added 1x1 conv

device_operation/device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_1x1_p0_f16_instance.cpp

+#include <stdlib.h>
+#include "config.hpp"
+#include "device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_1x1_p0.hpp"
+#include "device_conv_instance.hpp"
+#include "element_wise_operation.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+namespace device_conv_instance {
+
+using F16 = ck::half_t;
+using F32 = float;
+
+template <ck::index_t... Is>
+using S = ck::Sequence<Is...>;
+
+using PassThrough = ck::tensor_operation::element_wise::PassThrough;
+
+using device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_1x1_p0_f16_instances = std::tuple<
+    // clang-format off
+        //#######################################################################| InData| WeiData| OutData| AccData|           A|           B|           C| Block|  MPer|  NPer| K0Per| K1| MPer| NPer| MXdl| NXdl|  ABlockTransfer|  ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer| ABlockTransfer|  BBlockTransfer|  BBlockTransfer| BBlockTransfer| BBlockTransfer| BlockTransfer| BBlockTransfer| BBlockTransfer| CThreadTransfer| CThreadTransfer| ABlockLds| BBlockLds|
+        //#######################################################################|   Type|    Type|    Type|    Type| Elementwise| Elementwise| Elementwise|  Size| Block| Block| Block|   |  XDL|  XDL|  Per|  Per|     ThreadSlice|   ThreadCluster|  ThreadCluster| SrcAccessOrder|   SrcVectorDim|      SrcScalar|      DstScalar|     ThreadSlice|   ThreadCluster|  ThreadCluster| SrcAccessOrder|  SrcVectorDim|      SrcScalar|      DstScalar| SrcDstVectorDim|       DstScalar| AddExtraM| AddExtraN|
+        //#######################################################################|       |        |        |        |   Operation|   Operation|   Operation|      |      |      |      |   |     |     | Wave| Wave| Lengths_K0_N_K1| Lengths_K0_M_K1|   ArrangeOrder|               |               |      PerVector|   PerVector_K1| Lengths_K0_N_K1| Lengths_K0_N_K1|   ArrangeOrder|               |              |      PerVector|   PerVector_K1|                |       PerVector|          |          |
+        //#######################################################################|       |        |        |        |            |            |            |      |      |      |      |   |     |     |     |     |                |                |               |               |               |               |               |                |                |               |               |              |               |               |                |                |          |          |
+        DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K_1x1_P0<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,   256,   256,   128,     4,  8,   32,   32,    4,    2,      S<1, 4, 8>,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              8,              8,      S<1, 2, 8>,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              8,              8,               7,               1,      true,      true>,
+        DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K_1x1_P0<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,   256,   128,   256,     4,  8,   32,   32,    2,    4,      S<1, 2, 8>,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              8,              8,      S<1, 4, 8>,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              8,              8,               7,               1,      true,      true>,
+        DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K_1x1_P0<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,   128,   128,   128,     4,  8,   32,   32,    4,    2,      S<1, 4, 8>,     S<4, 32, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              8,              8,      S<1, 4, 8>,     S<4, 32, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              8,              8,               7,               1,      true,      true>,
+        DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K_1x1_P0<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,   256,   128,   128,     4,  8,   32,   32,    2,    2,      S<1, 2, 8>,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              8,              8,      S<1, 2, 8>,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              8,              8,               7,               1,      true,      true>,
