Improve external interface for GEMM and GEMM+add+add+fastgelu (#311)

* interface for GEMM and GEMM+add+add+fastgelu

* rename namespace

* instance factory

* fix build

* fix build; add GEMM client example

* clean

README.md

@@ -26,6 +26,7 @@ cmake                                                                 \
 -D CMAKE_CXX_FLAGS=" --offload-arch=gfx908 --offload-arch=gfx90a -O3" \
 -D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc                             \
 -D CMAKE_PREFIX_PATH=/opt/rocm                                        \
+-D CMAKE_INSTALL_PREFIX=${PATH_TO_CK_INSTALL_DIRECTORY}               \
 ..
 ```
 
@@ -47,6 +48,12 @@ Instructions for running each individual examples are under ```example/```
 ```
 Instructions for running ckProfiler are under ```profiler/```
 
+## Install CK
+```bash
+make install
+```
+
+## Using CK as pre-built kernel library
 
 ## Caveat
 ### Kernel Timing and Verification

client_example/01_gemm/CMakeLists.txt

+add_executable(client_gemm gemm.cpp)
+target_link_libraries(client_gemm PRIVATE composable_kernel::device_operations)

client_example/01_gemm/gemm.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <iomanip>
+#include <vector>
+#include <iostream>
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_gemm.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+
+#include "ck/library/tensor_operation_instance/gpu/gemm.hpp"
+
+using F16 = ck::half_t;
+using F32 = float;
+
+using Row = ck::tensor_layout::gemm::RowMajor;
+using Col = ck::tensor_layout::gemm::ColumnMajor;
+
+using PassThrough = ck::tensor_operation::element_wise::PassThrough;
+
+using AElementOp = PassThrough;
+using BElementOp = PassThrough;
+using CElementOp = PassThrough;
+
+using ADataType = F16;
+using BDataType = F16;
+using CDataType = F16;
+
+using ALayout = Row;
+using BLayout = Col;
+using CLayout = Row;
+
+struct SimpleDeviceMem
+{
+    SimpleDeviceMem() = delete;
+
+    SimpleDeviceMem(std::size_t mem_size) : p_mem_{}
+    {
+        (void)hipMalloc(static_cast<void**>(&p_mem_), mem_size);
+    }
+
+    void* GetDeviceBuffer() { return p_mem_; }
+
+    ~SimpleDeviceMem() { (void)hipFree(p_mem_); }
+
+    void* p_mem_;
+};
+
+int main(int argc, char* argv[])
+{
+    // GEMM shape
+    ck::index_t M = 3840;
+    ck::index_t N = 4096;
+    ck::index_t K = 4096;
+
+    ck::index_t StrideA = 4096;
+    ck::index_t StrideB = 4096;
+    ck::index_t StrideC = 4096;
+
+    if(argc == 1)
+    {
+        // use default case
+    }
+    else if(argc == 5)
+    {
+        M = std::stoi(argv[1]);
+        N = std::stoi(argv[2]);
+        K = std::stoi(argv[3]);
+
+        StrideA = std::stoi(argv[4]);
+        StrideB = std::stoi(argv[5]);
+        StrideC = std::stoi(argv[6]);
+    }
+    else
+    {
+        printf("arg1 to 6: M, N, K, StrideA, StrideB, StrideC\n");
+        exit(0);
+    }
+
+    auto f_matrix_space_size =
+        [](std::size_t nRow, std::size_t nCol, std::size_t stride, auto layout) {
+            using Layout = decltype(layout);
+
+            if(std::is_same<Layout, ck::tensor_layout::gemm::RowMajor>::value)
+            {
+                return (nRow - 1) * stride + nCol;
+            }
+            else
+            {
+                return (nCol - 1) * stride + nRow;
+            }
+        };
+
+    SimpleDeviceMem a_device_buf(sizeof(ADataType) * f_matrix_space_size(M, K, StrideA, ALayout{}));
+    SimpleDeviceMem b_device_buf(sizeof(BDataType) * f_matrix_space_size(K, N, StrideB, BLayout{}));
+    SimpleDeviceMem c_device_buf(sizeof(CDataType) * f_matrix_space_size(M, N, StrideC, CLayout{}));
+
+    using DeviceOp =
+        ck::tensor_operation::device::DeviceGemm<ALayout,
+                                                 BLayout,
+                                                 CLayout,
+                                                 ADataType,
+                                                 BDataType,
+                                                 CDataType,
+                                                 ck::tensor_operation::element_wise::PassThrough,
+                                                 ck::tensor_operation::element_wise::PassThrough,
+                                                 ck::tensor_operation::element_wise::PassThrough>;
+
+    // get device op instances
