_through_transform(C)),
+                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}),
+                make_tuple(Sequence<0>{}, Sequence<1, 2>{}, Sequence<3>{}));
+
+            const auto in_gemmk_gemmmraw_grid_desc =
+                transform_tensor_descriptor(in_n_x_wo_c_grid_desc,
+                                            make_tuple(make_merge_transform(make_tuple(X, C)),
+                                                       make_merge_transform(make_tuple(N, Wo))),
+                                            make_tuple(Sequence<1, 3>{}, Sequence<0, 2>{}),
+                                            make_tuple(Sequence<0>{}, Sequence<1>{}));
+
+            const auto in_gemmk0_gemmmraw_gemmk1_grid_desc = transform_tensor_descriptor(
+                in_gemmk_gemmmraw_grid_desc,
+                make_tuple(make_unmerge_transform(make_tuple(gemm_k0, GemmK1Number)),
+                           make_pass_through_transform(gemm_m)),
+                make_tuple(Sequence<0>{}, Sequence<1>{}),
+                make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
+
+            // in_gemmk0_gemmm_gemmk1_grid_desc
+            return transform_tensor_descriptor(
+                in_gemmk0_gemmmraw_gemmk1_grid_desc,
+                make_tuple(make_pass_through_transform(gemm_k0),
+                           make_right_pad_transform(gemm_m, gemm_m_pad),
+                           make_pass_through_transform(GemmK1Number)),
+                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}),
+                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}));
+        }
+    }
+
+    template <ck::index_t NDim, typename std::enable_if<NDim == 2, bool>::type = false>
+    static auto GetInputTensorDescriptor(ck::index_t N,
+                                         ck::index_t C,
+                                         ck::index_t gemm_m,
+                                         ck::index_t gemm_k,
+                                         ck::index_t gemm_m_pad,
+                                         const std::vector<ck::index_t>& input_spatial_lengths,
+                                         const std::vector<ck::index_t>& filter_spatial_lengths,
+                                         const std::vector<ck::index_t>& output_spatial_lengths,
+                                         const std::vector<ck::index_t>& conv_filter_strides,
+                                         const std::vector<ck::index_t>& conv_filter_dilations,
+                                         const std::vector<ck::index_t>& input_left_pads,
+                                         const std::vector<ck::index_t>& input_right_pads)
+    {
+        const ck::index_t gemm_k0 = gemm_k / GemmK1Number;
+        const index_t Hi          = input_spatial_lengths[0];
+        const index_t Wi          = input_spatial_lengths[1];
+
+        const index_t Ho = output_spatial_lengths[0];
+        const index_t Wo = output_spatial_lengths[1];
+
+        const index_t ConvStrideH = conv_filter_strides[0];
+        const index_t ConvStrideW = conv_filter_strides[1];
+
+        if constexpr(ConvForwardSpecialization ==
+                     ConvolutionForwardSpecialization::Filter1x1Stride1Pad0)
+        {
+            const auto in_gemmmraw_gemmk_grid_desc =
+                make_naive_tensor_descriptor_packed(make_tuple(gemm_m, gemm_k));
+
+            // in_gemmk0_gemmm_gemmk1_grid_desc
+            return transform_tensor_descriptor(
+                in_gemmmraw_gemmk_grid_desc,
+                make_tuple(make_unmerge_transform(make_tuple(gemm_k0, GemmK1Number)),
+                           make_right_pad_transform(gemm_m, gemm_m_pad)),
+                make_tuple(Sequence<1>{}, Sequence<0>{}),
+                make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
+        }
+        else if constexpr(ConvForwardSpecialization ==
+                          ConvolutionForwardSpecialization::Filter1x1Pad0)
+        {
+            const auto in_n_hi_wi_c_grid_desc =
+                make_naive_tensor_descriptor_packed(make_tuple(N, Hi, Wi, C));
+
+            const auto in_n_ho_wo_c_grid_desc = transform_tensor_descriptor(
+                in_n_hi_wi_c_grid_desc,
+                make_tuple(make_pass_through_transform(N),
+                           make_embed_transform(make_tuple(Ho), make_tuple(ConvStrideH)),
+                           make_embed_transform(make_tuple(Wo), make_tuple(ConvStrideW)),
+                           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_gemmk0_gemmmraw_gemmk1_grid_desc = transform_tensor_descriptor(
+                in_n_ho_wo_c_grid_desc,
+                make_tuple(make_unmerge_transform(make_tuple(gemm_k0, GemmK1Number)),
+                           make_merge_transform(make_tuple(N, Ho, Wo))),
+                make_tuple(Sequence<3>{}, Sequence<0, 1, 2>{}),
+                make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
