merge develop

include/ck/tensor_operation/gpu/device/impl/device_elementwise_2d_impl.hpp

@@ -13,6 +13,7 @@
 #include "ck/tensor_description/tensor_descriptor_helper.hpp"
 
 #include "ck/host_utility/kernel_launch.hpp"
+#include "ck/host_utility/stream_utility.hpp"
 
 namespace ck {
 namespace tensor_operation {
@@ -171,10 +172,7 @@ struct DeviceElementwise2dImpl : public DeviceElementwise<InDataTypeTuple,
               inStridesArray_(inStridesArray),
               outStridesArray_(outStridesArray),
               elementwise_op_(elementwise_op),
-              blockSize_(256),
-              gridSize_(120), // FIXME - Calculate the grid size by number of CU in the future
-              num_threads_m_((gridSize_ * blockSize_) / 16),
-              num_threads_n_(16)
+              blockSize_(256)
         {
             static_assert(NumDim_m > 0, "");
             static_assert(NumDim_n > 0, "");
@@ -192,34 +190,10 @@ struct DeviceElementwise2dImpl : public DeviceElementwise<InDataTypeTuple,
                     return static_cast<DataType*>(out_dev_buffers[I.value]);
                 },
                 Number<NumOutput>{});
-
-            in_grid_2d_desc_tuple_ = generate_tuple(
-                [&](auto I) {
-                    return MakeDescriptor_MN(lengths,
-                                             inStridesArray[I.value],
-                                             gridSize_,
-                                             blockSize_,
-                                             num_threads_m_,
-                                             num_threads_n_);
-                },
-                Number<NumInput>{});
-
-            out_grid_2d_desc_tuple_ = generate_tuple(
-                [&](auto I) {
-                    return MakeDescriptor_MN(lengths,
-                                             outStridesArray[I.value],
-                                             gridSize_,
-                                             blockSize_,
-                                             num_threads_m_,
-                                             num_threads_n_);
-                },
-                Number<NumOutput>{});
         }
 
         InDataTypePointerTuple in_dev_buffers_;
         OutDataTypePointerTuple out_dev_buffers_;
-        InGrid2dDescTuple in_grid_2d_desc_tuple_;
-        OutGrid2dDescTuple out_grid_2d_desc_tuple_;
 
         std::array<index_t, NumDim> lengths_;
         std::array<std::array<index_t, NumDim>, NumInput> inStridesArray_;
@@ -227,15 +201,38 @@ struct DeviceElementwise2dImpl : public DeviceElementwise<InDataTypeTuple,
 
         ElementwiseOperation elementwise_op_;
         index_t blockSize_;
-        index_t gridSize_;
-        index_t num_threads_m_;
-        index_t num_threads_n_;
     };
 
     struct Invoker : public BaseInvoker
     {
         float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
         {
+            index_t gridSize      = getAvailableComputeUnitCount(stream_config);
+            index_t num_threads_m = (gridSize * arg.blockSize_) / 16;
+            index_t num_threads_n = 16;
+
+            auto in_grid_2d_desc_tuple = generate_tuple(
+                [&](auto I) {
+                    return MakeDescriptor_MN(arg.lengths_,
+                                             arg.inStridesArray_[I.value],
+                                             gridSize,
+                                             arg.blockSize_,
+                                             num_threads_m,
+                                             num_threads_n);
+                },
+                Number<NumInput>{});
+
+            auto out_grid_2d_desc_tuple = generate_tuple(
+                [&](auto I) {
+                    return MakeDescriptor_MN(arg.lengths_,
+                                             arg.outStridesArray_[I.value],
+                                             gridSize,
+                                             arg.blockSize_,
+                                             num_threads_m,
+                                             num_threads_n);
+                },
+                Number<NumOutput>{});
+
             const auto kernel = kernel_elementwise_2d<GridwiseElementwise,
                                                       InGrid2dDescTuple,
                                                       OutGrid2dDescTuple,
@@ -245,16 +242,16 @@ struct DeviceElementwise2dImpl : public DeviceElementwise<InDataTypeTuple,
 
             float elapsed_time = launch_and_time_kernel(stream_config,
                                                         kernel,
-                                                        dim3(arg.gridSize_),
+                                                        dim3(gridSize),
                                                         dim3(arg.blockSize_),
                                                         0,
-                                                        arg.in_grid_2d_desc_tuple_,
-                                                        arg.out_grid_2d_desc_tuple_,
+                                                        in_grid_2d_desc_tuple,
+                                                        out_grid_2d_desc_tuple,
                                                         arg.in_dev_buffers_,
                                                         arg.out_dev_buffers_,
                                                         arg.elementwise_op_,
-                                                        arg.num_threads_m_,
-                                                        arg.num_threads_n_);
+                                                        num_threads_m,
+                                                        num_threads_n);
             return elapsed_time;
         }
 