+        DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K_1x1_P0<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,   128,   128,    64,     4,  8,   32,   32,    2,    2,      S<1, 4, 8>,     S<4, 32, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              8,              8,      S<1, 2, 8>,     S<4, 32, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              8,              8,               7,               1,      true,      true>,
+        DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K_1x1_P0<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,   128,    64,   128,     4,  8,   32,   32,    2,    2,      S<1, 2, 8>,     S<4, 32, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              8,              8,      S<1, 4, 8>,     S<4, 32, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              8,              8,               7,               1,      true,      true>,
+        DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K_1x1_P0<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,    64,    64,    64,     4,  8,   32,   32,    2,    2,      S<1, 4, 8>,     S<4, 16, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              8,              8,      S<1, 4, 8>,     S<4, 16, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              8,              8,               7,               1,      true,      true>,
+        DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K_1x1_P0<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,   256,   128,    64,     4,  8,   32,   32,    2,    1,      S<1, 2, 8>,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              8,              8,      S<1, 1, 8>,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              8,              8,               7,               1,      true,      true>,
+        DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K_1x1_P0<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,   256,    64,   128,     4,  8,   32,   32,    1,    2,      S<1, 1, 8>,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              8,              8,      S<1, 2, 8>,     S<4, 64, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              8,              8,               7,               1,      true,      true>,
+        DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K_1x1_P0<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,   128,   128,    32,     4,  8,   32,   32,    2,    1,      S<1, 4, 8>,     S<4, 32, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              8,              8,      S<1, 1, 8>,     S<4, 32, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              8,              8,               7,               1,      true,      true>,
+        DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K_1x1_P0<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,   128,    32,   128,     4,  8,   32,   32,    1,    2,      S<1, 1, 8>,     S<4, 32, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              8,              8,      S<1, 4, 8>,     S<4, 32, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              8,              8,               7,               1,      true,      true>,
+        DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K_1x1_P0<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,    64,    64,    32,     4,  8,   32,   32,    2,    1,      S<1, 4, 8>,     S<4, 16, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              8,              8,      S<1, 2, 8>,     S<4, 16, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              8,              8,               7,               1,      true,      true>,
+        DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K_1x1_P0<    F16,     F16,     F16,     F32, PassThrough, PassThrough, PassThrough,    64,    32,    64,     4,  8,   32,   32,    1,    2,      S<1, 2, 8>,     S<4, 16, 1>,     S<1, 0, 2>,     S<1, 0, 2>,              2,              8,              8,      S<1, 4, 8>,     S<4, 16, 1>,     S<1, 0, 2>,     S<1, 0, 2>,             2,              8,              8,               7,               1,      true,      true>
+    // clang-format on
+    >;
+
+void add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_1x1_p0_fp16_instances(
+    std::vector<DeviceConvFwdPtr<PassThrough, PassThrough, PassThrough>>& device_conv_instances)
+{
+    using DeviceConvs = device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_1x1_p0_f16_instances;
+
+    const auto device_convs = DeviceConvs{};
+
+    ck::static_for<0, std::tuple_size_v<DeviceConvs>, 1>{}([&](auto i) {
+        using Conv = remove_cvref_t<decltype(std::get<i>(device_convs))>;
+
+        auto conv = Conv{};
+
+        device_conv_instances.push_back(std::make_unique<Conv>(conv));
+    });
+}
+
+} // namespace device_conv_instance
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