+
+            // in_gemmk0_gemmm_gemmk1_grid_desc
+            return transform_tensor_descriptor(
+                in_gemmk0_gemmmraw_gemmk1_grid_desc,
+                make_tuple(make_pass_through_transform(gemm_k0),
+                           make_right_pad_transform(gemm_m, gemm_m_pad),
+                           make_pass_through_transform(GemmK1Number)),
+                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}),
+                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}));
+        }
+        else
+        {
+            const index_t Y = filter_spatial_lengths[0];
+            const index_t X = filter_spatial_lengths[1];
+
+            const index_t ConvDilationH = conv_filter_dilations[0];
+            const index_t ConvDilationW = conv_filter_dilations[1];
+
+            const index_t InLeftPadH = input_left_pads[0];
+            const index_t InLeftPadW = input_left_pads[1];
+
+            const index_t InRightPadH = input_right_pads[0];
+            const index_t InRightPadW = input_right_pads[1];
+
+            const auto in_n_hi_wi_c_grid_desc =
+                make_naive_tensor_descriptor_packed(make_tuple(N, Hi, Wi, C));
+
+            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_gemmmraw_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<0>{}, Sequence<1>{}));
+
+            const auto in_gemmk0_gemmmraw_gemmk1_grid_desc = transform_tensor_descriptor(
+                in_gemmk_gemmmraw_grid_desc,
+                make_tuple(make_unmerge_transform(make_tuple(gemm_k0, GemmK1Number)),
+                           make_pass_through_transform(gemm_m)),
+                make_tuple(Sequence<0>{}, Sequence<1>{}),
+                make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
+
+            // in_gemmk0_gemmm_gemmk1_grid_desc
+            return transform_tensor_descriptor(
+                in_gemmk0_gemmmraw_gemmk1_grid_desc,
+                make_tuple(make_pass_through_transform(gemm_k0),
+                           make_right_pad_transform(gemm_m, gemm_m_pad),
+                           make_pass_through_transform(GemmK1Number)),
+                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}),
+                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}));
+        }
+    }
+
+    template <ck::index_t NDim, typename std::enable_if<NDim == 3, bool>::type = false>
+    static auto GetInputTensorDescriptor(ck::index_t N,
+                                         ck::index_t C,
+                                         ck::index_t gemm_m,
+                                         ck::index_t gemm_k,
+                                         ck::index_t gemm_m_pad,
+                                         const std::vector<ck::index_t>& input_spatial_lengths,
+                                         const std::vector<ck::index_t>& filter_spatial_lengths,
+                                         const std::vector<ck::index_t>& output_spatial_lengths,
+                                         const std::vector<ck::index_t>& conv_filter_strides,
+                                         const std::vector<ck::index_t>& conv_filter_dilations,
+                                         const std::vector<ck::index_t>& input_left_pads,
+                                         const std::vector<ck::index_t>& input_right_pads)
+    {
+        const ck::index_t gemm_k0 = gemm_k / GemmK1Number;
+        const index_t Di          = input_spatial_lengths[0];
+        const index_t Hi          = input_spatial_lengths[1];
+        const index_t Wi          = input_spatial_lengths[2];
+
+        const index_t Do = output_spatial_lengths[0];
+        const index_t Ho = output_spatial_lengths[1];
+        const index_t Wo = output_spatial_lengths[2];
+
+        const index_t ConvStrideD = conv_filter_strides[0];
+        const index_t ConvStrideH = conv_filter_strides[1];
+        const index_t ConvStrideW = conv_filter_strides[2];
+
+        if constexpr(ConvForwardSpecialization ==
+                     ConvolutionForwardSpecialization::Filter1x1Stride1Pad0)
+        {
+            const auto in_gemmmraw_gemmk_grid_desc =
+                make_naive_tensor_descriptor_packed(make_tuple(gemm_m, gemm_k));
+
+            // in_gemmk0_gemmm_gemmk1_grid_desc
+            return transform_tensor_descriptor(
+                in_gemmmraw_gemmk_grid_desc,
+                make_tuple(make_unmerge_transform(make_tuple(gemm_k0, GemmK1Number)),
+                           make_right_pad_transform(gemm_m, gemm_m_pad)),
+                make_tuple(Sequence<1>{}, Sequence<0>{}),
+                make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
+        }
+        else if constexpr(ConvForwardSpecialization ==
+                          ConvolutionForwardSpecialization::Filter1x1Pad0)
+        {
+            const auto in_n_di_hi_wi_c_grid_desc =
+                make_naive_tensor_descriptor_packed(make_tuple(N, Di, Hi, Wi, C));
