adding implicit gemm v4r3

composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v4r2_nchw_kcyx_nkhw_lds_double_buffer.hpp

@@ -181,7 +181,7 @@ struct GridwiseConvolutionImplicitGemm_v4r2_nchw_kcyx_nkhw_lds_double_buffer
             InBlockCopyDataPerAccess_W2>({0, 0, 0, 0, b_block_data_on_global, 0, 0, 0},
                                          {0, 0, 0, 0, 0, 0, 0, 0});
 
-#if 1
+#if 0
         {
             printf("id (%d %d), in offset: %d %d\n", get_block_1d_id(), get_thread_local_1d_id(),  blockwise_in_copy.mThreadSrcOffset, blockwise_in_copy.mThreadDstOffset);
         }

composable_kernel/include/kernel_algorithm/gridwise_convolution_implicit_gemm_v4r3_nchw_kcyx_nkhw_lds_double_buffer.hpp

+#ifndef CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V4R3_NCHW_KCYX_NKHW_LDS_DOUBLE_BUFFER
+#define CK_GRIDWISE_CONVOLUTION_IMPLICIT_GEMM_V4R3_NCHW_KCYX_NKHW_LDS_DOUBLE_BUFFER
+
+#include "common_header.hpp"
+#include "ConstantTensorDescriptor.hpp"
+#include "ConstantMergedTensorDescriptor.hpp"
+#include "ConstantMatrixDescriptor.hpp"
+#include "blockwise_generic_tensor_slice_copy.hpp"
+#include "blockwise_gemm.hpp"
+#include "threadwise_generic_tensor_slice_copy.hpp"
+
+namespace ck {
+
+template <index_t GridSize,
+          index_t BlockSize,
+          class Float,
+          class InGlobalDesc,
+          class WeiGlobalDesc,
+          class OutGlobalDesc,
+          class ConvStrides,
+          class ConvDilations,
+          index_t N0,
+          index_t N1,
+          index_t N2,
+          index_t Ho0,
+          index_t Ho1,
+          index_t Ho2,
+          index_t Wo0,
+          index_t Wo1,
+          index_t Wo2,
+          index_t BPerBlock,
+          index_t KPerBlock,
+          index_t EPerBlock,
+          index_t GemmMPerThreadSubC,
+          index_t GemmNPerThreadSubC,
+          index_t GemmMLevel0Cluster,
+          index_t GemmNLevel0Cluster,
+          index_t GemmMLevel1Cluster,
+          index_t GemmNLevel1Cluster,
+          index_t GemmKPerThreadLoop,
+          index_t GemmDataPerReadA,
+          index_t GemmDataPerReadB,
+          class InBlockCopySubLengths_E_N1_Ho1_Wo1_B_N2_Ho2_Wo2,
+          class InBlockCopyClusterLengths_E_N1_Ho1_Wo1_B_N2_Ho2_Wo2,
+          class InBlockCopyThreadClusterArrangeOrder,
+          class InBlockCopySrcAccessOrder,
+          class InBlockCopyDstAccessOrder,
+          index_t InBlockCopyDataPerAccess_W2,
+          class WeiBlockCopySubLengths_E_K,
+          class WeiBlockCopyClusterLengths_E_K,
+          class WeiBlockCopyThreadClusterArrangeOrder,
+          class WeiBlockCopySrcAccessOrder,
+          class WeiBlockCopyDstAccessOrder,
+          index_t WeiBlockCopySrcDataPerRead_E,
+          index_t WeiBlockCopyDstDataPerWrite_K>
+struct GridwiseConvolutionImplicitGemm_v4r3_nchw_kcyx_nkhw_lds_double_buffer
+{
+    __device__ void Run(const Float* const __restrict__ p_in_global,
+                        const Float* const __restrict__ p_wei_global,
+                        Float* const __restrict__ p_out_global) const
+    {
+        // this is a mess
+        // TODO: find more elegent way of specifying (or calculating) performance parameters
+        static_assert(N2 * Ho2 * Wo2 == GemmNPerThreadSubC, "wrong!");
+        static_assert((N1 * Ho1 * Wo1 * BPerBlock * N2 * Ho2 * Wo2) %
+                              (GemmNPerThreadSubC * GemmNLevel0Cluster * GemmNLevel1Cluster) ==
+                          0,
+                      "wrong!");
+
+        constexpr auto I0 = Number<0>{};
+        constexpr auto I1 = Number<1>{};
+        constexpr auto I2 = Number<2>{};
+        constexpr auto I3 = Number<3>{};
+        constexpr auto I5 = Number<5>{};
+        constexpr auto I7 = Number<7>{};
+
+        constexpr auto True = integral_constant<bool, true>{};