+    const auto op_ptrs = ck::tensor_operation::device::instance::DeviceOperationInstanceFactory<
+        DeviceOp>::GetInstances();
+
+    std::cout << "found " << op_ptrs.size() << " instances" << std::endl;
+
+    const auto a_element_op = AElementOp{};
+    const auto b_element_op = BElementOp{};
+    const auto c_element_op = CElementOp{};
+
+    std::string best_op_name;
+    bool found            = false;
+    int best_op_id        = -1;
+    float best_ave_time   = 0;
+    float best_tflops     = 0;
+    float best_gb_per_sec = 0;
+
+    // profile device operation instances
+    std::cout << "Run all instances and do timing" << std::endl;
+
+    for(int i = 0; i < op_ptrs.size(); ++i)
+    {
+        auto& op_ptr = op_ptrs[i];
+
+        auto argument_ptr = op_ptr->MakeArgumentPointer(a_device_buf.GetDeviceBuffer(),
+                                                        b_device_buf.GetDeviceBuffer(),
+                                                        c_device_buf.GetDeviceBuffer(),
+                                                        M,
+                                                        N,
+                                                        K,
+                                                        StrideA,
+                                                        StrideB,
+                                                        StrideC,
+                                                        a_element_op,
+                                                        b_element_op,
+                                                        c_element_op);
+
+        auto invoker_ptr = op_ptr->MakeInvokerPointer();
+
+        std::string op_name = op_ptr->GetTypeString();
+
+        if(op_ptr->IsSupportedArgument(argument_ptr.get()))
+        {
+            float ave_time = invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, true});
+
+            std::size_t flop = std::size_t(2) * M * N * K;
+
+            std::size_t num_btype =
+                sizeof(ADataType) * M * K + sizeof(BDataType) * K * N + sizeof(CDataType) * M * N;
+
+            float tflops = static_cast<float>(flop) / 1.E9 / ave_time;
+
+            float gb_per_sec = num_btype / 1.E6 / ave_time;
+
+            std::cout << "Perf: " << std::setw(10) << ave_time << " ms, " << tflops << " TFlops, "
+                      << gb_per_sec << " GB/s, " << op_name << std::endl;
+
+            if(tflops > best_tflops)
+            {
+                found           = true;
+                best_op_id      = i;
+                best_op_name    = op_name;
+                best_tflops     = tflops;
+                best_ave_time   = ave_time;
+                best_gb_per_sec = gb_per_sec;
+            }
+        }
+        else
+        {
+            std::cout << op_name << " does not support this problem" << std::endl;
+        }
+    }
+
+    std::cout << "Best Perf: " << best_ave_time << " ms, " << best_tflops << " TFlops, "
+              << best_gb_per_sec << " GB/s, " << best_op_name << std::endl;
+
+    // run the best intance
+    {
+        auto& op_ptr = op_ptrs[best_op_id];
+
+        std::cout << "Run the best instance without timing: " << op_ptr->GetTypeString()
+                  << std::endl;
+
+        auto argument_ptr = op_ptr->MakeArgumentPointer(a_device_buf.GetDeviceBuffer(),
+                                                        b_device_buf.GetDeviceBuffer(),
+                                                        c_device_buf.GetDeviceBuffer(),
+                                                        M,
+                                                        N,
+                                                        K,
+                                                        StrideA,
+                                                        StrideB,
+                                                        StrideC,
+                                                        a_element_op,
+                                                        b_element_op,
+                                                        c_element_op);
+
+        auto invoker_ptr = op_ptr->MakeInvokerPointer();
+
+        if(op_ptr->IsSupportedArgument(argument_ptr.get()))
+        {
+            invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, false});
+        }
+
+        std::cout << "Done" << std::endl;
+    }
+
+    return 0;
+}