include/ck/tensor_operation/gpu/device/impl/device_elementwise_3d_impl.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include <iostream>
+#include <sstream>
+
+#include "ck/utility/math.hpp"
+#include "ck/utility/sequence.hpp"
+#include "ck/tensor_operation/gpu/device/device_elementwise.hpp"
+#include "ck/tensor_operation/gpu/grid/gridwise_elementwise_3d.hpp"
+#include "ck/tensor_description/tensor_descriptor_helper.hpp"
+
+#include "ck/host_utility/kernel_launch.hpp"
+#include "ck/host_utility/device_prop.hpp"
+#include "ck/host_utility/stream_utility.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+template <typename InDataTypeTuple,
+          typename OutDataTypeTuple,
+          typename ElementwiseOperation,
+          index_t NumDim_m, // choose how to set dims
+          index_t NumDim_n,
+          index_t NumDim_k,
+          index_t MPerThread,
+          index_t NPerThread,
+          index_t KPerThread,
+          typename InScalarPerVectorSeq,
+          typename OutScalarPerVectorSeq>
+struct DeviceElementwise3dImpl : public DeviceElementwise<InDataTypeTuple,
+                                                          OutDataTypeTuple,
+                                                          ElementwiseOperation,
+                                                          NumDim_m + NumDim_n + NumDim_k>
+{
+    static constexpr index_t NumDim = NumDim_m + NumDim_n + NumDim_k;
+
+    static constexpr int NumInput  = InDataTypeTuple::Size();
+    static constexpr int NumOutput = OutDataTypeTuple::Size();
+
+    static constexpr auto I0 = Number<0>{};
+    static constexpr auto I1 = Number<1>{};
+    static constexpr auto I2 = Number<2>{};
+    static constexpr auto I3 = Number<3>{};
+    static constexpr auto I4 = Number<4>{};
+
+    static_assert(NumInput == InScalarPerVectorSeq::Size() &&
+                      NumOutput == OutScalarPerVectorSeq::Size(),
+                  "Tuple size is inconsistent with the number of in/out!");
+
+    static auto GenerateInDataTypePointerTuple()
+    {
+        return generate_tuple(
+            [&](auto I) {
+                using DataType = remove_cvref_t<decltype(InDataTypeTuple{}[I])>;
+
+                return static_cast<const DataType*>(nullptr);
+            },
+            Number<NumInput>{});
+    }
+
+    static auto GenerateOutDataTypePointerTuple()
+    {
+        return generate_tuple(
+            [&](auto I) {
+                using DataType = remove_cvref_t<decltype(OutDataTypeTuple{}[I])>;
+
+                return static_cast<DataType*>(nullptr);
+            },
+            Number<NumOutput>{});
+    }
+
+    using InDataTypePointerTuple  = decltype(GenerateInDataTypePointerTuple());
+    using OutDataTypePointerTuple = decltype(GenerateOutDataTypePointerTuple());
+
+    template <typename Desc_MNK>
+    static auto PadDescriptor_MNK(Desc_MNK desc_mnk,
+                                  index_t gridSize,
+                                  index_t blockSize,
+                                  index_t num_threads_m,
+                                  index_t num_threads_n,
+                                  index_t num_threads_k)
+    {
+        std::ignore = blockSize;
+        std::ignore = gridSize;
+
+        const auto m = desc_mnk.GetLength(I0);
+        const auto n = desc_mnk.GetLength(I1);
+        const auto k = desc_mnk.GetLength(I2);
+
+        const index_t loop_step_m = num_threads_m * MPerThread;
+        const index_t loop_step_n = num_threads_n * NPerThread;
+        const index_t loop_step_k = num_threads_k * KPerThread;
+
+        const auto pad_m = math::integer_least_multiple(m, loop_step_m) - m;
+        const auto pad_n = math::integer_least_multiple(n, loop_step_n) - n;
+        const auto pad_k = math::integer_least_multiple(k, loop_step_k) - k;
+
+        const auto desc_mnk_pad =
+            transform_tensor_descriptor(desc_mnk,
+                                        make_tuple(make_right_pad_transform(m, pad_m),
+                                                   make_right_pad_transform(n, pad_n),
+                                                   make_right_pad_transform(k, pad_k)),
+                                        make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}),
+                                        make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}));
+        return desc_mnk_pad;
+    }
+
+    static auto MakeDescriptor_MNK(const std::array<index_t, NumDim>& lengths,
+                                   const std::array<index_t, NumDim>& stride,
+                                   index_t gridSize,
+                                   index_t blockSize,
+                                   index_t num_threads_m,
+                                   index_t num_threads_n,
+                                   index_t num_threads_k)
+    {
+        auto tupleOfShape  = generate_tuple([&](auto I) { return lengths[I]; }, Number<NumDim>{});
+        auto tupleOfStride = generate_tuple([&](auto I) { return stride[I]; }, Number<NumDim>{});
+
+        // nd desc - [s0, s1, s2, ...]
+        const auto desc = make_naive_tensor_descriptor(tupleOfShape, tupleOfStride);
+
+        constexpr auto mDimIds = typename arithmetic_sequence_gen<0, NumDim_m, 1>::type();
+        constexpr auto nDimIds =
+            typename arithmetic_sequence_gen<NumDim_m, NumDim_m + NumDim_n, 1>::type();
+        constexpr auto kDimIds =
+            typename arithmetic_sequence_gen<NumDim_m + NumDim_n, NumDim, 1>::type();
+
+        const auto mLengths = get_container_subset(tupleOfShape, mDimIds);
+        const auto nLengths = get_container_subset(tupleOfShape, nDimIds);
+        const auto kLengths = get_container_subset(tupleOfShape, kDimIds);
+
+        // merge nd to 3d desc - [s0 * s1 * ...]
+        if constexpr(NumDim > 3)
+        {
+            const auto desc_mnk = transform_tensor_descriptor(
+                desc,
+                make_tuple(make_merge_transform(mLengths),
+                           make_merge_transform(nLengths),
+                           make_merge_transform(kLengths)),
+                make_tuple(mDimIds, nDimIds, kDimIds),
+                make_tuple(Sequence<0>{}, Sequence<1>{}, Sequence<2>{}));
+
+            return PadDescriptor_MNK(
+                desc_mnk, gridSize, blockSize, num_threads_m, num_threads_n, num_threads_k);
+        }
+        else
+            return PadDescriptor_MNK(
+                desc, gridSize, blockSize, num_threads_m, num_threads_n, num_threads_k);
+    }
+
+    template <index_t TupleSize>
+    static auto GenerateInOutGrid3dDescTuple(Number<TupleSize>)
+    {
+        return generate_tuple(
+            [&](auto) {
+                if constexpr(NumDim > 3)
+                {
+                    return MakeDescriptor_MNK({1, 1, 1}, {1, 1, 1}, 1, 1, 1, 1, 1);
+                }
+                else
+                {
+                    return MakeDescriptor_MNK({1}, {1}, 1, 1, 1, 1, 1);
+                };
+            },
+            Number<TupleSize>{});
+    }
+
+    using OutGrid3dDescTuple = decltype(GenerateInOutGrid3dDescTuple(Number<NumOutput>{}));
+    using InGrid3dDescTuple  = decltype(GenerateInOutGrid3dDescTuple(Number<NumInput>{}));
+
+    using GridwiseElementwise = GridwiseElementwise_3D<InGrid3dDescTuple,
+                                                       OutGrid3dDescTuple,
+                                                       InDataTypePointerTuple,
+                                                       OutDataTypePointerTuple,
+                                                       ElementwiseOperation,
+                                                       MPerThread,
+                                                       NPerThread,
+                                                       KPerThread,
+                                                       InScalarPerVectorSeq,
+                                                       OutScalarPerVectorSeq>;
+
+    struct Argument : public BaseArgument
+    {
+        Argument(const std::array<index_t, NumDim> lengths,