+
+        constexpr auto in_n_c_h_w_global_desc  = InGlobalDesc{};
+        constexpr auto wei_k_c_y_x_global_desc = WeiGlobalDesc{};
+        constexpr auto out_n_k_h_w_global_desc = OutGlobalDesc{};
+
+        constexpr index_t N = in_n_c_h_w_global_desc.GetLengths()[0];
+        constexpr index_t C = in_n_c_h_w_global_desc.GetLengths()[1];
+
+        constexpr index_t K  = out_n_k_h_w_global_desc.GetLengths()[1];
+        constexpr index_t Ho = out_n_k_h_w_global_desc.GetLengths()[2];
+        constexpr index_t Wo = out_n_k_h_w_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];
+
+        constexpr index_t E = C * Y * X;
+
+        constexpr index_t B = N0 * Ho0 * Wo0;
+
+        static_assert(N == N0 * N1 * N2 && Ho == Ho * Ho1 * Ho2 && Wo == Wo0 * Wo1 * Wo2, "wrong!");
+
+        static_assert((X == 1 || ConvDilationW % InBlockCopyDataPerAccess_W2 == 0),
+                      "wrong! aligment requirement for vectorized global load of input tensor will "
+                      "be violated");
+
+        // divide block work by [K, B]
+        static_assert(K % KPerBlock == 0 && B % BPerBlock == 0 && E % (2 * EPerBlock) == 0,
+                      "wrong! cannot divide work evenly among block");
+
+        constexpr index_t KBlockWork = K / KPerBlock;
+        constexpr index_t BBlockWork = B / BPerBlock;
+
+        constexpr auto block_work_desc =
+            make_ConstantTensorDescriptor_packed(Sequence<KBlockWork, BBlockWork>{});
+
+        const auto block_work_multi_id =
+            block_work_desc.GetMultiIndexFrom1dIndex(get_block_1d_id());
+
+        const index_t k_block_data_on_global = block_work_multi_id[0] * KPerBlock;
+        const index_t b_block_data_on_global = block_work_multi_id[1] * BPerBlock;
+
+        // input tensor
+        //     tensor descriptor in device memory [N0, N1, N2, Ho0, Ho1, Ho2, Wo0, Wo1, Wo2]
+        constexpr auto in_n0_n1_n2_ho0_ho1_ho2_wo0_wo1_wo2_global_desc =
+            in_n_c_h_w_global_desc.Extract(I0, I2, I3)
+                .StridedSlice(I1, Number<Ho>{}, Number<ConvStrideH>{})
+                .StridedSlice(I2, Number<Wo>{}, Number<ConvStrideW>{})
+                .Fold(I2, Number<Wo1>{}, Number<Wo2>{})
+                .Fold(I1, Number<Ho1>{}, Number<Ho2>{})
+                .Fold(I0, Number<N1>{}, Number<N2>{});
+
+        constexpr auto in_n1_ho1_wo1_n0_ho0_wo0_n2_ho2_wo2_global_desc =
+            in_n0_n1_n2_ho0_ho1_ho2_wo0_wo1_wo2_global_desc.ReorderGivenNew2Old(
+                Sequence<1, 4, 7, 0, 3, 6, 2, 5, 8>{});
+
+        //     batch descritpor for device memory
+        constexpr auto in_c_y_x_global_desc =
+            in_n_c_h_w_global_desc.StridedSlice(I2, Number<Y>{}, Number<ConvDilationH>{})
+                .StridedSlice(I3, Number<X>{}, Number<ConvDilationW>{})
+                .Extract(Sequence<1, 2, 3>{});
+
+        //     merged tensor descriptor in device memory [E, N1, B, N2], src of blockwise copy
+        constexpr auto in_e_n1_ho1_wo1_b_n2_ho2_wo2_global_merged_desc =
+            make_ConstantMergedTensorDescriptor(
+                in_c_y_x_global_desc.Embed(in_n1_ho1_wo1_n0_ho0_wo0_n2_ho2_wo2_global_desc),
+                Sequence<0, 1, 2>{},
+                Sequence<3>{},
+                Sequence<4>{},
+                Sequence<5>{},
+                Sequence<6, 7, 8>{},
+                Sequence<9>{},
+                Sequence<10>{},
+                Sequence<11>{});
+
+        //     memory layout descriptor in LDS [E, N1, B, N2], dst of blockwise copy
+        //     be careful of LDS alignment
+        constexpr auto in_e_n1_ho1_wo1_b_n2_ho2_wo2_block_desc =
+            make_ConstantTensorDescriptor_packed(
+                Sequence<EPerBlock, N1, Ho1, Wo1, BPerBlock, N2, Ho2, Wo2>{});
+