client_example/02_gemm_add_add_fastgelu/gemm_add_add_fastgelu.cpp

@@ -10,7 +10,7 @@
 #include "ck/tensor_operation/gpu/device/device_gemm_multiple_d.hpp"
 #include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
 
-#include "ck/library/tensor_operation_instance/gpu/device_gemm_add_add_fastgelu_instance.hpp"
+#include "ck/library/tensor_operation_instance/gpu/gemm_add_add_fastgelu.hpp"
 
 using F16 = ck::half_t;
 using F32 = float;
@@ -27,16 +27,15 @@ using CDEElementOp = AddAddFastGelu;
 
 using ADataType  = F16;
 using BDataType  = F16;
-using AccDataType = F32;
 using D0DataType = F16;
 using D1DataType = F16;
 using EDataType  = F16;
 
 using ALayout   = Row;
 using BLayout   = Col;
-using D0Layout = Row;
-using D1Layout = Row;
-using ELayout  = Row;
+using DDELayout = Row;
+using DDELayout = Row;
+using DELayout  = Row;
 
 struct SimpleDeviceMem
 {
@@ -106,24 +105,27 @@ int main(int argc, char* argv[])
     SimpleDeviceMem a_device_buf(sizeof(ADataType) * f_matrix_space_size(M, K, StrideA, ALayout{}));
     SimpleDeviceMem b_device_buf(sizeof(BDataType) * f_matrix_space_size(K, N, StrideB, BLayout{}));
     SimpleDeviceMem d0_m_n_device_buf(sizeof(D0DataType) *
-                                      f_matrix_space_size(M, N, StrideD0, D0Layout{}));
+                                      f_matrix_space_size(M, N, StrideD0, DDELayout{}));
     SimpleDeviceMem d1_m_n_device_buf(sizeof(D1DataType) *
-                                      f_matrix_space_size(M, N, StrideD1, D1Layout{}));
-    SimpleDeviceMem e_device_buf(sizeof(EDataType) * f_matrix_space_size(M, N, StrideE, ELayout{}));
+                                      f_matrix_space_size(M, N, StrideD1, DDELayout{}));
+    SimpleDeviceMem e_device_buf(sizeof(EDataType) *
+                                 f_matrix_space_size(M, N, StrideE, DELayout{}));
 
-    // add device op instances
-    const auto op_ptrs = ck::tensor_operation::device::device_gemm_instance::
-        get_device_gemm_add_add_fastgelu_instances<ADataType,
-                                                   BDataType,
-                                                   AccDataType,
-                                                   D0DataType,
-                                                   D1DataType,
-                                                   EDataType,
+    using DeviceOp = ck::tensor_operation::device::DeviceGemmMultipleD<
         ALayout,
         BLayout,
-                                                   D0Layout,
-                                                   D1Layout,
-                                                   ELayout>();
+        DDELayout,
+        ADataType,
+        BDataType,
+        ck::Tuple<D0DataType, D1DataType>,
+        EDataType,
+        ck::tensor_operation::element_wise::PassThrough,
+        ck::tensor_operation::element_wise::PassThrough,
+        ck::tensor_operation::element_wise::AddAddFastGelu>;
+
+    // get device op instances
+    const auto op_ptrs = ck::tensor_operation::device::instance::DeviceOperationInstanceFactory<
+        DeviceOp>::GetInstances();
 
     std::cout << "found " << op_ptrs.size() << " instances" << std::endl;
 