+                 const std::array<std::array<index_t, NumDim>, NumInput> inStridesArray,
+                 const std::array<std::array<index_t, NumDim>, NumOutput> outStridesArray,
+                 const std::array<const void*, NumInput> in_dev_buffers,
+                 const std::array<void*, NumOutput> out_dev_buffers,
+                 ElementwiseOperation elementwise_op)
+
+            : lengths_(lengths),
+              inStridesArray_(inStridesArray),
+              outStridesArray_(outStridesArray),
+              elementwise_op_(elementwise_op),
+              blockSize_(256)
+        {
+            static_assert(NumDim_m > 0, "");
+            static_assert(NumDim_n > 0, "");
+            static_assert(NumDim_k > 0, "");
+
+            in_dev_buffers_ = generate_tuple(
+                [&](auto I) {
+                    using DataType = remove_cvref_t<decltype(InDataTypeTuple{}[I])>;
+                    return static_cast<const DataType*>(in_dev_buffers[I.value]);
+                },
+                Number<NumInput>{});
+
+            out_dev_buffers_ = generate_tuple(
+                [&](auto I) {
+                    using DataType = remove_cvref_t<decltype(OutDataTypeTuple{}[I])>;
+                    return static_cast<DataType*>(out_dev_buffers[I.value]);
+                },
+                Number<NumOutput>{});
+        }
+
+        InDataTypePointerTuple in_dev_buffers_;
+        OutDataTypePointerTuple out_dev_buffers_;
+
+        std::array<index_t, NumDim> lengths_;
+        std::array<std::array<index_t, NumDim>, NumInput> inStridesArray_;
+        std::array<std::array<index_t, NumDim>, NumOutput> outStridesArray_;
+
+        ElementwiseOperation elementwise_op_;
+        index_t blockSize_;
+    };
+
+    struct Invoker : public BaseInvoker
+    {
+        float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
+        {
+            index_t gridSize      = getAvailableComputeUnitCount(stream_config) * arg.blockSize_;
+            index_t num_threads_m = gridSize / (16 * 16);
+            index_t num_threads_n = 16;
+            index_t num_threads_k = 16;
+
+            auto in_grid_3d_desc_tuple = generate_tuple(
+                [&](auto I) {
+                    return MakeDescriptor_MNK(arg.lengths_,
+                                              arg.inStridesArray_[I.value],
+                                              gridSize,
+                                              arg.blockSize_,
+                                              num_threads_m,
+                                              num_threads_n,
+                                              num_threads_k);
+                },
+                Number<NumInput>{});
+
+            auto out_grid_3d_desc_tuple = generate_tuple(
+                [&](auto I) {
+                    return MakeDescriptor_MNK(arg.lengths_,
+                                              arg.outStridesArray_[I.value],
+                                              gridSize,
+                                              arg.blockSize_,
+                                              num_threads_m,
+                                              num_threads_n,
+                                              num_threads_k);
+                },
+                Number<NumOutput>{});
+
+            const auto kernel = kernel_elementwise_3d<GridwiseElementwise,
+                                                      InGrid3dDescTuple,
+                                                      OutGrid3dDescTuple,
+                                                      InDataTypePointerTuple,
+                                                      OutDataTypePointerTuple,
+                                                      ElementwiseOperation>;
+
+            float elapsed_time = launch_and_time_kernel(stream_config,
+                                                        kernel,
+                                                        dim3(gridSize),
+                                                        dim3(arg.blockSize_),
+                                                        0,
+                                                        in_grid_3d_desc_tuple,
+                                                        out_grid_3d_desc_tuple,
+                                                        arg.in_dev_buffers_,
+                                                        arg.out_dev_buffers_,
+                                                        arg.elementwise_op_,
+                                                        num_threads_m,
+                                                        num_threads_n,
+                                                        num_threads_k);
+            return elapsed_time;
+        }
+
+        // polymorphic
+        float Run(const BaseArgument* p_arg,
+                  const StreamConfig& stream_config = StreamConfig{}) override
+        {
+            return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
+        }
+    };
+
+    bool IsSupportedArgument(const BaseArgument* p_arg) override
+    {
+        if((ck::get_device_name() == "gfx940" || ck::get_device_name() == "gfx941" ||
+            ck::get_device_name() == "gfx942"))
+        {
+            return false;
+        }
+
+        const Argument* pArg = dynamic_cast<const Argument*>(p_arg);
+
+        if(pArg == nullptr)
+            return false;
+
+        if(pArg->lengths_.back() % MPerThread != 0)
+            return false;
+
+        auto IsScalarPerVectorValid = [&](const std::array<index_t, NumDim>& lengths,
+                                          const std::array<index_t, NumDim>& strides,
+                                          index_t scalarPerVector,
+                                          index_t vectorDim) {
+            if(strides[vectorDim] == 1 &&
+               (lengths[vectorDim] % scalarPerVector == 0 ||
+                lengths[vectorDim] % scalarPerVector == lengths[vectorDim]))
+            {
+                return true;
+            }
+
+            if(strides[vectorDim] >= scalarPerVector)
+            {
+                return true;
+            }
+            return false;
+        };
+
+        bool valid = true;
+        static_for<0, NumInput, 1>{}([&](auto I) {
+            valid = valid && IsScalarPerVectorValid(pArg->lengths_,
+                                                    pArg->inStridesArray_[I.value],
+                                                    InScalarPerVectorSeq::At(I),
+                                                    NumDim_m - 1);
+        });
+
+        static_for<0, NumOutput, 1>{}([&](auto I) {
+            valid = valid && IsScalarPerVectorValid(pArg->lengths_,
+                                                    pArg->outStridesArray_[I.value],
+                                                    OutScalarPerVectorSeq::At(I),
+                                                    NumDim - 1);
+        });
+
+        return valid;
+    }
+
+    std::unique_ptr<BaseArgument>
+    MakeArgumentPointer(const std::array<index_t, NumDim> lengths,
+                        const std::array<std::array<index_t, NumDim>, NumInput> inStridesArray,
+                        const std::array<std::array<index_t, NumDim>, NumOutput> outStridesArray,
+                        const std::array<const void*, NumInput> in_dev_buffers,
+                        const std::array<void*, NumOutput> out_dev_buffers,
+                        ElementwiseOperation elementwise_op) override
+    {
+        return std::make_unique<Argument>(lengths,
+                                          inStridesArray,
+                                          outStridesArray,
+                                          in_dev_buffers,
+                                          out_dev_buffers,
+                                          elementwise_op);
+    }
+
+    static auto MakeInvoker() { return Invoker{}; }
+    std::unique_ptr<BaseInvoker> MakeInvokerPointer() override
+    {
+        return std::make_unique<Invoker>();
+    }
+}; // namespace device
+
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