+        // input blockwise copy
+        //     slice a merged tensor, reorder and copy to a normal tensor
+        //     this copy operator already has blockwise offset built-in
+        auto blockwise_in_copy = BlockwiseGenericTensorSliceCopy_v1<
+            BlockSize,
+            Float,
+            decltype(in_e_n1_ho1_wo1_b_n2_ho2_wo2_global_merged_desc),
+            decltype(in_e_n1_ho1_wo1_b_n2_ho2_wo2_block_desc),
+            decltype(in_e_n1_ho1_wo1_b_n2_ho2_wo2_block_desc.GetLengths()),
+            InBlockCopySubLengths_E_N1_Ho1_Wo1_B_N2_Ho2_Wo2,
+            InBlockCopyClusterLengths_E_N1_Ho1_Wo1_B_N2_Ho2_Wo2,
+            InBlockCopyThreadClusterArrangeOrder,
+            InBlockCopySrcAccessOrder,
+            InBlockCopyDstAccessOrder,
+            InBlockCopyDataPerAccess_W2,
+            InBlockCopyDataPerAccess_W2>({0, 0, 0, 0, b_block_data_on_global, 0, 0, 0},
+                                         {0, 0, 0, 0, 0, 0, 0, 0});
+
+#if 0
+        {
+            printf("id (%d %d), in offset: %d %d\n", get_block_1d_id(), get_thread_local_1d_id(),  blockwise_in_copy.mThreadSrcOffset, blockwise_in_copy.mThreadDstOffset);
+        }
+#endif
+
+        // weight tensor
+        //     tensor descriptor in device memory, src of blockwise copy
+        constexpr auto wei_e_k_global_desc =
+            wei_k_c_y_x_global_desc.Unfold(I1, I3).ReorderGivenNew2Old(Sequence<1, 0>{});
+
+        //     tensor descriptor in LDS, dst of blockwise copy
+        //     be careful of LDS alignment
+        constexpr auto wei_e_k_block_desc = make_ConstantTensorDescriptor_aligned(
+            Sequence<EPerBlock, KPerBlock>{},
+            Number<math::lcm(WeiBlockCopyDstDataPerWrite_K, GemmDataPerReadA)>{});
+
+        // operator for blockwise copy of weight into LDS
+        //     slice a tensor, and copy it into another tensor
+        //     this copy operator already have blockwise offset built-in
+        auto blockwise_wei_copy =
+            BlockwiseGenericTensorSliceCopy_v1<BlockSize,
+                                               Float,
+                                               decltype(wei_e_k_global_desc),
+                                               decltype(wei_e_k_block_desc),
+                                               decltype(wei_e_k_block_desc.GetLengths()),
+                                               WeiBlockCopySubLengths_E_K,
+                                               WeiBlockCopyClusterLengths_E_K,
+                                               WeiBlockCopyThreadClusterArrangeOrder,
+                                               WeiBlockCopySrcAccessOrder,
+                                               WeiBlockCopyDstAccessOrder,
+                                               WeiBlockCopySrcDataPerRead_E,
+                                               WeiBlockCopyDstDataPerWrite_K>(
+                {0, k_block_data_on_global}, {0, 0});
+
+        // GEMM definition
+        // c_mtx += transpose(a_mtx) * b_mtx
+        //     a_mtx[EPerBlock, KPerBlock] is in LDS
+        //     b_mtx[EPerBlocl, N1 * BPerBlock * N2] is in LDS
+        //     c_mtx[KPerBlock, N1 * BPerBlock * N2] is distributed among threads, and saved in
+        //     register
+        constexpr auto a_e_k_block_mtx_desc =
+            make_ConstantMatrixDescriptor_from_ConstantTensorDescriptor(wei_e_k_block_desc);
+
+        //     this check is ad-hoc
+        //     TODO: need to properly implement tensor descriptor with multiple alignment
+        //     requirements
+        static_assert(in_e_n1_ho1_wo1_b_n2_ho2_wo2_block_desc.GetStrides()[3] % GemmDataPerReadB ==
+                          0,
+                      "GemmDataPerReadB alignment requirement is not satisfied");
+
+        constexpr auto b_e_n1ho1wo1bn2ho2wo2_block_mtx_desc =