@@ -231,6 +233,8 @@ int main(int argc, char* argv[])
         {
             invoker_ptr->Run(argument_ptr.get(), StreamConfig{nullptr, false});
         }
+
+        std::cout << "Done" << std::endl;
     }
 
     return 0;

client_example/03_gemm_layernorm/CMakeLists.txt

-add_executable(gemm_add_add_reduce_normalize gemm_add_add_layernorm.cpp)
-target_link_libraries(gemm_add_add_reduce_normalize PRIVATE composable_kernel::device_operations)
+add_executable(client_gemm_add_add_reduce_normalize gemm_add_add_layernorm.cpp)
+target_link_libraries(client_gemm_add_add_reduce_normalize PRIVATE composable_kernel::device_operations)

client_example/03_gemm_layernorm/gemm_add_add_layernorm.cpp

@@ -160,8 +160,9 @@ int main()
     ck::index_t StrideC  = 1024;
     ck::index_t StrideD0 = 1024;
 
-    const auto gemm_reduce_ptrs = ck::tensor_operation::device::device_gemm_instance::
-        get_device_gemm_add_add_mean_squaremean_instances<ADataType,
+    const auto gemm_reduce_ptrs =
+        ck::tensor_operation::device::instance::get_device_gemm_add_add_mean_squaremean_instances<
+            ADataType,
             BDataType,
             CDataType,
             ALayout,
@@ -169,7 +170,7 @@ int main()
             CLayout>();
 
     const auto normalize_ptrs =
-        ck::tensor_operation::device::get_device_normalize_from_mean_meansquare_instances<
+        ck::tensor_operation::device::instance::get_device_normalize_from_mean_meansquare_instances<
             CDataType,
             ReduceDataType,
             ReduceDataType,

client_example/CMakeLists.txt

@@ -6,5 +6,6 @@ find_package(composable_kernel 1.0.0 COMPONENTS device_operations)
 find_package(hip REQUIRED PATHS /opt/rocm)
 message(STATUS "Build with HIP ${hip_VERSION}")
 
+add_subdirectory(01_gemm)
 add_subdirectory(02_gemm_add_add_fastgelu)
 add_subdirectory(03_gemm_layernorm)

client_example/README.md

 ##
 Client application links to CK library, and therefore CK library needs to be installed before building client applications.
 
-## Docker script
-```bash
-docker run                                     \
--it                                            \
---privileged                                   \
---group-add sudo                               \
--w /root/workspace                             \
--v ${PATH_TO_LOCAL_WORKSPACE}:/root/workspace  \
-rocm/tensorflow:rocm5.1-tf2.6-dev              \
-/bin/bash
-```
 