include/ck/tensor_operation/gpu/device/impl/device_elementwise_impl.hpp

@@ -13,6 +13,7 @@
 #include "ck/tensor_description/tensor_descriptor_helper.hpp"
 
 #include "ck/host_utility/kernel_launch.hpp"
+#include "ck/host_utility/stream_utility.hpp"
 
 namespace ck {
 namespace tensor_operation {
@@ -144,8 +145,7 @@ struct DeviceElementwiseImpl
               inStridesArray_(inStridesArray),
               outStridesArray_(outStridesArray),
               elementwise_op_(elementwise_op),
-              blockSize_(256),
-              gridSize_(120) // FIXME - Calculate the grid size by number of CU in the future
+              blockSize_(256)
         {
             in_dev_buffers_ = generate_tuple(
                 [&](auto I) {
@@ -160,26 +160,10 @@ struct DeviceElementwiseImpl
                     return static_cast<DataType*>(out_dev_buffers[I.value]);
                 },
                 Number<NumOutput>{});
-
-            in_grid_1d_desc_tuple_ = generate_tuple(
-                [&](auto I) {
-                    return MakeDescriptor_M(
-                        lengths, inStridesArray[I.value], gridSize_, blockSize_);
-                },
-                Number<NumInput>{});
-
-            out_grid_1d_desc_tuple_ = generate_tuple(
-                [&](auto I) {
-                    return MakeDescriptor_M(
-                        lengths, outStridesArray[I.value], gridSize_, blockSize_);
-                },
-                Number<NumOutput>{});
         }
 
         InDataTypePointerTuple in_dev_buffers_;
         OutDataTypePointerTuple out_dev_buffers_;
-        InGrid1dDescTuple in_grid_1d_desc_tuple_;
-        OutGrid1dDescTuple out_grid_1d_desc_tuple_;
 
         std::array<index_t, NumDim> lengths_;
         std::array<std::array<index_t, NumDim>, NumInput> inStridesArray_;
@@ -187,13 +171,28 @@ struct DeviceElementwiseImpl
 
         ElementwiseOperation elementwise_op_;
         index_t blockSize_;
-        index_t gridSize_;
     };
 
     struct Invoker : public BaseInvoker
     {
         float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
         {
+            index_t gridSize = getAvailableComputeUnitCount(stream_config);
+
+            auto in_grid_1d_desc_tuple = generate_tuple(
+                [&](auto I) {
+                    return MakeDescriptor_M(
+                        arg.lengths_, arg.inStridesArray_[I.value], gridSize, arg.blockSize_);
+                },
+                Number<NumInput>{});
+
+            auto out_grid_1d_desc_tuple = generate_tuple(
+                [&](auto I) {
+                    return MakeDescriptor_M(
+                        arg.lengths_, arg.outStridesArray_[I.value], gridSize, arg.blockSize_);
+                },
+                Number<NumOutput>{});
+
             const auto kernel = kernel_elementwise_1d<GridwiseElementwise,
                                                       InGrid1dDescTuple,
                                                       OutGrid1dDescTuple,
@@ -203,11 +202,11 @@ struct DeviceElementwiseImpl
 
             float elapsed_time = launch_and_time_kernel(stream_config,
                                                         kernel,
-                                                        dim3(arg.gridSize_),
+                                                        dim3(gridSize),
                                                         dim3(arg.blockSize_),
                                                         0,
-                                                        arg.in_grid_1d_desc_tuple_,
-                                                        arg.out_grid_1d_desc_tuple_,
+                                                        in_grid_1d_desc_tuple,
+                                                        out_grid_1d_desc_tuple,
                                                         arg.in_dev_buffers_,
                                                         arg.out_dev_buffers_,
                                                         arg.elementwise_op_);
@@ -297,6 +296,28 @@ struct DeviceElementwiseImpl
     {
         return std::make_unique<Invoker>();
     };
+
+    std::string GetTypeString() const override
+    {
+        auto str = std::stringstream();
+
+        // clang-format off
+        str << "DeviceElementwiseImpl<" ;
+        str << "NumDim_" << NumDim << ","; 
+	str << "MPerThread_" << MPerThread << ","; 
+
+        str << "InScalarPerVector"; 
+        static_for<0, InScalarPerVectorSeq::Size(), 1>{}([&](auto i) { str << "_" << InScalarPerVectorSeq::At(i).value; });
+        str << ","; 
+        str << "OutScalarPerVector"; 
+        static_for<0, OutScalarPerVectorSeq::Size(), 1>{}([&](auto i) { str << "_" << OutScalarPerVectorSeq::At(i).value; });
+
+        str << ">";
+        // clang-format on
+
+        return str.str();
+    }
+
 }; // namespace device
 