device_operation/include/device_base.hpp

 #ifndef DEVICE_BASE_HPP
 #define DEVICE_BASE_HPP
 
+#include <string>
+
 namespace ck {
 namespace tensor_operation {
 namespace device {
@@ -32,6 +34,7 @@ struct BaseOperator
     BaseOperator& operator=(const BaseOperator&) = default;
 
     virtual bool IsSupportedArgument(const BaseArgument*) = 0;
+    virtual std::string GetTypeString() const             = 0;
 
     virtual ~BaseOperator() {}
 };

device_operation/include/device_conv.hpp

@@ -34,76 +34,12 @@ struct DeviceConvFwd : public BaseOperator
     virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0;
 };
 
-template <typename InElementwiseOperation,
-          typename WeiElementwiseOperation,
-          typename OutElementwiseOperation>
-struct DeviceConvBwd : public BaseOperator
-{
-    virtual std::unique_ptr<BaseArgument>
-    MakeArgumentPointer(void* p_in,
-                        const void* p_wei,
-                        const void* p_out,
-                        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,
-                        InElementwiseOperation in_element_op,
-                        WeiElementwiseOperation wei_element_op,
-                        OutElementwiseOperation out_element_op) = 0;
-
-    virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0;
-};
-
-template <typename InElementwiseOperation,
-          typename WeiElementwiseOperation,
-          typename OutElementwiseOperation>
-struct DeviceConvWrw : public BaseOperator
-{
-    virtual std::unique_ptr<BaseArgument>
-    MakeArgumentPointer(const void* p_in,
-                        void* p_wei,
-                        const void* p_out,
-                        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,
-                        InElementwiseOperation in_element_op,
-                        WeiElementwiseOperation wei_element_op,
-                        OutElementwiseOperation out_element_op) = 0;
-
-    virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0;
-};
-
 template <typename InElementwiseOperation,
           typename WeiElementwiseOperation,
           typename OutElementwiseOperation>
 using DeviceConvFwdPtr = std::unique_ptr<
     DeviceConvFwd<InElementwiseOperation, WeiElementwiseOperation, OutElementwiseOperation>>;
 
-template <typename InElementwiseOperation,
-          typename WeiElementwiseOperation,
-          typename OutElementwiseOperation>
-using DeviceConvBwdPtr = std::unique_ptr<
-    DeviceConvBwd<InElementwiseOperation, WeiElementwiseOperation, OutElementwiseOperation>>;
-
-template <typename InElementwiseOperation,
-          typename WeiElementwiseOperation,
-          typename OutElementwiseOperation>
-using DeviceConvWrwPtr = std::unique_ptr<
-    DeviceConvWrw<InElementwiseOperation, WeiElementwiseOperation, OutElementwiseOperation>>;
-
 } // namespace device
 } // namespace tensor_operation
 } // namespace ck

device_operation/include/device_conv2d_fwd_xdl_nhwc_kyxc_nhwk.hpp

@@ -2,6 +2,7 @@
 #define DEVICE_CONV2D_FWD_XDL_NHWC_KYXC_NHWK_HPP
 
 #include <iostream>
+#include <sstream>
 #include "device.hpp"
 #include "device_base.hpp"
 #include "device_conv.hpp"
@@ -594,6 +595,24 @@ struct DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K
     {
         return std::make_unique<Invoker>(Invoker{});
     }
+
+    // polymorphic
+    std::string GetTypeString() const override
+    {
+        auto str = std::stringstream();
+
+        // clang-format off
+        str << "DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K"
+            << "<"
+            << BlockSize << ", "
+            << MPerBlock << ", "
+            << NPerBlock << ", "
+            << K0PerBlock
+            << ">";
+        // clang-format on
+
+        return str.str();
+    }
 }; // namespace device
 
 } // namespace device

device_operation/include/device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_1x1_s1_p0.hpp

@@ -2,6 +2,7 @@
 #define DEVICE_CONV2D_FWD_XDL_NHWC_KYXC_NHWK_1X1_S1_P0_HPP
 
 #include <iostream>
+#include <sstream>
 #include "device.hpp"
 #include "device_base.hpp"
 #include "device_conv.hpp"
@@ -546,6 +547,24 @@ struct DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K_1x1_S1
     {
         return std::make_unique<Invoker>(Invoker{});
     }
+
+    // polymorphic
+    std::string GetTypeString() const override
+    {
+        auto str = std::stringstream();
+
+        // clang-format off
+        str << "DeviceConv2dFwdXdl_Input_N_Hi_Wi_C_Weight_K_Y_X_C_Output_N_Ho_Wo_K_1x1_s1_P0"
+            << "<"
+            << BlockSize << ", "
+            << MPerBlock << ", "
+            << NPerBlock << ", "
+            << K0PerBlock
+            << ">";
+        // clang-format on
+
+        return str.str();
+    }
 }; // namespace device
 