 ## Build
 ```bash
@@ -22,7 +11,7 @@ cd client_example/build
 ```bash
 cmake                                                                 \
 -D CMAKE_CXX_COMPILER=/opt/rocm/bin/hipcc                             \
--D CMAKE_PREFIX_PATH=/opt/rocm                                        \
+-D CMAKE_PREFIX_PATH="/opt/rocm;${PATH_TO_CK_INSTALL_DIRECTORY}"      \
 ..
 ```
 

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

@@ -12,7 +12,13 @@ namespace ck {
 namespace tensor_operation {
 namespace device {
 
-template <typename AElementwiseOperation,
+template <typename ALayout,
+          typename BLayout,
+          typename CLayout,
+          typename ADataType,
+          typename BDataType,
+          typename CDataType,
+          typename AElementwiseOperation,
           typename BElementwiseOperation,
           typename CElementwiseOperation>
 struct DeviceBatchedGemm : public BaseOperator
@@ -34,11 +40,24 @@ struct DeviceBatchedGemm : public BaseOperator
     virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0;
 };
 
-template <typename AElementwiseOperation,
+template <typename ALayout,
+          typename BLayout,
+          typename CLayout,
+          typename ADataType,
+          typename BDataType,
+          typename CDataType,
+          typename AElementwiseOperation,
           typename BElementwiseOperation,
           typename CElementwiseOperation>
-using DeviceBatchedGemmPtr = std::unique_ptr<
-    DeviceBatchedGemm<AElementwiseOperation, BElementwiseOperation, CElementwiseOperation>>;
+using DeviceBatchedGemmPtr = std::unique_ptr<DeviceBatchedGemm<ALayout,
+                                                               BLayout,
+                                                               CLayout,
+                                                               ADataType,
+                                                               BDataType,
+                                                               CDataType,
+                                                               AElementwiseOperation,
+                                                               BElementwiseOperation,
+                                                               CElementwiseOperation>>;
 
 } // namespace device
 } // namespace tensor_operation

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

@@ -113,7 +113,7 @@ __global__ void
     ignore = c_element_op;
     ignore = compute_ptr_offset_of_batch;
     ignore = block_2_ctile_map;
-#endif // end of if (defined(__gfx908__) || defined(__gfx90a__))
+#endif
 }
 
 template <typename ADataType,
@@ -151,8 +151,15 @@ template <typename ADataType,
           bool BBlockLdsAddExtraN,
           ck::index_t CThreadTransferSrcDstVectorDim,
           ck::index_t CThreadTransferDstScalarPerVector>
-struct DeviceBatchedGemmXdl
-    : public DeviceBatchedGemm<AElementwiseOperation, BElementwiseOperation, CElementwiseOperation>
+struct DeviceBatchedGemmXdl : public DeviceBatchedGemm<ALayout,
+                                                       BLayout,
+                                                       CLayout,
+                                                       ADataType,
+                                                       BDataType,
+                                                       CDataType,
+                                                       AElementwiseOperation,
+                                                       BElementwiseOperation,
+                                                       CElementwiseOperation>
 {
     static constexpr auto I0 = Number<0>{};
     static constexpr auto I1 = Number<1>{};

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

@@ -17,12 +17,19 @@ struct GemmShape
     ck::index_t StrideA, StrideB, StrideC;
 };
 
-template <typename AElementwiseOperation,
+template <typename ALayout,
+          typename BLayout,
+          typename CLayout,
+          typename ADataType,
+          typename BDataType,
+          typename CDataType,
+          typename AElementwiseOperation,
           typename BElementwiseOperation,
           typename CElementwiseOperation>
 struct DeviceGemm : public BaseOperator
 {
-    virtual std::unique_ptr<BaseArgument> MakeArgumentPointer(const void* p_a,
+    virtual std::unique_ptr<BaseArgument>
+    MakeArgumentPointer(const void* p_a,
                         const void* p_b,
                         void* p_c,
                         ck::index_t M,
@@ -33,17 +40,29 @@ struct DeviceGemm : public BaseOperator
                         ck::index_t StrideC,
                         AElementwiseOperation a_element_op,
                         BElementwiseOperation b_element_op,
-                                                              CElementwiseOperation c_element_op,
-                                                              ck::index_t KBatch = 1) = 0;
+                        CElementwiseOperation c_element_op) = 0;
 
     virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0;
 };
 
-template <typename AElementwiseOperation,
+template <typename ALayout,
+          typename BLayout,
+          typename CLayout,
+          typename ADataType,
+          typename BDataType,
+          typename CDataType,
+          typename AElementwiseOperation,