 } // namespace device

include/ck/tensor_operation/gpu/device/impl/device_elementwise_scale_impl.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include <iostream>
+#include <sstream>
+
+#include "ck/utility/math.hpp"
+#include "ck/utility/sequence.hpp"
+#include "ck/tensor_operation/gpu/device/device_elementwise_scale.hpp"
+#include "ck/tensor_operation/gpu/grid/gridwise_elementwise_1d_scale.hpp"
+#include "ck/tensor_description/tensor_descriptor_helper.hpp"
+
+#include "ck/host_utility/kernel_launch.hpp"
+#include "ck/host_utility/stream_utility.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+
+template <typename InDataTypeTuple,
+          typename OutDataTypeTuple,
+          typename ElementwiseOperation,
+          typename UnaryOperation,
+          typename Scale,
+          index_t NumDim,
+          index_t MPerThread,
+          typename InScalarPerVectorSeq,
+          typename OutScalarPerVectorSeq>
+struct DeviceElementwiseImpl : public DeviceElementwise<InDataTypeTuple,
+                                                        OutDataTypeTuple,
+                                                        ElementwiseOperation,
+                                                        UnaryOperation,
+                                                        Scale,
+                                                        NumDim>
+{
+    static constexpr int NumInput  = InDataTypeTuple::Size();
+    static constexpr int NumOutput = OutDataTypeTuple::Size();
+
+    static_assert(NumInput == InScalarPerVectorSeq::Size() &&
+                      NumOutput == OutScalarPerVectorSeq::Size(),
+                  "Tuple size is inconsistent with the number of in/out!");
+
+    static auto GenerateInDataTypePointerTuple()
+    {
+        return generate_tuple(
+            [&](auto I) {
+                using DataType = remove_cvref_t<decltype(InDataTypeTuple{}[I])>;
+
+                return static_cast<const DataType*>(nullptr);
+            },
+            Number<NumInput>{});
+    };
+
+    static auto GenerateOutDataTypePointerTuple()
+    {
+        return generate_tuple(
+            [&](auto I) {
+                using DataType = remove_cvref_t<decltype(OutDataTypeTuple{}[I])>;
+
+                return static_cast<DataType*>(nullptr);
+            },
+            Number<NumOutput>{});
+    };
+
+    using InDataTypePointerTuple  = decltype(GenerateInDataTypePointerTuple());
+    using OutDataTypePointerTuple = decltype(GenerateOutDataTypePointerTuple());
+
+    template <typename Desc_M>
+    static auto PadDescriptor_M_1d(Desc_M desc_m, index_t gridSize, index_t blockSize)
+    {
+        constexpr auto I0 = Number<0>{};
+
+        const auto m            = desc_m.GetLength(I0);
+        const index_t loop_step = gridSize * blockSize * MPerThread;
+        const auto pad          = math::integer_least_multiple(m, loop_step) - m;
+        const auto desc_m_pad =
+            transform_tensor_descriptor(desc_m,
+                                        make_tuple(make_right_pad_transform(m, pad)),
+                                        make_tuple(Sequence<0>{}),
+                                        make_tuple(Sequence<0>{}));
+        return desc_m_pad;
+    }
+
+    static auto MakeDescriptor_M(const std::array<index_t, NumDim>& lengths,
+                                 const std::array<index_t, NumDim>& stride,
+                                 index_t gridSize,
+                                 index_t blockSize)
+    {
+        auto tupleOfShape  = generate_tuple([&](auto I) { return lengths[I]; }, Number<NumDim>{});
+        auto tupleOfStride = generate_tuple([&](auto I) { return stride[I]; }, Number<NumDim>{});
+
+        // nd desc - [s0, s1, s2, ...]
+        const auto desc = make_naive_tensor_descriptor(tupleOfShape, tupleOfStride);
+
+        // merge nd to 1d desc - [s0 * s1 * ...]
+        if constexpr(NumDim > 1)
+        {
+            const auto desc_m = transform_tensor_descriptor(
+                desc,
+                make_tuple(make_merge_transform(tupleOfShape)),
+                make_tuple(generate_sequence_v2([&](auto I) { return I; }, Number<NumDim>{})),
+                make_tuple(Sequence<0>{}));
+
+            return PadDescriptor_M_1d(desc_m, gridSize, blockSize);
+        }
+        else
+            return PadDescriptor_M_1d(desc, gridSize, blockSize);
+    }
+
+    template <index_t TupleSize>
+    static auto GenerateInOutGrid1dDescTuple(Number<TupleSize>)
+    {
+        return generate_tuple(
+            [&](auto) {
+                if constexpr(NumDim > 1)
+                {
+                    return MakeDescriptor_M({1, 1}, {1, 1}, 1, 1);
+                }
+                else
+                {
+                    return MakeDescriptor_M({1}, {1}, 1, 1);
+                };
+            },
+            Number<TupleSize>{});
+    };
+
+    using InGrid1dDescTuple  = decltype(GenerateInOutGrid1dDescTuple(Number<NumInput>{}));
+    using OutGrid1dDescTuple = decltype(GenerateInOutGrid1dDescTuple(Number<NumOutput>{}));
+
+    using GridwiseElementwise = GridwiseElementwise_1D<InGrid1dDescTuple,
+                                                       OutGrid1dDescTuple,
+                                                       InDataTypePointerTuple,
+                                                       OutDataTypePointerTuple,
+                                                       ElementwiseOperation,
+                                                       UnaryOperation,
+                                                       Scale,
+                                                       MPerThread,
+                                                       InScalarPerVectorSeq,
+                                                       OutScalarPerVectorSeq>;
+
+    struct Argument : public BaseArgument
+    {
+        Argument(const std::array<index_t, NumDim> lengths,
+                 const std::array<std::array<index_t, NumDim>, NumInput> inStridesArray,
+                 const std::array<std::array<index_t, NumDim>, NumOutput> outStridesArray,
+                 const std::array<const void*, NumInput> in_dev_buffers,
+                 const std::array<void*, NumOutput> out_dev_buffers,
+                 ElementwiseOperation elementwise_op,
+                 UnaryOperation unary_op,
+                 Scale scale_op)
+
+            : lengths_(lengths),
+              inStridesArray_(inStridesArray),
+              outStridesArray_(outStridesArray),
+              elementwise_op_(elementwise_op),
+              unary_op_(unary_op),
+              scale_op_(scale_op),
+              blockSize_(256)
+        {
+            in_dev_buffers_ = generate_tuple(
+                [&](auto I) {
+                    using DataType = remove_cvref_t<decltype(InDataTypeTuple{}[I])>;
+                    return static_cast<const DataType*>(in_dev_buffers[I.value]);
+                },
+                Number<NumInput>{});
+
+            out_dev_buffers_ = generate_tuple(
+                [&](auto I) {