+
+            const auto in_n_do_ho_wo_c_grid_desc = transform_tensor_descriptor(
+                in_n_di_hi_wi_c_grid_desc,
+                make_tuple(make_pass_through_transform(N),
+                           make_embed_transform(make_tuple(Do), make_tuple(ConvStrideD)),
+                           make_embed_transform(make_tuple(Ho), make_tuple(ConvStrideH)),
+                           make_embed_transform(make_tuple(Wo), make_tuple(ConvStrideW)),
+                           make_pass_through_transform(C)),
+                make_tuple(
+                    Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}, Sequence<4>{}),
+                make_tuple(
+                    Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}, Sequence<4>{}));
+
+            const auto in_gemmk0_gemmmraw_gemmk1_grid_desc = transform_tensor_descriptor(
+                in_n_do_ho_wo_c_grid_desc,
+                make_tuple(make_unmerge_transform(make_tuple(gemm_k0, GemmK1Number)),
+                           make_merge_transform(make_tuple(N, Do, Ho, Wo))),
+                make_tuple(Sequence<4>{}, Sequence<0, 1, 2, 3>{}),
+                make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
+
+            // in_gemmk0_gemmm_gemmk1_grid_desc
+            return transform_tensor_descriptor(
+                in_gemmk0_gemmmraw_gemmk1_grid_desc,
+                make_tuple(make_pass_through_transform(gemm_k0),
+                           make_right_pad_transform(gemm_m, gemm_m_pad),
+                           make_pass_through_transform(GemmK1Number)),
+                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}),
+                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}));
+        }
+        else
+        {
+            const index_t Z = filter_spatial_lengths[0];
+            const index_t Y = filter_spatial_lengths[1];
+            const index_t X = filter_spatial_lengths[2];
+
+            const index_t ConvDilationD = conv_filter_dilations[0];
+            const index_t ConvDilationH = conv_filter_dilations[1];
+            const index_t ConvDilationW = conv_filter_dilations[2];
+
+            const index_t InLeftPadD = input_left_pads[0];
+            const index_t InLeftPadH = input_left_pads[1];
+            const index_t InLeftPadW = input_left_pads[2];
+
+            const index_t InRightPadD = input_right_pads[0];
+            const index_t InRightPadH = input_right_pads[1];
+            const index_t InRightPadW = input_right_pads[2];
+
+            const auto in_n_di_hi_wi_c_grid_desc =
+                make_naive_tensor_descriptor_packed(make_tuple(N, Di, Hi, Wi, C));
+
+            const auto in_n_hip_wip_c_grid_desc = transform_tensor_descriptor(
+                in_n_di_hi_wi_c_grid_desc,
+                make_tuple(make_pass_through_transform(N),
+                           make_pad_transform(Di, InLeftPadD, InRightPadD),
+                           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>{}, Sequence<4>{}),
+                make_tuple(
+                    Sequence<0>{}, Sequence<1>{}, Sequence<2>{}, Sequence<3>{}, Sequence<4>{}));
+
+            const auto in_n_z_do_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(Z, Do), make_tuple(ConvDilationD, ConvStrideD)),
+                    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>{}, Sequence<4>{}),
+                make_tuple(Sequence<0>{},
+                           Sequence<1, 2>{},
+                           Sequence<3, 4>{},
+                           Sequence<5, 6>{},
+                           Sequence<7>{}));
+
+            const auto in_gemmk_gemmmraw_grid_desc = transform_tensor_descriptor(
+                in_n_z_do_y_ho_x_wo_c_grid_desc,
+                make_tuple(make_merge_transform(make_tuple(Z, Y, X, C)),
+                           make_merge_transform(make_tuple(N, Do, Ho, Wo))),
+                make_tuple(Sequence<1, 3, 5, 7>{}, Sequence<0, 2, 4, 6>{}),
+                make_tuple(Sequence<0>{}, Sequence<1>{}));
+
+            const auto in_gemmk0_gemmmraw_gemmk1_grid_desc = transform_tensor_descriptor(
+                in_gemmk_gemmmraw_grid_desc,
+                make_tuple(make_unmerge_transform(make_tuple(gemm_k0, GemmK1Number)),
+                           make_pass_through_transform(gemm_m)),
+                make_tuple(Sequence<0>{}, Sequence<1>{}),
+                make_tuple(Sequence<0, 2>{}, Sequence<1>{}));
+
+            // in_gemmk0_gemmm_gemmk1_grid_desc
+            return transform_tensor_descriptor(
+                in_gemmk0_gemmmraw_gemmk1_grid_desc,
+                make_tuple(make_pass_through_transform(gemm_k0),
+                           make_right_pad_transform(gemm_m, gemm_m_pad),
+                           make_pass_through_transform(GemmK1Number)),
+                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}),
+                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}));