 } // namespace device

device_operation/include/device_conv_instance.hpp

@@ -21,30 +21,6 @@ void add_device_conv_fwd_instance(
                                  ck::tensor_operation::element_wise::PassThrough,
                                  ck::tensor_operation::element_wise::PassThrough>>&);
 
-template <ck::index_t NDimSpatial,
-          typename InDataType,
-          typename WeiDataType,
-          typename OutDataType,
-          typename InLayout,
-          typename WeiLayout,
-          typename OutLayout>
-void add_device_conv_bwd_instance(
-    std::vector<DeviceConvBwdPtr<ck::tensor_operation::element_wise::PassThrough,
-                                 ck::tensor_operation::element_wise::PassThrough,
-                                 ck::tensor_operation::element_wise::PassThrough>>&);
-
-template <ck::index_t NDimSpatial,
-          typename InDataType,
-          typename WeiDataType,
-          typename OutDataType,
-          typename InLayout,
-          typename WeiLayout,
-          typename OutLayout>
-void add_device_conv_wrw_instance(
-    std::vector<DeviceConvWrwPtr<ck::tensor_operation::element_wise::PassThrough,
-                                 ck::tensor_operation::element_wise::PassThrough,
-                                 ck::tensor_operation::element_wise::PassThrough>>&);
-
 } // namespace device_conv_instance
 } // namespace device
 } // namespace tensor_operation

device_operation/include/device_gemm_xdl.hpp

@@ -2,6 +2,7 @@
 #define DEVICE_GEMM_XDL_HPP
 
 #include <iostream>
+#include <sstream>
 #include "device.hpp"
 #include "device_base.hpp"
 #include "device_gemm.hpp"
@@ -483,6 +484,24 @@ struct DeviceGemmXdl
     {
         return std::make_unique<Invoker>(Invoker{});
     }
+
+    // polymorphic
+    std::string GetTypeString() const override
+    {
+        auto str = std::stringstream();
+
+        // clang-format off
+        str << "DeviceGemmXdl"
+            << "<"
+            << BlockSize << ", "
+            << MPerBlock << ", "
+            << NPerBlock << ", "
+            << K0PerBlock
+            << ">";
+        // clang-format on
+
+        return str.str();
+    }
 };
 
 } // namespace device

profiler/CMakeLists.txt

@@ -34,6 +34,7 @@ install(TARGETS device_gemm_instance LIBRARY DESTINATION lib)
 set(DEVICE_CONV_INSTANCE_SOURCE 
    ${PROJECT_SOURCE_DIR}/device_operation/device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_f32_instance.cpp;
    ${PROJECT_SOURCE_DIR}/device_operation/device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_f16_instance.cpp;
+   ${PROJECT_SOURCE_DIR}/device_operation/device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_1x1_p0_f16_instance.cpp;
    ${PROJECT_SOURCE_DIR}/device_operation/device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_1x1_s1_p0_f16_instance.cpp;
 ) 
 
@@ -48,4 +49,5 @@ set(PROFILER_SOURCE profiler.cpp gemm_profiler.cpp conv_profiler.cpp)
 add_executable(ckProfiler ${PROFILER_SOURCE})
 
 target_link_libraries(ckProfiler PRIVATE host_tensor)
-target_link_libraries(ckProfiler PRIVATE device_gemm_instance device_conv_instance)
+target_link_libraries(ckProfiler PRIVATE device_gemm_instance)
+target_link_libraries(ckProfiler PRIVATE device_conv_instance)

profiler/include/profile_conv.hpp

@@ -39,6 +39,9 @@ void add_device_conv_fwd_instance<2,
                                   ck::tensor_layout::convolution::NHWK>(
     std::vector<DeviceConvFwdNoOpPtr>&);
 
+void add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_1x1_p0_fp16_instances(
+    std::vector<DeviceConvFwdNoOpPtr>&);
+
 void add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_1x1_s1_p0_fp16_instances(
     std::vector<DeviceConvFwdNoOpPtr>&);
 