+            make_ConstantMatrixDescriptor_from_ConstantTensorDescriptor(
+                in_e_n1_ho1_wo1_b_n2_ho2_wo2_block_desc.Unfold(I1, I7));
+
+        // sanity check
+        static_assert(KPerBlock % (GemmMPerThreadSubC * GemmMLevel0Cluster * GemmMLevel1Cluster) ==
+                          0,
+                      "wrong!");
+
+        constexpr index_t GemmMRepeat =
+            KPerBlock / (GemmMPerThreadSubC * GemmMLevel0Cluster * GemmMLevel1Cluster);
+
+        // c_thread_mtx definition: this is a mess
+        // TODO:: more elegent way of defining c_thread_mtx
+        constexpr auto c_k0k2_n1ho1wo1n2ho2wo2_thread_mtx_desc =
+            make_ConstantMatrixDescriptor_packed(Number<GemmMRepeat * GemmMPerThreadSubC>{},
+                                                 Number<N1 * Ho1 * Wo1 * N2 * Ho2 * Wo2>{});
+
+        const auto blockwise_gemm = BlockwiseGemmBlockABlockBThreadCTransANormalBNormalC_v2<
+            BlockSize,
+            decltype(a_e_k_block_mtx_desc),
+            decltype(b_e_n1ho1wo1bn2ho2wo2_block_mtx_desc),
+            decltype(c_k0k2_n1ho1wo1n2ho2wo2_thread_mtx_desc),
+            GemmMPerThreadSubC,
+            GemmNPerThreadSubC,
+            GemmMLevel0Cluster,
+            GemmNLevel0Cluster,
+            GemmMLevel1Cluster,
+            GemmNLevel1Cluster,
+            GemmKPerThreadLoop,
+            GemmDataPerReadA,
+            GemmDataPerReadB>{};
+
+        // LDS allocation for input and weight: be careful of alignment
+        constexpr index_t max_align = math::lcm(InBlockCopyDataPerAccess_W2,
+                                                WeiBlockCopyDstDataPerWrite_K,
+                                                GemmDataPerReadA,
+                                                GemmDataPerReadB);
+
+        constexpr index_t in_block_space = math::integer_least_multiple(
+            in_e_n1_ho1_wo1_b_n2_ho2_wo2_block_desc.GetElementSpace(), max_align);
+
+        constexpr index_t wei_block_space =
+            math::integer_least_multiple(wei_e_k_block_desc.GetElementSpace(), max_align);
+
+        __shared__ Float p_in_block_double[2 * in_block_space];
+        __shared__ Float p_wei_block_double[2 * wei_block_space];
+
+        // register allocation for output
+        Float p_out_thread[c_k0k2_n1ho1wo1n2ho2wo2_thread_mtx_desc.GetElementSpace()];
+
+        // zero out threadwise output
+        threadwise_matrix_set_zero(c_k0k2_n1ho1wo1n2ho2wo2_thread_mtx_desc, p_out_thread);
+
+        const Float* p_wei_block_on_global = p_wei_global;
+
+        // LDS double buffer: preload data into LDS
+        {
+            blockwise_in_copy.Run(p_in_global, p_in_block_double);
+            blockwise_wei_copy.Run(p_wei_global, p_wei_block_double);
+        }
+
+        // LDS double buffer: main body
+        for(index_t e_block_data_begin = 0; e_block_data_begin + 2 * EPerBlock < E;
+            e_block_data_begin += 2 * EPerBlock)
+        {
+#pragma unroll
+            for(index_t iloop = 0; iloop < 2; ++iloop)
+            {
+                const bool even_loop = (iloop % 2 == 0);
+
+                Float* p_in_block_now =
+                    even_loop ? p_in_block_double : p_in_block_double + in_block_space;
+                Float* p_wei_block_now =
+                    even_loop ? p_wei_block_double : p_wei_block_double + wei_block_space;
+
+                Float* p_in_block_next =
+                    even_loop ? p_in_block_double + in_block_space : p_in_block_double;
+                Float* p_wei_block_next =
+                    even_loop ? p_wei_block_double + wei_block_space : p_wei_block_double;
+
+                Float p_in_register_clipboard[blockwise_in_copy.GetRegisterClipboardSize()];