+        }
+    }
+
+    static index_t GetGemmMRaw(ck::index_t N,
+                               const std::vector<ck::index_t>& output_spatial_lengths)
+    {
+        return N * std::accumulate(std::begin(output_spatial_lengths),
+                                   std::end(output_spatial_lengths),
+                                   1,
+                                   std::multiplies<ck::index_t>());
+    }
+
+    static index_t GetGemmK(ck::index_t C, const std::vector<ck::index_t>& filter_spatial_lengths)
+    {
+        return C * std::accumulate(std::begin(filter_spatial_lengths),
+                                   std::end(filter_spatial_lengths),
+                                   1,
+                                   std::multiplies<ck::index_t>());
+    }
+
+    static auto
+    MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N(ck::index_t N,
+                                                    ck::index_t K,
+                                                    ck::index_t C,
+                                                    std::vector<ck::index_t> input_spatial_lengths,
+                                                    std::vector<ck::index_t> filter_spatial_lengths,
+                                                    std::vector<ck::index_t> output_spatial_lengths,
+                                                    std::vector<ck::index_t> conv_filter_strides,
+                                                    std::vector<ck::index_t> conv_filter_dilations,
+                                                    std::vector<ck::index_t> input_left_pads,
+                                                    std::vector<ck::index_t> input_right_pads)
+    {
+        using namespace ck;
+
+        const index_t GemmMRaw = GetGemmMRaw(N, output_spatial_lengths);
+        const index_t GemmN    = K;
+        const index_t GemmK    = GetGemmK(C, filter_spatial_lengths);
+
+        const auto GemmMPad = math::integer_least_multiple(GemmMRaw, MPerBlock) - GemmMRaw;
+
+        assert(GemmK % GemmK1Number == 0);
+
+        // C = A^T*B
+        // A:
+        const auto in_gemmk0_gemmm_gemmk1_grid_desc =
+            GetInputTensorDescriptor<NDimSpatial>(N,
+                                                  C,
+                                                  GemmMRaw,
+                                                  GemmK,
+                                                  GemmMPad,
+                                                  input_spatial_lengths,
+                                                  filter_spatial_lengths,
+                                                  output_spatial_lengths,
+                                                  conv_filter_strides,
+                                                  conv_filter_dilations,
+                                                  input_left_pads,
+                                                  input_right_pads);
+        // B:
+        const auto wei_gemmk0_gemmn_gemmk1_grid_desc = GetWeightTensorDescriptor(GemmN, GemmK);
+        // C:
+        const auto out_gemmm_gemmn_grid_desc = GetOutputTensorDescriptor(GemmMRaw, GemmN, GemmMPad);
+
+        return make_tuple(in_gemmk0_gemmm_gemmk1_grid_desc,
+                          wei_gemmk0_gemmn_gemmk1_grid_desc,
+                          out_gemmm_gemmn_grid_desc);
+    }
+
+    template <ck::index_t NDim, typename std::enable_if<NDim == 1, bool>::type = false>
+    static auto GetABCGridDesc()
+    {
+        return MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N(
+            1, 1, 1, {1}, {1}, {1}, {1}, {1}, {1}, {1});
+    }
+
+    template <ck::index_t NDim, typename std::enable_if<NDim == 2, bool>::type = false>
+    static auto GetABCGridDesc()
+    {
+        return MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N(
+            1, 1, 1, {1, 1}, {1, 1}, {1, 1}, {1, 1}, {1, 1}, {1, 1}, {1, 1});
+    }
+
+    template <ck::index_t NDim, typename std::enable_if<NDim == 3, bool>::type = false>
+    static auto GetABCGridDesc()
+    {
+        return MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N(
+            1, 1, 1, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1});
+    }
+
+    using ABCGridDescs = decltype(GetABCGridDesc<NDimSpatial>());
+
+    using AGridDesc_K0_M_K1 = remove_cvref_t<decltype(ABCGridDescs{}[I0])>;
+    using BGridDesc_K0_N_K1 = remove_cvref_t<decltype(ABCGridDescs{}[I1])>;
+    using CGridDesc_M_N     = remove_cvref_t<decltype(ABCGridDescs{}[I2])>;
+
+    using Block2CTileMap = BlockToCTileMap_M00_N0_M01<MPerBlock, NPerBlock, CGridDesc_M_N>;
+
+    // GridwiseGemm
+    using GridwiseGemm = GridwiseGemm_k0mk1_k0nk1_mn_xdlops_v2r3<
+        BlockSize,
+        ADataType, // TODO: distinguish A/B datatype
+        AccDataType,
+        EDataType,
+        InMemoryDataOperationEnum::Set,
+        AGridDesc_K0_M_K1,
+        BGridDesc_K0_N_K1,
+        CGridDesc_M_N,