+                    using DataType = remove_cvref_t<decltype(OutDataTypeTuple{}[I])>;
+                    return static_cast<DataType*>(out_dev_buffers[I.value]);
+                },
+                Number<NumOutput>{});
+        }
+
+        InDataTypePointerTuple in_dev_buffers_;
+        OutDataTypePointerTuple out_dev_buffers_;
+
+        std::array<index_t, NumDim> lengths_;
+        std::array<std::array<index_t, NumDim>, NumInput> inStridesArray_;
+        std::array<std::array<index_t, NumDim>, NumOutput> outStridesArray_;
+
+        ElementwiseOperation elementwise_op_;
+        UnaryOperation unary_op_;
+        Scale scale_op_;
+        index_t blockSize_;
+    };
+
+    struct Invoker : public BaseInvoker
+    {
+        float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
+        {
+            index_t gridSize = getAvailableComputeUnitCount(stream_config);
+
+            auto in_grid_1d_desc_tuple = generate_tuple(
+                [&](auto I) {
+                    return MakeDescriptor_M(
+                        arg.lengths_, arg.inStridesArray_[I.value], gridSize, arg.blockSize_);
+                },
+                Number<NumInput>{});
+
+            auto out_grid_1d_desc_tuple = generate_tuple(
+                [&](auto I) {
+                    return MakeDescriptor_M(
+                        arg.lengths_, arg.outStridesArray_[I.value], gridSize, arg.blockSize_);
+                },
+                Number<NumOutput>{});
+
+            const auto kernel = kernel_elementwise_1d<GridwiseElementwise,
+                                                      InGrid1dDescTuple,
+                                                      OutGrid1dDescTuple,
+                                                      InDataTypePointerTuple,
+                                                      OutDataTypePointerTuple,
+                                                      ElementwiseOperation,
+                                                      UnaryOperation,
+                                                      Scale>;
+
+            float elapsed_time = launch_and_time_kernel(stream_config,
+                                                        kernel,
+                                                        dim3(gridSize),
+                                                        dim3(arg.blockSize_),
+                                                        0,
+                                                        in_grid_1d_desc_tuple,
+                                                        out_grid_1d_desc_tuple,
+                                                        arg.in_dev_buffers_,
+                                                        arg.out_dev_buffers_,
+                                                        arg.elementwise_op_,
+                                                        arg.unary_op_,
+                                                        arg.scale_op_);
+            return elapsed_time;
+        }
+
+        // polymorphic
+        float Run(const BaseArgument* p_arg,
+                  const StreamConfig& stream_config = StreamConfig{}) override
+        {
+            return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
+        }
+    };
+
+    static bool IsSupportedArgument(const Argument& arg)
+    {
+        if(arg.lengths_.back() % MPerThread != 0)
+            return false;
+
+        auto IsScalarPerVectorValid = [&](const std::array<index_t, NumDim>& lengths,
+                                          const std::array<index_t, NumDim>& strides,
+                                          index_t scalarPerVector) {
+            if(strides.back() == 1 && lengths.back() % scalarPerVector == 0)
+                return true;
+
+            if(strides.back() != 1 && scalarPerVector == 1)
+                return true;
+
+            return false;
+        };
+
+        bool valid = true;
+        static_for<0, NumInput, 1>{}([&](auto I) {
+            if(!IsScalarPerVectorValid(
+                   arg.lengths_, arg.inStridesArray_[I.value], InScalarPerVectorSeq::At(I)))
+                valid = false;
+        });
+
+        static_for<0, NumOutput, 1>{}([&](auto I) {
+            if(!IsScalarPerVectorValid(
+                   arg.lengths_, arg.outStridesArray_[I.value], OutScalarPerVectorSeq::At(I)))
+                valid = false;
+        });
+
+        return valid;
+    };
+
+    bool IsSupportedArgument(const BaseArgument* p_arg) override
+    {
+        return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
+    }
+
+    static auto
+    MakeArgument(const std::array<index_t, NumDim> lengths,
+                 const std::array<std::array<index_t, NumDim>, NumInput> inStridesArray,
+                 const std::array<std::array<index_t, NumDim>, NumOutput> outStridesArray,
+                 const std::array<const void*, NumInput> in_dev_buffers,
+                 const std::array<void*, NumOutput> out_dev_buffers,
+                 ElementwiseOperation elementwise_op,
+                 UnaryOperation unary_op,
+                 Scale scale_op)
+    {
+        return Argument{lengths,
+                        inStridesArray,
+                        outStridesArray,
+                        in_dev_buffers,
+                        out_dev_buffers,
+                        elementwise_op,
+                        unary_op,
+                        scale_op};
+    }
+
+    std::unique_ptr<BaseArgument>
+    MakeArgumentPointer(const std::array<index_t, NumDim> lengths,
+                        const std::array<std::array<index_t, NumDim>, NumInput> inStridesArray,
+                        const std::array<std::array<index_t, NumDim>, NumOutput> outStridesArray,
+                        const std::array<const void*, NumInput> in_dev_buffers,
+                        const std::array<void*, NumOutput> out_dev_buffers,
+                        ElementwiseOperation elementwise_op,
+                        UnaryOperation unary_op,
+                        Scale scale_op) override
+    {
+        return std::make_unique<Argument>(lengths,
+                                          inStridesArray,
+                                          outStridesArray,
+                                          in_dev_buffers,
+                                          out_dev_buffers,
+                                          elementwise_op,
+                                          unary_op,
+                                          scale_op);
+    }
+
+    static auto MakeInvoker() { return Invoker{}; }
+    std::unique_ptr<BaseInvoker> MakeInvokerPointer() override
+    {
+        return std::make_unique<Invoker>();
+    };
+
+    std::string GetTypeString() const override
+    {
+        auto str = std::stringstream();
+
+        // clang-format off
+        str << "DeviceElementwiseNormalizationImpl<";
+        str << NumDim << ", ";
+        str << MPerThread << ">";
+        // clang-format on
+
+        return str.str();
+    }
+}; // namespace device
+
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