+                Float p_wei_register_clipboard[blockwise_wei_copy.GetRegisterClipboardSize()];
+
+                blockwise_in_copy.MoveSlicingWindowOnSourceTensor(I0, Number<EPerBlock>{}, True);
+                p_wei_block_on_global += EPerBlock * wei_e_k_global_desc.GetStride(I0);
+
+                __syncthreads();
+
+                // LDS doubel buffer: load next data from device mem
+                blockwise_in_copy.RunLoadRegisterClipboard(p_in_global, p_in_register_clipboard);
+                blockwise_wei_copy.RunLoadRegisterClipboard(p_wei_block_on_global,
+                                                            p_wei_register_clipboard);
+
+                // LDS double buffer: GEMM on current data
+                blockwise_gemm.Run(p_wei_block_now, p_in_block_now, p_out_thread);
+
+                // LDS double buffer: store next data to LDS
+                blockwise_in_copy.RunStoreRegisterClipboard(p_in_register_clipboard,
+                                                            p_in_block_next);
+                blockwise_wei_copy.RunStoreRegisterClipboard(p_wei_register_clipboard,
+                                                             p_wei_block_next);
+            }
+        }
+
+        // LDS double buffer: tail
+        {
+            Float p_in_register_clipboard[blockwise_in_copy.GetRegisterClipboardSize()];
+            Float p_wei_register_clipboard[blockwise_wei_copy.GetRegisterClipboardSize()];
+
+            // even iteration
+            blockwise_in_copy.MoveSlicingWindowOnSourceTensor(I0, Number<EPerBlock>{}, True);
+            p_wei_block_on_global += EPerBlock * wei_e_k_global_desc.GetStride(I0);
+
+            __syncthreads();
+
+            // LDS doubel buffer: load next data from device mem
+            blockwise_in_copy.RunLoadRegisterClipboard(p_in_global, p_in_register_clipboard);
+            blockwise_wei_copy.RunLoadRegisterClipboard(p_wei_block_on_global,
+                                                        p_wei_register_clipboard);
+
+            // LDS double buffer: GEMM on current data
+            blockwise_gemm.Run(p_wei_block_double, p_in_block_double, p_out_thread);
+
+            // LDS double buffer: store next data to LDS
+            blockwise_in_copy.RunStoreRegisterClipboard(p_in_register_clipboard,
+                                                        p_in_block_double + in_block_space);
+            blockwise_wei_copy.RunStoreRegisterClipboard(p_wei_register_clipboard,
+                                                         p_wei_block_double + wei_block_space);
+
+            // odd iteration
+            __syncthreads();
+
+            // LDS double buffer: GEMM on current data
+            blockwise_gemm.Run(p_wei_block_double + wei_block_space,
+                               p_in_block_double + in_block_space,
+                               p_out_thread);
+        }
+
+        // copy output: register to global memory
+        {
+            constexpr index_t K2 = GemmMPerThreadSubC;
+            constexpr index_t K1 = GemmMLevel0Cluster * GemmMLevel1Cluster;
+
+            // define tensor descriptor for threadwise copy
+            //     output memory layout descriptor in register
+            constexpr auto out_k0_k1_k2_n1_ho1_wo1_n0_ho0_wo0_n2_ho2_wo2_thread_mem_desc =
+                make_ConstantTensorDescriptor_packed(
+                    Sequence<KPerBlock / (K1 * K2), 1, K2, N1, Ho1, Wo1, 1, 1, 1, N2, Ho2, Wo2>{});
+
+            //     output tensor descriptor in register, src of threadwise copy
+            constexpr auto out_n0_n1_n2_k0_k1_k2_ho0_ho1_ho2_wo0_wo1_wo2_thread_desc =
+                out_k0_k1_k2_n1_ho1_wo1_n0_ho0_wo0_n2_ho2_wo2_thread_mem_desc.ReorderGivenNew2Old(
+                    Sequence<6, 3, 9, 0, 1, 2, 7, 4, 10, 8, 5, 11>{});
+