+        AElementwiseOperation,
+        BElementwiseOperation,
+        CDEElementwiseOperation,
+        MPerBlock,
+        NPerBlock,
+        K0PerBlock,
+        MPerXDL,
+        NPerXDL,
+        K1,
+        MXdlPerWave,
+        NXdlPerWave,
+        ABlockTransferThreadClusterLengths_K0_M_K1,
+        Sequence<1, 0, 2>, // ABlockTransferThreadClusterArrangeOrder,
+        Sequence<1, 0, 2>, // ABlockTransferSrcAccessOrder,
+        2,                 // ABlockTransferSrcVectorDim,
+        ABlockTransferSrcScalarPerVector,
+        ABlockTransferDstScalarPerVector_K1,
+        false, // AThreadTransferSrcResetCoordinateAfterRun,
+        ABlockLdsAddExtraM,
+        BBlockTransferThreadClusterLengths_K0_N_K1,
+        Sequence<1, 0, 2>, // BBlockTransferThreadClusterArrangeOrder,
+        Sequence<1, 0, 2>, // BBlockTransferSrcAccessOrder,
+        2,                 // BBlockTransferSrcVectorDim,
+        BBlockTransferSrcScalarPerVector,
+        BBlockTransferDstScalarPerVector_K1,
+        false, // BThreadTransferSrcResetCoordinateAfterRun,
+        BBlockLdsAddExtraN,
+        Sequence<2, 3, 0, 1, 7, 5, 4, 6>, // CThreadTransferSrcDstAccessOrder,
+        7,                                // CThreadTransferSrcDstVectorDim,
+        CThreadTransferDstScalarPerVector>;
+
+    // Argument
+    struct Argument : public BaseArgument
+    {
+        Argument(const ADataType* p_in_grid,
+                 const BDataType* p_wei_grid,
+                 EDataType* p_out_grid,
+                 ck::index_t N,
+                 ck::index_t K,
+                 ck::index_t C,
+                 std::vector<ck::index_t> input_spatial_lengths,
+                 std::vector<ck::index_t> filter_spatial_lengths,
+                 std::vector<ck::index_t> output_spatial_lengths,
+                 std::vector<ck::index_t> conv_filter_strides,
+                 std::vector<ck::index_t> conv_filter_dilations,
+                 std::vector<ck::index_t> input_left_pads,
+                 std::vector<ck::index_t> input_right_pads,
+                 AElementwiseOperation in_element_op,
+                 BElementwiseOperation wei_element_op,
+                 CDEElementwiseOperation out_element_op)
+            : p_a_grid_{p_in_grid},
+              p_b_grid_{p_wei_grid},
+              p_c_grid_{p_out_grid},
+              a_grid_desc_k0_m_k1_{},
+              b_grid_desc_k0_n_k1_{},
+              c_grid_desc_m_n_{},
+              c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_{},
+              block_2_ctile_map_{},
+              in_element_op_{in_element_op},
+              wei_element_op_{wei_element_op},
+              out_element_op_{out_element_op},
+              Conv_N_{N},
+              Conv_K_{K},
+              Conv_C_{C},
+              filter_spatial_lengths_{filter_spatial_lengths},
+              conv_filter_strides_{conv_filter_strides},
+              input_left_pads_{input_left_pads},
+              input_right_pads_{input_right_pads}
+        {
+            const auto descs =
+                DeviceOp::MakeABCGridDescriptor_A_K0_M_K1_B_K0_N_K1_C_M_N(N,
+                                                                          K,
+                                                                          C,
+                                                                          input_spatial_lengths,
+                                                                          filter_spatial_lengths,
+                                                                          output_spatial_lengths,
+                                                                          conv_filter_strides,
+                                                                          conv_filter_dilations,
+                                                                          input_left_pads,
+                                                                          input_right_pads);
+
+            a_grid_desc_k0_m_k1_ = descs[I0];
+            b_grid_desc_k0_n_k1_ = descs[I1];
+            c_grid_desc_m_n_     = descs[I2];
+
+            block_2_ctile_map_ = Block2CTileMap{c_grid_desc_m_n_};
+
+            if(GridwiseGemm::CheckValidity(a_grid_desc_k0_m_k1_,
+                                           b_grid_desc_k0_n_k1_,
+                                           c_grid_desc_m_n_,
+                                           block_2_ctile_map_))
+            {
+                c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_ =
+                    GridwiseGemm::MakeCGridDescriptor_M0_N0_M1_N1_M2_M3_M4_N2(c_grid_desc_m_n_);
+            }
+        }
+
+        //  private:
+        const ADataType* p_a_grid_;
+        const BDataType* p_b_grid_;
+        EDataType* p_c_grid_;
+        AGridDesc_K0_M_K1 a_grid_desc_k0_m_k1_;
+        BGridDesc_K0_N_K1 b_grid_desc_k0_n_k1_;
+        CGridDesc_M_N c_grid_desc_m_n_;
+        typename GridwiseGemm::CGridDesc_M0_N0_M1_N1_M2_M3_M4_N2