@@ -158,6 +161,9 @@ void profile_conv(int do_verification,
                                                                                      OutLayout>(
         conv_ptrs);
 
+    ck::tensor_operation::device::device_conv_instance::
+        add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_1x1_p0_fp16_instances(conv_ptrs);
+
     ck::tensor_operation::device::device_conv_instance::
         add_device_conv2d_fwd_xdl_nhwc_kyxc_nhwk_1x1_s1_p0_fp16_instances(conv_ptrs);
 
@@ -166,6 +172,7 @@ void profile_conv(int do_verification,
         throw std::runtime_error("wrong! no device Conv instance found");
     }
 
+    std::string best_conv_name;
     float best_ave_time   = 0;
     float best_tflops     = 0;
     float best_gb_per_sec = 0;
@@ -195,6 +202,8 @@ void profile_conv(int do_verification,
 
         if(conv_ptr->IsSupportedArgument(argument_ptr.get()))
         {
+            std::string conv_name = conv_ptr->GetTypeString();
+
             float ave_time = invoker_ptr->Run(argument_ptr.get(), nrepeat);
 
             std::size_t flop = std::size_t(2) * N * K * Ho * Wo * C * Y * X;
@@ -208,10 +217,11 @@ void profile_conv(int do_verification,
             float gb_per_sec = num_btype / 1.E6 / ave_time;
 
             std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec
-                      << " GB/s" << std::endl;
+                      << " GB/s, " << conv_name << std::endl;
 
             if(tflops > best_tflops)
             {
+                best_conv_name  = conv_name;
                 best_tflops     = tflops;
                 best_ave_time   = ave_time;
                 best_gb_per_sec = gb_per_sec;
@@ -241,7 +251,7 @@ void profile_conv(int do_verification,
     }
 
     std::cout << "Best Perf: " << best_ave_time << " ms, " << best_tflops << " TFlops, "
-              << best_gb_per_sec << " GB/s" << std::endl;
+              << best_gb_per_sec << " GB/s, " << best_conv_name << std::endl;
 }
 
 } // namespace profiler

profiler/include/profile_gemm.hpp

@@ -164,6 +164,7 @@ void profile_gemm(int do_verification,
         throw std::runtime_error("wrong! no device GEMM instance found");
     }
 
+    std::string best_gemm_name;
     float best_ave_time   = 0;
     float best_tflops     = 0;
     float best_gb_per_sec = 0;
@@ -189,9 +190,12 @@ void profile_gemm(int do_verification,
 
         if(gemm_ptr->IsSupportedArgument(argument_ptr.get()))
         {
+            std::string gemm_name = gemm_ptr->GetTypeString();
+
             float ave_time = invoker_ptr->Run(argument_ptr.get(), nrepeat);
 
             std::size_t flop = std::size_t(2) * M * N * K;
+
             std::size_t num_btype =
                 sizeof(ADataType) * M * K + sizeof(BDataType) * K * M + sizeof(CDataType) * M * N;
 
@@ -200,10 +204,11 @@ void profile_gemm(int do_verification,
             float gb_per_sec = num_btype / 1.E6 / ave_time;
 
             std::cout << "Perf: " << ave_time << " ms, " << tflops << " TFlops, " << gb_per_sec
-                      << " GB/s" << std::endl;
+                      << " GB/s, " << gemm_name << std::endl;
 
             if(tflops > best_tflops)
             {
+                best_gemm_name  = gemm_name;
                 best_tflops     = tflops;
                 best_ave_time   = ave_time;
                 best_gb_per_sec = gb_per_sec;
@@ -234,7 +239,7 @@ void profile_gemm(int do_verification,
     }
 
     std::cout << "Best Perf: " << best_ave_time << " ms, " << best_tflops << " TFlops, "
-              << best_gb_per_sec << " GB/s" << std::endl;
+              << best_gb_per_sec << " GB/s, " << best_gemm_name << std::endl;
 }
 
 } // namespace profiler