+            //     output memory layout descriptor in device memory, dst of threadwise copy
+            constexpr auto out_n0_n1_n2_k0_k1_k2_ho0_ho1_ho2_wo0_wo1_wo2_global_mem_desc =
+                out_n_k_h_w_global_desc.Fold(I3, Sequence<Wo1, Wo2>{})
+                    .Fold(I2, Sequence<Ho1, Ho2>{})
+                    .Fold(I1, Sequence<K1, K2>{})
+                    .Fold(I0, Sequence<N1, N2>{});
+
+            // calculate origin of thread output 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 k_thread_data_on_global =
+                k_block_data_on_global + c_thread_mtx_on_block.row;
+
+            const index_t b_thread_data_on_global =
+                b_block_data_on_global + c_thread_mtx_on_block.col / (N2 * Ho2 * Wo2);
+
+            //     output merged global tensor descriptor, for calculating origin of thread tensor
+            //     in global memory
+            constexpr auto out_k_n1_ho1_wo1_b_n2_ho2_wo2_global_merged_desc =
+                make_ConstantMergedTensorDescriptor(
+                    out_n0_n1_n2_k0_k1_k2_ho0_ho1_ho2_wo0_wo1_wo2_global_mem_desc.Unfold(I3, I5),
+                    Sequence<3>{},
+                    Sequence<1>{},
+                    Sequence<5>{},
+                    Sequence<8>{},
+                    Sequence<0, 4, 7>{},
+                    Sequence<2>{},
+                    Sequence<6>{},
+                    Sequence<9>{});
+
+            //     origin of dst in device memory
+            Float* p_out_thread_on_global =
+                p_out_global +
+                out_k_n1_ho1_wo1_b_n2_ho2_wo2_global_merged_desc.GetOffsetFromMultiIndex(
+                    k_thread_data_on_global, 0, 0, 0, b_thread_data_on_global, 0, 0, 0);
+
+            threadwise_generic_tensor_slice_copy_v1(
+                out_n0_n1_n2_k0_k1_k2_ho0_ho1_ho2_wo0_wo1_wo2_thread_desc,
+                p_out_thread,
+                {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+                out_n0_n1_n2_k0_k1_k2_ho0_ho1_ho2_wo0_wo1_wo2_global_mem_desc,
+                p_out_thread_on_global,
+                {0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0},
+                out_n0_n1_n2_k0_k1_k2_ho0_ho1_ho2_wo0_wo1_wo2_thread_desc.GetLengths(),
+                arithmetic_sequence_gen<0, 12, 1>::type{},
+                Number<1>{});
+        }
+    }
+};
+
+} // namespace ck
+#endif

driver/include/device_convolution_implicit_gemm_v4r2_nchw_kcyx_nkhw.hpp

@@ -53,7 +53,7 @@ void device_convolution_implicit_gemm_v4r2_nchw_kcyx_nkhw(InDesc,
     wei_kcyx_device_buf.ToDevice(wei_kcyx.mData.data());
     out_nkhw_device_buf.ToDevice(out_nkhw.mData.data());
 
-#if 1
+#if 0
     // 1x1 filter, 8x8 image
     constexpr index_t N0  = 1;
     constexpr index_t Ho0 = 2;

driver/include/device_convolution_implicit_gemm_v4r3_nchw_kcyx_nkhw.hpp

+#pragma once
+#include <unistd.h>
+#include "device.hpp"
+#include "tensor.hpp"
+#include "gridwise_convolution_kernel_wrapper.hpp"
+#include "gridwise_convolution_implicit_gemm_v4r3_nchw_kcyx_nkhw_lds_double_buffer.hpp"
+
+using namespace ck;
+
+template <class T,
+          class InDesc,
+          class WeiDesc,
+          class OutDesc,
+          class ConvStrides,
+          class ConvDilations>
+void device_convolution_implicit_gemm_v4r3_nchw_kcyx_nkhw(InDesc,
+                                                          const Tensor<T>& in_nchw,
+                                                          WeiDesc,
+                                                          const Tensor<T>& wei_kcyx,
+                                                          OutDesc,
+                                                          Tensor<T>& out_nkhw,
+                                                          ConvStrides,