+            c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_;
+        Block2CTileMap block_2_ctile_map_;
+        AElementwiseOperation in_element_op_;
+        BElementwiseOperation wei_element_op_;
+        CDEElementwiseOperation out_element_op_;
+        // for checking IsSupportedArgument()
+        index_t Conv_N_;
+        index_t Conv_K_;
+        index_t Conv_C_;
+        std::vector<index_t> filter_spatial_lengths_;
+        std::vector<index_t> conv_filter_strides_;
+        std::vector<index_t> input_left_pads_;
+        std::vector<index_t> input_right_pads_;
+    };
+
+    // Invoker
+    struct Invoker : public BaseInvoker
+    {
+        using Argument = DeviceOp::Argument;
+
+        float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
+        {
+#if 0
+            {
+                std::cout << "arg.a_grid_desc_k0_m_k1_{" << arg.a_grid_desc_k0_m_k1_.GetLength(I0)
+                          << ", " << arg.a_grid_desc_k0_m_k1_.GetLength(I1) << ", "
+                          << arg.a_grid_desc_k0_m_k1_.GetLength(I2) << "}" << std::endl;
+
+                std::cout << "arg.b_grid_desc_k0_n_k1_{" << arg.b_grid_desc_k0_n_k1_.GetLength(I0)
+                          << ", " << arg.b_grid_desc_k0_n_k1_.GetLength(I1) << ", "
+                          << arg.b_grid_desc_k0_n_k1_.GetLength(I2) << "}" << std::endl;
+
+                std::cout << "arg.c_grid_desc_m_n_{ " << arg.c_grid_desc_m_n_.GetLength(I0) << ", "
+                          << arg.c_grid_desc_m_n_.GetLength(I1) << "}" << std::endl;
+            }
+#endif
+            if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_,
+                                            arg.b_grid_desc_k0_n_k1_,
+                                            arg.c_grid_desc_m_n_,
+                                            arg.block_2_ctile_map_))
+            {
+                throw std::runtime_error(
+                    "wrong! GridwiseGemm_km_kn_m0m1n0n1_xdlops_v2r3 has invalid setting");
+            }
+
+            const index_t grid_size =
+                arg.block_2_ctile_map_.CalculateGridSize(arg.c_grid_desc_m_n_);
+
+            const auto K =
+                arg.a_grid_desc_k0_m_k1_.GetLength(I0) * arg.a_grid_desc_k0_m_k1_.GetLength(I2);
+
+            float ave_time = 0;
+
+            if(GridwiseGemm::CalculateHasMainKBlockLoop(K))
+            {
+                const auto kernel = kernel_gemm_xdlops_v2r3<
+                    GridwiseGemm,
+                    ADataType, // TODO: distiguish A/B datatype
+                    EDataType,
+                    remove_reference_t<DeviceOp::AGridDesc_K0_M_K1>,
+                    remove_reference_t<DeviceOp::BGridDesc_K0_N_K1>,
+                    remove_reference_t<typename GridwiseGemm::CGridDesc_M0_N0_M1_N1_M2_M3_M4_N2>,
+                    AElementwiseOperation,
+                    BElementwiseOperation,
+                    CDEElementwiseOperation,
+                    Block2CTileMap,
+                    true>;
+
+                ave_time = launch_and_time_kernel(stream_config,
+                                                  kernel,
+                                                  dim3(grid_size),
+                                                  dim3(BlockSize),
+                                                  0,
+                                                  arg.p_a_grid_,
+                                                  arg.p_b_grid_,
+                                                  arg.p_c_grid_,
+                                                  arg.a_grid_desc_k0_m_k1_,
+                                                  arg.b_grid_desc_k0_n_k1_,
+                                                  arg.c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_,
+                                                  arg.in_element_op_,
+                                                  arg.wei_element_op_,
+                                                  arg.out_element_op_,
+                                                  arg.block_2_ctile_map_);
+            }
+            else
+            {
+                const auto kernel = kernel_gemm_xdlops_v2r3<
+                    GridwiseGemm,
+                    ADataType, // TODO: distiguish A/B datatype
+                    EDataType,
+                    remove_reference_t<DeviceOp::AGridDesc_K0_M_K1>,
+                    remove_reference_t<DeviceOp::BGridDesc_K0_N_K1>,
+                    remove_reference_t<typename GridwiseGemm::CGridDesc_M0_N0_M1_N1_M2_M3_M4_N2>,
+                    AElementwiseOperation,
+                    BElementwiseOperation,
+                    CDEElementwiseOperation,
+                    Block2CTileMap,
+                    false>;
+
+                ave_time = launch_and_time_kernel(stream_config,
+                                                  kernel,
+                                                  dim3(grid_size),