           typename BElementwiseOperation,
           typename CElementwiseOperation>
-using DeviceGemmPtr = std::unique_ptr<
-    DeviceGemm<AElementwiseOperation, BElementwiseOperation, CElementwiseOperation>>;
+using DeviceGemmPtr = std::unique_ptr<DeviceGemm<ALayout,
+                                                 BLayout,
+                                                 CLayout,
+                                                 ADataType,
+                                                 BDataType,
+                                                 CDataType,
+                                                 AElementwiseOperation,
+                                                 BElementwiseOperation,
+                                                 CElementwiseOperation>>;
 
 template <typename AElementwiseOperation,
           typename BElementwiseOperation,

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

@@ -64,8 +64,16 @@ template <
             is_same_v<BElementwiseOperation, ck::tensor_operation::element_wise::PassThrough> &&
             is_same_v<CElementwiseOperation, ck::tensor_operation::element_wise::PassThrough>,
         bool> = false>
-struct DeviceGemmDl
-    : public DeviceGemm<AElementwiseOperation, BElementwiseOperation, CElementwiseOperation>
+struct DeviceGemmDl : public DeviceGemm<ALayout,
+                                        BLayout,
+                                        CLayout,
+                                        ADataType,
+                                        BDataType,
+                                        CDataType,
+                                        AElementwiseOperation,
+                                        BElementwiseOperation,
+                                        CElementwiseOperation>
+
 {
     static constexpr auto I0 = Number<0>{};
     static constexpr auto I1 = Number<1>{};
@@ -534,8 +542,7 @@ struct DeviceGemmDl
                                                       index_t StrideC,
                                                       AElementwiseOperation a_element_op,
                                                       BElementwiseOperation b_element_op,
-                                                      CElementwiseOperation c_element_op,
-                                                      index_t /* KBatch */ = 1) override
+                                                      CElementwiseOperation c_element_op) override
     {
         return std::make_unique<Argument>(static_cast<const ADataType*>(p_a),
                                           static_cast<const BDataType*>(p_b),

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

@@ -16,12 +16,20 @@ namespace device {
 // output : E[M, N]
 // C = a_op(A) * b_op(B)
 // E = cde_op(C, D0, D1, ...)
-template <ck::index_t NumDTensor,
+template <typename ALayout,
+          typename BLayout,
+          typename DELayout,
+          typename ADataType,
+          typename BDataType,
+          typename DsDataType,
+          typename EDataType,
           typename AElementwiseOperation,
           typename BElementwiseOperation,
           typename CDEElementwiseOperation>
 struct DeviceGemmMultipleD : public BaseOperator
 {
+    static constexpr index_t NumDTensor = DsDataType::Size();
+
     virtual std::unique_ptr<BaseArgument>
     MakeArgumentPointer(const void* p_a,
                         const void* p_b,
@@ -41,14 +49,26 @@ struct DeviceGemmMultipleD : public BaseOperator
     virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0;
 };
 
-template <ck::index_t NumDTensor,
+template <typename ALayout,
+          typename BLayout,
+          typename DELayout,
+          typename ADataType,
+          typename BDataType,
+          typename DsDataType,
+          typename EDataType,
           typename AElementwiseOperation,
           typename BElementwiseOperation,
-          typename CElementwiseOperation>
-using DeviceGemmMultipleDPtr = std::unique_ptr<DeviceGemmMultipleD<NumDTensor,
+          typename CDEElementwiseOperation>
+using DeviceGemmMultipleDPtr = std::unique_ptr<DeviceGemmMultipleD<ALayout,
+                                                                   BLayout,
+                                                                   DELayout,
+                                                                   ADataType,
+                                                                   BDataType,
+                                                                   DsDataType,
+                                                                   EDataType,
                                                                    AElementwiseOperation,
                                                                    BElementwiseOperation,
-                                                                   CElementwiseOperation>>;
+                                                                   CDEElementwiseOperation>>;
 
 } // namespace device
 } // namespace tensor_operation

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

@@ -96,7 +96,7 @@ namespace device {
 // E = cde_op(C, D0, D1, ...)
 template <typename ALayout,
           typename BLayout,
-          typename CDELayout,
+          typename DELayout,