+                                                          ConvDilations,
+                                                          index_t nrepeat)
+{
+    constexpr auto I0 = Number<0>{};
+    constexpr auto I1 = Number<1>{};
+    constexpr auto I2 = Number<2>{};
+    constexpr auto I3 = Number<3>{};
+
+    constexpr auto in_nchw_desc  = InDesc{};
+    constexpr auto wei_kcyx_desc = WeiDesc{};
+    constexpr auto out_nkhw_desc = OutDesc{};
+
+    constexpr index_t Hi = in_nchw_desc.GetLength(I2);
+    constexpr index_t Wi = in_nchw_desc.GetLength(I3);
+
+    constexpr index_t N  = out_nkhw_desc.GetLength(I0);
+    constexpr index_t Ho = out_nkhw_desc.GetLength(I2);
+    constexpr index_t Wo = out_nkhw_desc.GetLength(I3);
+
+    constexpr index_t K = wei_kcyx_desc.GetLength(I0);
+    constexpr index_t C = wei_kcyx_desc.GetLength(I1);
+    constexpr index_t Y = wei_kcyx_desc.GetLength(I2);
+    constexpr index_t X = wei_kcyx_desc.GetLength(I3);
+
+    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
+    // 1x1 filter, 8x8 image
+    constexpr index_t N1  = 2;
+    constexpr index_t Ho1 = 1;
+    constexpr index_t Wo1 = 1;
+
+    constexpr index_t N2  = 1;
+    constexpr index_t Ho2 = 1;
+    constexpr index_t Wo2 = 4;
+
+    constexpr index_t BlockSize = 256;
+
+    constexpr index_t BPerBlock = 16;
+    constexpr index_t KPerBlock = 128;
+    constexpr index_t EPerBlock = 8;
+
+    constexpr index_t GemmMPerThreadSubC = 4;
+    constexpr index_t GemmNPerThreadSubC = 4;
+    constexpr index_t GemmMLevel0Cluster = 4;
+    constexpr index_t GemmNLevel0Cluster = 4;
+    constexpr index_t GemmMLevel1Cluster = 4;
+    constexpr index_t GemmNLevel1Cluster = 4;
+    constexpr index_t GemmKPerThreadLoop = 1;
+    constexpr index_t GemmDataPerReadA   = 4;
+    constexpr index_t GemmDataPerReadB   = 4;
+
+    using InBlockCopySubLengths_E_N1_Ho1_Wo1_B_N2_Ho2_Wo2     = Sequence<1, 1, 1, 1, 1, 1, 1, 4>;
+    using InBlockCopyClusterLengths_E_N1_Ho1_Wo1_B_N2_Ho2_Wo2 = Sequence<8, 2, 1, 1, 16, 1, 1, 1>;
+    using InBlockCopyThreadClusterArrangeOrder =
+        Sequence<0, 1, 5, 2, 6, 3, 4, 7>; // [E, N1, N2, Ho1, Ho2, Wo1, B, Wo2]
+    using InBlockCopySrcAccessOrder =
+        Sequence<0, 1, 5, 2, 6, 3, 4, 7>; // [E, N1, N2, Ho1, Ho2, Wo1, B, Wo2]
+    using InBlockCopyDstAccessOrder =
+        Sequence<0, 1, 2, 3, 4, 5, 6, 7>; // [E, N1, Ho1, Wo1, B, N2, Ho2, Wo2]
+
+    constexpr index_t InBlockCopyDataPerAccess_W2 = 4;
+
+    using WeiBlockCopySubLengths_E_K            = Sequence<4, 1>;
+    using WeiBlockCopyClusterLengths_E_K        = Sequence<2, 128>;
+    using WeiBlockCopyThreadClusterArrangeOrder = Sequence<1, 0>; // [K, E]
+    using WeiBlockCopySrcAccessOrder            = Sequence<1, 0>; // [K, E]
+    using WeiBlockCopyDstAccessOrder            = Sequence<0, 1>; // [E, K]
+
+    constexpr index_t WeiBlockCopySrcDataPerRead_E  = 4;
+    constexpr index_t WeiBlockCopyDstDataPerWrite_K = 1;
+#endif
+
+    constexpr index_t N0  = N / (N1 * N2);
+    constexpr index_t Ho0 = Ho / (Ho1 * Ho2);
+    constexpr index_t Wo0 = Wo / (Wo1 * Wo2);
+
+    constexpr index_t B = N0 * Ho0 * Wo0;
+
+    constexpr index_t GridSize =
+        ((B + BPerBlock - 1) / BPerBlock) * ((K + KPerBlock - 1) / KPerBlock);
+
+    printf("%s: BlockSize %u, GridSize %u \n", __func__, BlockSize, GridSize);
+
+    for(index_t i = 0; i < nrepeat; ++i)
+    {
+        constexpr auto gridwise_conv =
+            GridwiseConvolutionImplicitGemm_v4r3_nchw_kcyx_nkhw_lds_double_buffer<
+                GridSize,
+                BlockSize,
+                T,
+                decltype(in_nchw_desc),
+                decltype(wei_kcyx_desc),
+                decltype(out_nkhw_desc),
+                ConvStrides,
+                ConvDilations,
+                N0,
+                N1,