include/ck/tensor_operation/gpu/device/impl/device_gemm_bias_add_reduce_xdl_cshuffle.hpp

@@ -683,6 +683,11 @@ struct DeviceGemmBiasAddReduce_Xdl_CShuffle : public DeviceGemmReduce<1, ReduceO
 
     static bool IsSupportedArgument(const Argument& arg)
     {
+        if(!ck::is_xdl_supported())
+        {
+            return false;
+        }
+
         return GridwiseGemm::CheckValidity(arg.a_grid_desc_ak0_m_ak1_,
                                            arg.b_grid_desc_bk0_n_bk1_,
                                            arg.c_grid_desc_m_n_,

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

@@ -273,6 +273,9 @@ struct DeviceGemmDl : public DeviceGemm<ALayout,
               block_2_ctile_map_{},
               M01_{M01},
               N01_{N01},
+              M_raw_{M},
+              N_raw_{N},
+              K_raw_{K},
               a_element_op_{a_element_op},
               b_element_op_{b_element_op},
               c_element_op_{c_element_op}
@@ -314,6 +317,10 @@ struct DeviceGemmDl : public DeviceGemm<ALayout,
         index_t M01_;
         index_t N01_;
 
+        index_t M_raw_;
+        index_t N_raw_;
+        index_t K_raw_;
+
         // TODO: unused since gridwise_gemm_dl_v1r3 does NOT support prologue for the time being.
         AElementwiseOperation a_element_op_;
         BElementwiseOperation b_element_op_;
@@ -485,17 +492,57 @@ struct DeviceGemmDl : public DeviceGemm<ALayout,
 
     static bool IsSupportedArgument(const Argument& arg)
     {
-        if(ck::get_device_name() == "gfx906" || ck::get_device_name() == "gfx1030" ||
-           ck::get_device_name() == "gfx1100" || ck::get_device_name() == "gfx1101" ||
-           ck::get_device_name() == "gfx1102")
+        // Make sure that the M, N, K dimensions before padding are divisible by respective vector
+        // lengths.
+        if constexpr(is_same<tensor_layout::gemm::RowMajor, ALayout>::value)
         {
-            return GridwiseGemm::CheckValidity(
-                arg.a_grid_desc_k0_m_k1_, arg.b_grid_desc_k0_n_k1_, arg.c_grid_desc_m_n_);
+            constexpr auto A_K_vec_length =
+                ABlockTransferSrcVectorTensorLengths_K0_M0_M1_K1::At(I0) *
+                ABlockTransferSrcVectorTensorLengths_K0_M0_M1_K1::At(I3);
+            if(arg.K_raw_ % A_K_vec_length != 0)
+            {
+                return false;
+            }
+        }
+        else
+        {
+            constexpr auto A_M_vec_lenght =
+                ABlockTransferSrcVectorTensorLengths_K0_M0_M1_K1::At(I1) *
+                ABlockTransferSrcVectorTensorLengths_K0_M0_M1_K1::At(I2);
+            if(arg.M_raw_ % A_M_vec_lenght != 0)
+            {
+                return false;
+            }
+        }
+
+        if constexpr(is_same<tensor_layout::gemm::RowMajor, BLayout>::value)
+        {
+            constexpr auto B_N_vec_lenght =
+                BBlockTransferSrcVectorTensorLengths_K0_N0_N1_K1::At(I1) *
+                BBlockTransferSrcVectorTensorLengths_K0_N0_N1_K1::At(I2);
+            if(arg.N_raw_ % B_N_vec_lenght != 0)
+            {
+                return false;
+            }
         }
         else
         {
-            return false;
+            constexpr auto B_K_vec_length =
+                BBlockTransferSrcVectorTensorLengths_K0_N0_N1_K1::At(I0) *
+                BBlockTransferSrcVectorTensorLengths_K0_N0_N1_K1::At(I3);
+            if(arg.K_raw_ % B_K_vec_length != 0)
+            {
+                return false;
+            }
+        }
+
+        if(ck::get_device_name() == "gfx906" || ck::is_navi2_supported() ||
+           ck::is_navi3_supported())
+        {
+            return GridwiseGemm::CheckValidity(
+                arg.a_grid_desc_k0_m_k1_, arg.b_grid_desc_k0_n_k1_, arg.c_grid_desc_m_n_);
         }
+        return false;
     }
 
     // polymorphic
@@ -572,7 +619,7 @@ struct DeviceGemmDl : public DeviceGemm<ALayout,
     }
 
     // polymorphic
-    std::string GetTypeString() const override
+    virtual std::string GetTypeString() const override
     {
         auto str = std::stringstream();
 