           typename ADataType,
           typename BDataType,
           typename GemmAccDataType,
@@ -137,7 +137,13 @@ template <typename ALayout,
           typename CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
           index_t CDEBlockTransferScalarPerVector_NPerBlock,
           LoopScheduler LoopSched = make_default_loop_scheduler()>
-struct DeviceGemmMultipleD_Xdl_CShuffle : public DeviceGemmMultipleD<DsDataType::Size(),
+struct DeviceGemmMultipleD_Xdl_CShuffle : public DeviceGemmMultipleD<ALayout,
+                                                                     BLayout,
+                                                                     DELayout,
+                                                                     ADataType,
+                                                                     BDataType,
+                                                                     DsDataType,
+                                                                     EDataType,
                                                                      AElementwiseOperation,
                                                                      BElementwiseOperation,
                                                                      CDEElementwiseOperation>
@@ -360,12 +366,12 @@ struct DeviceGemmMultipleD_Xdl_CShuffle : public DeviceGemmMultipleD<DsDataType:
     static auto MakeCGridDescriptor_M_N(index_t MRaw, index_t NRaw, index_t StrideE)
     {
         const auto c_grid_desc_mraw_nraw = [&]() {
-            if constexpr(is_same<tensor_layout::gemm::RowMajor, CDELayout>::value)
+            if constexpr(is_same<tensor_layout::gemm::RowMajor, DELayout>::value)
             {
                 return make_naive_tensor_descriptor(make_tuple(MRaw, NRaw),
                                                     make_tuple(StrideE, I1));
             }
-            else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, CDELayout>::value)
+            else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, DELayout>::value)
             {
                 return make_naive_tensor_descriptor(make_tuple(MRaw, NRaw),
                                                     make_tuple(I1, StrideE));

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

@@ -2,13 +2,16 @@
 // Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
 
 #pragma once
+
 #include <iostream>
+
 #include "device_base.hpp"
 
 namespace ck {
 namespace tensor_operation {
 namespace device {
 
+// FIXME: DeviceGemmReduce type need to well define the problem
 template <ck::index_t NumDTensor, ck::index_t NumReduce>
 struct DeviceGemmReduce : public BaseOperator
 {

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

@@ -2,6 +2,7 @@
 // Copyright (c) 2018-2022, Advanced Micro Devices, Inc. All rights reserved.
 
 #pragma once
+
 #include <iostream>
 #include <vector>
 
@@ -11,7 +12,13 @@ namespace ck {
 namespace tensor_operation {
 namespace device {
 
-template <typename AElementwiseOperation,
+template <typename ALayout,
+          typename BLayout,
+          typename CLayout,
+          typename ADataType,
+          typename BDataType,
+          typename CDataType,
+          typename AElementwiseOperation,
           typename BElementwiseOperation,
           typename CElementwiseOperation>
 struct DeviceGemmSplitK : public BaseOperator
@@ -33,11 +40,24 @@ struct DeviceGemmSplitK : public BaseOperator
     virtual std::unique_ptr<BaseInvoker> MakeInvokerPointer() = 0;
 };
 
-template <typename AElementwiseOperation,
+template <typename ALayout,
+          typename BLayout,
+          typename CLayout,
+          typename ADataType,
+          typename BDataType,
+          typename CDataType,
+          typename AElementwiseOperation,
           typename BElementwiseOperation,
           typename CElementwiseOperation>
-using DeviceGemmSplitKPtr = std::unique_ptr<
-    DeviceGemmSplitK<AElementwiseOperation, BElementwiseOperation, CElementwiseOperation>>;
+using DeviceGemmSplitKPtr = std::unique_ptr<DeviceGemmSplitK<ALayout,
+                                                             BLayout,
+                                                             CLayout,
+                                                             ADataType,
+                                                             BDataType,
+                                                             CDataType,
+                                                             AElementwiseOperation,
+                                                             BElementwiseOperation,
+                                                             CElementwiseOperation>>;
 
 } // namespace device
 } // namespace tensor_operation

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

@@ -57,8 +57,15 @@ template <typename ADataType,
           ck::index_t CThreadTransferSrcDstVectorDim,
           ck::index_t CThreadTransferDstScalarPerVector,
           ck::index_t NumPrefetch = 1>
-struct DeviceGemmXdl
-    : public DeviceGemm<AElementwiseOperation, BElementwiseOperation, CElementwiseOperation>
+struct DeviceGemmXdl : public DeviceGemm<ALayout,
+                                         BLayout,
+                                         CLayout,
