fix bug after merge develop

example/01_gemm/gemm_xdl_skip_b_lds_fp16.cpp

@@ -13,7 +13,6 @@
 #include "device_tensor.hpp"
 #include "device_gemm_xdl_skip_b_lds.hpp"
 #include "device_gemm_xdl.hpp"
-#include "device_gemm_xdl_c_shuffle.hpp"
 #include "device_gemm_xdl_cshuffle.hpp"
 #include "element_wise_operation.hpp"
 #include "reference_gemm.hpp"
@@ -82,7 +81,7 @@ using AccDataType = float;
     // clang-format on
 
     using ReferenceGemmInstance = ck::tensor_operation::host::
-        ReferenceGemm<ADataType, BDataType, CDataType, AElementOp, BElementOp, CElementOp>;
+        ReferenceGemm<ADataType, BDataType, CDataType, float, AElementOp, BElementOp, CElementOp>;
 
 template <typename DataType>
 std::ostream& show_2d_matrix(std::ostream& os, Tensor<DataType>& matrix)
@@ -104,7 +103,7 @@ int main(int argc, char* argv[])
 {
     bool do_verification = 0;
     int init_method      = 0;
-    int nrepeat          = 5;
+    bool time_kernel     = false;
 
     // GEMM shape
 #if 1
@@ -129,13 +128,13 @@ int main(int argc, char* argv[])
     {
         do_verification = std::stoi(argv[1]);
         init_method     = std::stoi(argv[2]);
-        nrepeat         = std::stoi(argv[3]);
+        time_kernel     = std::stoi(argv[3]);
     }
     else if(argc == 10)
     {
         do_verification = std::stoi(argv[1]);
         init_method     = std::stoi(argv[2]);
-        nrepeat         = std::stoi(argv[3]);
+        time_kernel     = std::stoi(argv[3]);
 
         M = std::stoi(argv[4]);
         N = std::stoi(argv[5]);
@@ -149,7 +148,7 @@ int main(int argc, char* argv[])
     {
         printf("arg1: verification (0=no, 1=yes)\n");
         printf("arg2: initialization (0=no init, 1=integer value, 2=decimal value)\n");
-        printf("arg3: run kernel # of times (>1)\n");
+        printf("arg3: time kernel (0=n0, 1=yes)\n");
         printf("arg4 to 9: M (256x), N(128x), K(32x), StrideA, StrideB, StrideC\n");
         exit(0);
     }
@@ -228,7 +227,7 @@ int main(int argc, char* argv[])
             "not support this GEMM problem");
     }
 
-    float ave_time = invoker.Run(argument, nrepeat);
+    float ave_time = invoker.Run(argument, StreamConfig{nullptr, time_kernel});
 
     std::size_t flop = std::size_t(2) * M * N * K;
     std::size_t num_btype =

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

@@ -283,7 +283,7 @@ struct DeviceGemmXdlSkipBLds
     {
         using Argument = DeviceGemmXdlSkipBLds::Argument;
 
-        float Run(const Argument& arg, int nrepeat = 1)
+        float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
         {
             {
                 std::cout << "arg.a_grid_desc_k0_m_k1_{" << arg.a_grid_desc_k0_m_k1_.GetLength(I0)
@@ -332,8 +332,8 @@ struct DeviceGemmXdlSkipBLds
                     remove_reference_t<typename GridwiseGemm::DefaultBlock2CTileMap>,
                     true>;
 
-                ave_time = launch_and_time_kernel(kernel,
-                                                  nrepeat,
+                ave_time = launch_and_time_kernel(stream_config,
+                                                  kernel,
                                                   dim3(grid_size),
                                                   dim3(BlockSize),
                                                   0,
@@ -364,8 +364,8 @@ struct DeviceGemmXdlSkipBLds
                     remove_reference_t<typename GridwiseGemm::DefaultBlock2CTileMap>,
                     false>;
 
-                ave_time = launch_and_time_kernel(kernel,
-                                                  nrepeat,
+                ave_time = launch_and_time_kernel(stream_config,
+                                                  kernel,
                                                   dim3(grid_size),
                                                   dim3(BlockSize),
                                                   0,
@@ -385,9 +385,10 @@ struct DeviceGemmXdlSkipBLds
         }
 
         // polymorphic
-        float Run(const BaseArgument* p_arg, int nrepeat = 1) override
+        float Run(const BaseArgument* p_arg,
+                  const StreamConfig& stream_config = StreamConfig{}) override
         {
-            return Run(*dynamic_cast<const Argument*>(p_arg), nrepeat);
+            return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
         }
     };
 

include/ck/tensor_operation/gpu/grid/gridwise_gemm_xdlops_skip_b_lds_v1.hpp

@@ -7,7 +7,7 @@
 #include "tensor_descriptor_helper.hpp"
 #include "blockwise_gemm_xdlops.hpp"
 #include "blockwise_gemm_xdlops_skip_b_lds.hpp"
-#include "blockwise_tensor_slice_transfer_v4r1.hpp"
+#include "thread_group_tensor_slice_transfer_v4r1.hpp"
 #include "threadwise_tensor_slice_transfer.hpp"
 #include "gridwise_gemm_pipeline_v1.hpp"
 
@@ -124,6 +124,8 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_skip_b_lds_v1
     static constexpr auto xdlops_gemm    = XdlopsGemm<FloatAB, MPerXDL, NPerXDL, K1>{};
     static constexpr index_t K0PerThread = K0PerBlock / xdlops_gemm.K0PerXdlops;
 
+    using ThisThreadBlock = ThisThreadBlock<BlockSize>;
+
     __host__ __device__ static constexpr auto GetABlockDescriptor_K0PerBlock_MPerBlock_K1()
     {
         constexpr auto max_lds_align = K1;
@@ -397,7 +399,7 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_skip_b_lds_v1
 
         // A matrix blockwise copy
         auto a_blockwise_copy =
-            BlockwiseTensorSliceTransfer_v4r1<BlockSize,
+            ThreadGroupTensorSliceTransfer_v4r1<ThisThreadBlock,
                                                 AElementwiseOperation,
                                                 ck::tensor_operation::element_wise::PassThrough,
                                                 InMemoryDataOperationEnum::Set,
@@ -418,7 +420,8 @@ struct GridwiseGemm_k0mk1_k0nk1_mn_xdlops_skip_b_lds_v1
                                                 1,
                                                 AThreadTransferSrcResetCoordinateAfterRun,
                                                 true,
-                                              1>(a_grid_desc_k0_m_k1,
+                                                1>(
+                a_grid_desc_k0_m_k1,
                 make_multi_index(0, m_block_data_idx_on_grid, 0),
                 a_element_op,
                 a_block_desc_k0_m_k1,