+                                                  dim3(BlockSize),
+                                                  0,
+                                                  arg.p_a_grid_,
+                                                  arg.p_b_grid_,
+                                                  arg.p_c_grid_,
+                                                  arg.a_grid_desc_k0_m_k1_,
+                                                  arg.b_grid_desc_k0_n_k1_,
+                                                  arg.c_grid_desc_m0_n0_m1_n1_m2_m3_m4_n2_,
+                                                  arg.in_element_op_,
+                                                  arg.wei_element_op_,
+                                                  arg.out_element_op_,
+                                                  arg.block_2_ctile_map_);
+            }
+
+            return ave_time;
+        }
+
+        float Run(const BaseArgument* p_arg,
+                  const StreamConfig& stream_config = StreamConfig{}) override
+        {
+            return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
+        }
+    };
+
+    static constexpr bool IsValidCompilationParameter()
+    {
+        // TODO: properly implement this check
+        return true;
+    }
+
+    static bool IsSupportedArgument(const Argument& arg)
+    {
+        if(ck::get_device_name() == "gfx908")
+        {
+            if constexpr(!(is_same_v<AccDataType, float> || is_same_v<AccDataType, float> ||
+                           is_same_v<AccDataType, int32_t>))
+            {
+                return false;
+            }
+        }
+        else if(ck::get_device_name() == "gfx90a")
+        {
+            if constexpr(!(is_same_v<AccDataType, float> || is_same_v<AccDataType, float> ||
+                           is_same_v<AccDataType, int32_t> || is_same_v<AccDataType, double>))
+            {
+                return false;
+            }
+        }
+        else
+        {
+            return false;
+        }
+
+        // Input tensors can't be bigger than 2GB each.
+        constexpr ck::long_index_t GB2 = (ck::long_index_t{1} << 31);
+
+        if(arg.a_grid_desc_k0_m_k1_.GetElementSpaceSize() * sizeof(ADataType) > GB2 ||
+           arg.b_grid_desc_k0_n_k1_.GetElementSpaceSize() * sizeof(BDataType) > GB2 ||
+           arg.c_grid_desc_m_n_.GetElementSpaceSize() * sizeof(EDataType) > GB2)
+        {
+            return false;
+        }
+
+        if constexpr(ConvForwardSpecialization ==
+                     ConvolutionForwardSpecialization::Filter1x1Stride1Pad0)
+        {
+            // check if it's 1x1, stride=1 conv
+            for(ck::index_t i = 0; i < NDimSpatial; ++i)
+            {
+                if(!(arg.filter_spatial_lengths_[i] == 1 && arg.conv_filter_strides_[i] == 1 &&
+                     arg.input_left_pads_[i] == 0 && arg.input_right_pads_[i] == 0))
+                {
+                    return false;
+                }
+            }
+        }
+        else if constexpr(ConvForwardSpecialization ==
+                          ConvolutionForwardSpecialization::Filter1x1Pad0)
+        {
+            // check if it's 1x1 conv
+            for(ck::index_t i = 0; i < NDimSpatial; ++i)
+            {
+                if(!(arg.filter_spatial_lengths_[i] == 1 && arg.input_left_pads_[i] == 0 &&
+                     arg.input_right_pads_[i] == 0))
+                {
+                    return false;
+                }
+            }
+        }
+
+        // vector load A/B matrix from global memory
+        if(!(ABlockTransferSrcVectorDim == 2 && BBlockTransferSrcVectorDim == 2 &&
+             arg.Conv_C_ % ABlockTransferSrcScalarPerVector == 0 &&
+             arg.Conv_C_ % BBlockTransferSrcScalarPerVector == 0))
+        {
+            return false;
+        }
+
+        // vector store C matrix into global memory
+        if(!(arg.Conv_K_ % CThreadTransferDstScalarPerVector == 0))
+        {
+            return false;
+        }
+
+        // Gridwise GEMM size
+        return GridwiseGemm::CheckValidity(arg.a_grid_desc_k0_m_k1_,
+                                           arg.b_grid_desc_k0_n_k1_,
+                                           arg.c_grid_desc_m_n_,
+                                           arg.block_2_ctile_map_);
+    }
+
+    bool IsSupportedArgument(const BaseArgument* p_arg) override
+    {
+        return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
+    }
+
+    static auto MakeArgument(const ADataType* p_in_grid,
+                             const BDataType* p_wei_grid,
+                             EDataType* p_out_grid,
+                             ck::index_t N,
+                             ck::index_t K,
+                             ck::index_t C,
+                             std::vector<ck::index_t> input_spatial_lengths,
+                             std::vector<ck::index_t> filter_spatial_lengths,