+                N2,
+                Ho0,
+                Ho1,
+                Ho2,
+                Wo0,
+                Wo1,
+                Wo2,
+                BPerBlock,
+                KPerBlock,
+                EPerBlock,
+                GemmMPerThreadSubC,
+                GemmNPerThreadSubC,
+                GemmMLevel0Cluster,
+                GemmNLevel0Cluster,
+                GemmMLevel1Cluster,
+                GemmNLevel1Cluster,
+                GemmKPerThreadLoop,
+                GemmDataPerReadA,
+                GemmDataPerReadB,
+                InBlockCopySubLengths_E_N1_Ho1_Wo1_B_N2_Ho2_Wo2,
+                InBlockCopyClusterLengths_E_N1_Ho1_Wo1_B_N2_Ho2_Wo2,
+                InBlockCopyThreadClusterArrangeOrder,
+                InBlockCopySrcAccessOrder,
+                InBlockCopyDstAccessOrder,
+                InBlockCopyDataPerAccess_W2,
+                WeiBlockCopySubLengths_E_K,
+                WeiBlockCopyClusterLengths_E_K,
+                WeiBlockCopyThreadClusterArrangeOrder,
+                WeiBlockCopySrcAccessOrder,
+                WeiBlockCopyDstAccessOrder,
+                WeiBlockCopySrcDataPerRead_E,
+                WeiBlockCopyDstDataPerWrite_K>{};
+
+        float time = launch_kernel(run_gridwise_convolution_kernel<decltype(gridwise_conv), T>,
+                                   dim3(GridSize),
+                                   dim3(BlockSize),
+                                   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()));
+
+        printf("Elapsed time : %f ms, %f TFlop/s\n",
+               time,
+               (float)calculate_convolution_flops(InDesc{}, WeiDesc{}, OutDesc{}) /
+                   (std::size_t(1000) * 1000 * 1000) / time);
+        usleep(std::min(time * 1000, float(10000)));
+    }
+
+    out_nkhw_device_buf.FromDevice(out_nkhw.mData.data());
+}

driver/src/driver.cpp

@@ -15,6 +15,7 @@
 #include "device_convolution_implicit_gemm_v3_nchw_cyxk_nkhw.hpp"
 #include "device_convolution_implicit_gemm_v4r1_nchw_kcyx_nkhw.hpp"
 #include "device_convolution_implicit_gemm_v4r2_nchw_kcyx_nkhw.hpp"
+#include "device_convolution_implicit_gemm_v4r3_nchw_kcyx_nkhw.hpp"
 
 struct GeneratorTensor_1
 {
@@ -537,7 +538,7 @@ int main(int argc, char* argv[])
                                                          ConvStrides{},
                                                          ConvDilations{},
                                                          nrepeat);
-#elif 1
+#elif 0
     device_convolution_implicit_gemm_v4r2_nchw_kcyx_nkhw(in_nchw_desc,
                                                          in_nchw,
                                                          wei_kcyx_desc,
@@ -547,6 +548,16 @@ int main(int argc, char* argv[])
                                                          ConvStrides{},
                                                          ConvDilations{},
                                                          nrepeat);
+#elif 1
+    device_convolution_implicit_gemm_v4r3_nchw_kcyx_nkhw(in_nchw_desc,
+                                                         in_nchw,
+                                                         wei_kcyx_desc,
+                                                         wei_kcyx,
+                                                         out_nkhw_desc,
+                                                         out_nkhw_device,
+                                                         ConvStrides{},
+                                                         ConvDilations{},
+                                                         nrepeat);
 #elif 0
     device_implicit_gemm_convolution_1_chwn_cyxk_khwn_padded(in_nchw_desc,
                                                              in_nchw,