+                                         ADataType,
+                                         BDataType,
+                                         CDataType,
+                                         AElementwiseOperation,
+                                         BElementwiseOperation,
+                                         CElementwiseOperation>
 {
     static constexpr auto I0 = Number<0>{};
     static constexpr auto I1 = Number<1>{};
@@ -487,8 +494,7 @@ struct DeviceGemmXdl
                                                       index_t StrideC,
                                                       AElementwiseOperation a_element_op,
                                                       BElementwiseOperation b_element_op,
-                                                      CElementwiseOperation c_element_op,
-                                                      index_t /* KBatch */ = 1) override
+                                                      CElementwiseOperation c_element_op) override
     {
         return std::make_unique<Argument>(static_cast<const ADataType*>(p_a),
                                           static_cast<const BDataType*>(p_b),

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

@@ -65,8 +65,15 @@ template <typename ALayout,
           typename CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
           index_t CShuffleBlockTransferScalarPerVector_NPerBlock,
           LoopScheduler LoopSched = make_default_loop_scheduler()>
-struct DeviceGemm_Xdl_CShuffle
-    : public DeviceGemm<AElementwiseOperation, BElementwiseOperation, CElementwiseOperation>
+struct DeviceGemm_Xdl_CShuffle : public DeviceGemm<ALayout,
+                                                   BLayout,
+                                                   CLayout,
+                                                   ADataType,
+                                                   BDataType,
+                                                   CDataType,
+                                                   AElementwiseOperation,
+                                                   BElementwiseOperation,
+                                                   CElementwiseOperation>
 {
     using DeviceOp = DeviceGemm_Xdl_CShuffle;
 
@@ -622,8 +629,7 @@ struct DeviceGemm_Xdl_CShuffle
                                                       index_t StrideC,
                                                       AElementwiseOperation a_element_op,
                                                       BElementwiseOperation b_element_op,
-                                                      CElementwiseOperation c_element_op,
-                                                      index_t /* KBatch */ = 1) override
+                                                      CElementwiseOperation c_element_op) override
     {
         return std::make_unique<Argument>(static_cast<const ADataType*>(p_a),
                                           static_cast<const BDataType*>(p_b),

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

@@ -56,8 +56,15 @@ template <typename ADataType,
           bool BBlockLdsAddExtraN,
           ck::index_t CThreadTransferSrcDstVectorDim,
           ck::index_t CThreadTransferDstScalarPerVector>
-struct DeviceGemmXdlSplitK
-    : public DeviceGemmSplitK<AElementwiseOperation, BElementwiseOperation, CElementwiseOperation>
+struct DeviceGemmXdlSplitK : public DeviceGemmSplitK<ALayout,
+                                                     BLayout,
+                                                     CLayout,
+                                                     ADataType,
+                                                     BDataType,
+                                                     CDataType,
+                                                     AElementwiseOperation,
+                                                     BElementwiseOperation,
+                                                     CElementwiseOperation>
 {
     static constexpr auto I0 = Number<0>{};
     static constexpr auto I1 = Number<1>{};

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

@@ -58,8 +58,15 @@ template <typename ADataType,
           index_t CShuffleNRepeatPerShuffle,
           typename CBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
           index_t CBlockTransferScalarPerVector_NWaveNPerXDL>
-struct DeviceGemmXdlSplitKCShuffle
-    : public DeviceGemmSplitK<AElementwiseOperation, BElementwiseOperation, CElementwiseOperation>
+struct DeviceGemmXdlSplitKCShuffle : public DeviceGemmSplitK<ALayout,
+                                                             BLayout,
+                                                             CLayout,
+                                                             ADataType,
+                                                             BDataType,
+                                                             CDataType,
+                                                             AElementwiseOperation,
+                                                             BElementwiseOperation,
+                                                             CElementwiseOperation>
 {
     static constexpr auto I0 = Number<0>{};
     static constexpr auto I1 = Number<1>{};