+                             std::vector<ck::index_t> output_spatial_lengths,
+                             std::vector<ck::index_t> conv_filter_strides,
+                             std::vector<ck::index_t> conv_filter_dilations,
+                             std::vector<ck::index_t> input_left_pads,
+                             std::vector<ck::index_t> input_right_pads,
+                             AElementwiseOperation in_element_op,
+                             BElementwiseOperation wei_element_op,
+                             CDEElementwiseOperation out_element_op)
+    {
+        return Argument{p_in_grid,
+                        p_wei_grid,
+                        p_out_grid,
+                        N,
+                        K,
+                        C,
+                        input_spatial_lengths,
+                        filter_spatial_lengths,
+                        output_spatial_lengths,
+                        conv_filter_strides,
+                        conv_filter_dilations,
+                        input_left_pads,
+                        input_right_pads,
+                        in_element_op,
+                        wei_element_op,
+                        out_element_op};
+    }
+
+    static auto MakeInvoker() { return Invoker{}; }
+
+    std::unique_ptr<BaseArgument>
+    MakeArgumentPointer(const void* p_in_grid,
+                        const void* p_wei_grid,
+                        void* p_out_grid,
+                        ck::index_t N,
+                        ck::index_t K,
+                        ck::index_t C,
+                        std::vector<ck::index_t> input_spatial_lengths,
+                        std::vector<ck::index_t> filter_spatial_lengths,
+                        std::vector<ck::index_t> output_spatial_lengths,
+                        std::vector<ck::index_t> conv_filter_strides,
+                        std::vector<ck::index_t> conv_filter_dilations,
+                        std::vector<ck::index_t> input_left_pads,
+                        std::vector<ck::index_t> input_right_pads,
+                        AElementwiseOperation in_element_op,
+                        BElementwiseOperation wei_element_op,
+                        CDEElementwiseOperation out_element_op) override
+    {
+        return std::make_unique<Argument>(static_cast<const ADataType*>(p_in_grid),
+                                          static_cast<const BDataType*>(p_wei_grid),
+                                          static_cast<EDataType*>(p_out_grid),
+                                          N,
+                                          K,
+                                          C,
+                                          input_spatial_lengths,
+                                          filter_spatial_lengths,
+                                          output_spatial_lengths,
+                                          conv_filter_strides,
+                                          conv_filter_dilations,
+                                          input_left_pads,
+                                          input_right_pads,
+                                          in_element_op,
+                                          wei_element_op,
+                                          out_element_op);
+    }
+
+    std::unique_ptr<BaseInvoker> MakeInvokerPointer() override
+    {
+        return std::make_unique<Invoker>(Invoker{});
+    }
+
+    std::string GetTypeString() const override
+    {
+        auto str = std::stringstream();
+
+        // clang-format off
+        str << "DeviceConvNdFwdMultipleD_NwcKxcNwk_Xdl_CShuffle"
+            << "<"
+            << BlockSize << ", "
+            << MPerBlock << ", "
+            << NPerBlock << ", "
+            << K0PerBlock << ", "
+            << getConvForwardSpecializationString(ConvForwardSpecialization)
+            << ">";
+        // clang-format on
+
+        return str.str();
+    }
+};
+
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

include/ck/tensor_operation/gpu/device/device_gemm_multiple_d_xdl_cshuffle.hpp

@@ -127,14 +127,14 @@ template <typename ALayout,
           index_t ABlockTransferSrcVectorDim,
           index_t ABlockTransferSrcScalarPerVector,
           index_t ABlockTransferDstScalarPerVector_AK1,
-          bool ABlockLdsExtraM,
+          index_t ABlockLdsExtraM,
           typename BBlockTransferThreadClusterLengths_BK0_N_BK1,
           typename BBlockTransferThreadClusterArrangeOrder,
           typename BBlockTransferSrcAccessOrder,
           index_t BBlockTransferSrcVectorDim,
           index_t BBlockTransferSrcScalarPerVector,
           index_t BBlockTransferDstScalarPerVector_BK1,
-          bool BBlockLdsExtraN,
+          index_t BBlockLdsExtraN,
           index_t CShuffleMXdlPerWavePerShuffle,
           index_t CShuffleNXdlPerWavePerShuffle,
           typename CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,