include/ck/tensor_operation/gpu/device/impl/device_gemm_dpp.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include <sstream>
+
+#include "ck/utility/common_header.hpp"
+#include "ck/tensor_description/tensor_descriptor.hpp"
+#include "ck/tensor_description/tensor_descriptor_helper.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_gemm.hpp"
+#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
+#include "ck/tensor_operation/gpu/grid/gridwise_gemm_dpp.hpp"
+#include "ck/host_utility/device_prop.hpp"
+#include "ck/host_utility/kernel_launch.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+
+template <typename ADataType,
+          typename BDataType,
+          typename CDataType,
+          typename AccDataType,
+          typename ALayout,
+          typename BLayout,
+          typename CLayout,
+          typename AElementwiseOperation,
+          typename BElementwiseOperation,
+          typename CElementwiseOperation,
+          GemmSpecialization GemmSpec,
+          ck::index_t BlockSize,
+          ck::index_t MPerBlock,
+          ck::index_t NPerBlock,
+          ck::index_t KPerBlock,
+          ck::index_t AK1,
+          ck::index_t BK1,
+          ck::index_t MPerDpp,
+          ck::index_t NPerDpp,
+          ck::index_t MDppPerWave,
+          ck::index_t NDppPerWave,
+          typename ABlockTransferThreadClusterLengths_K0_M_K1,
+          typename ABlockTransferThreadClusterArrangeOrder,
+          typename ABlockTransferSrcAccessOrder,
+          ck::index_t ABlockTransferSrcVectorDim,
+          ck::index_t ABlockTransferSrcScalarPerVector,
+          ck::index_t ABlockTransferDstScalarPerVector_K1,
+          bool ABlockLdsAddExtraM,
+          typename BBlockTransferThreadClusterLengths_K0_N_K1,
+          typename BBlockTransferThreadClusterArrangeOrder,
+          typename BBlockTransferSrcAccessOrder,
+          ck::index_t BBlockTransferSrcVectorDim,
+          ck::index_t BBlockTransferSrcScalarPerVector,
+          ck::index_t BBlockTransferDstScalarPerVector_K1,
+          bool BBlockLdsAddExtraN,
+          ck::index_t CThreadTransferSrcDstVectorDim,
+          ck::index_t CThreadTransferDstScalarPerVector,
+          ck::index_t NumPrefetch         = 1,
+          ck::PipelineVersion PipelineVer = ck::PipelineVersion::v1>
+struct DeviceGemmDpp : public DeviceGemm<ALayout,
+                                         BLayout,
+                                         CLayout,
+                                         ADataType,
+                                         BDataType,
+                                         CDataType,
+                                         AElementwiseOperation,
+                                         BElementwiseOperation,
+                                         CElementwiseOperation>
+{
+    using GridwiseGemm = GridwiseGemm_ak0mak1_bk0nbk1_mn_dpp<
+        BlockSize,
+        ADataType,
+        AccDataType,
+        CDataType,
+        InMemoryDataOperationEnum::Set,
+        ALayout,
+        BLayout,
+        CLayout,
+        AElementwiseOperation,
+        BElementwiseOperation,
+        CElementwiseOperation,
+        GemmSpec,
+        MPerBlock,
+        NPerBlock,
+        KPerBlock,
+        MPerDpp,
+        NPerDpp,
+        AK1,
+        BK1,
+        MDppPerWave,
+        NDppPerWave,
+        ABlockTransferThreadClusterLengths_K0_M_K1,
+        ABlockTransferThreadClusterArrangeOrder,
+        ABlockTransferSrcAccessOrder,
+        ABlockTransferSrcVectorDim,
+        ABlockTransferSrcScalarPerVector,
+        ABlockTransferDstScalarPerVector_K1,
+        false, // AThreadTransferSrcResetCoordinateAfterRun,
+        ABlockLdsAddExtraM,
+        BBlockTransferThreadClusterLengths_K0_N_K1,
+        BBlockTransferThreadClusterArrangeOrder,
+        BBlockTransferSrcAccessOrder,
+        BBlockTransferSrcVectorDim,
+        BBlockTransferSrcScalarPerVector,
+        BBlockTransferDstScalarPerVector_K1,
+        false, // BThreadTransferSrcResetCoordinateAfterRun,
+        BBlockLdsAddExtraN,
+        Sequence<0, 2, 4, 1, 3, 5>, // CThreadTransferSrcDstAccessOrder,
+        CThreadTransferSrcDstVectorDim,
+        CThreadTransferDstScalarPerVector,
+        NumPrefetch,
+        PipelineVer>;
+
+    using Argument = typename GridwiseGemm::Argument;
+
+    // Invoker
+    struct Invoker : public BaseInvoker
+    {
+        float Run(const Argument& karg, const StreamConfig& stream_config = StreamConfig{})
+        {
+            if(stream_config.log_level_ > 0)
+            {
+                karg.Print();
+            }
+
+            if(!GridwiseGemm::CheckValidity(karg))
+            {
+                throw std::runtime_error(
+                    "wrong! GridwiseGemm_k0mk1_k0nk1_mn_dpp has invalid setting");
+            }
+
+            const auto [gdx, gdy, gdz] = GridwiseGemm::CalculateGridSize(karg.M, karg.N);
+
+            float ave_time = 0;
+
+            if(GridwiseGemm::CalculateHasMainKBlockLoop(karg.K))
+            {
+                const auto kernel = kernel_gemm_dpp<GridwiseGemm, true>;
+
+                ave_time = launch_and_time_kernel(
+                    stream_config, kernel, dim3(gdx, gdy, gdz), dim3(BlockSize), 0, karg);
+            }
+            else
+            {
+                const auto kernel = kernel_gemm_dpp<GridwiseGemm, false>;
+
+                ave_time = launch_and_time_kernel(
+                    stream_config, kernel, dim3(gdx, gdy, gdz), dim3(BlockSize), 0, karg);
+            }
+
+            return ave_time;
+        }
+
+        // polymorphic
+        float Run(const BaseArgument* p_arg,
+                  const StreamConfig& stream_config = StreamConfig{}) override
+        {
+            return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
+        }
+    };
+
+    static constexpr bool IsValidCompilationParameter()
+    {
+        // TODO: properly implement this check
+        return true;
+    }
+
+    static bool IsSupportedArgument(const Argument& karg)
+    {
+        if(ck::is_navi2_supported() || ck::is_navi3_supported())
+        {
+            return GridwiseGemm::CheckValidity(karg);
+        }
+        return false;
+    }
+
+    // polymorphic
+    bool IsSupportedArgument(const BaseArgument* p_arg) override
+    {
+        return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
+    }
+
+    static auto MakeArgument(const ADataType* p_a,
+                             const BDataType* p_b,
+                             CDataType* p_c,
+                             index_t M,
+                             index_t N,
+                             index_t K,
+                             index_t StrideA,
+                             index_t StrideB,
+                             index_t StrideC,
+                             AElementwiseOperation,
+                             BElementwiseOperation,
+                             CElementwiseOperation)
+    {
+        return Argument{p_a, p_b, p_c, M, N, K, StrideA, StrideB, StrideC};
+    }
+
+    static auto MakeInvoker() { return Invoker{}; }
+
+    // polymorphic
+    std::unique_ptr<BaseArgument> MakeArgumentPointer(const void* p_a,
+                                                      const void* p_b,
+                                                      void* p_c,
+                                                      index_t M,
+                                                      index_t N,
+                                                      index_t K,
+                                                      index_t StrideA,
+                                                      index_t StrideB,
+                                                      index_t StrideC,
+                                                      AElementwiseOperation,
+                                                      BElementwiseOperation,
+                                                      CElementwiseOperation) override
+    {
+        return std::make_unique<Argument>(static_cast<const ADataType*>(p_a),
+                                          static_cast<const BDataType*>(p_b),
+                                          static_cast<CDataType*>(p_c),
+                                          M,
+                                          N,
+                                          K,
+                                          StrideA,
+                                          StrideB,
+                                          StrideC);
+    }
+
+    // polymorphic
+    std::unique_ptr<BaseInvoker> MakeInvokerPointer() override
+    {
+        return std::make_unique<Invoker>(Invoker{});
+    }
+
+    // polymorphic
+    std::string GetTypeString() const override
+    {
+        auto str = std::stringstream();
+
+        std::map<PipelineVersion, std::string> PipelineVersionToString{{PipelineVersion::v1, "v1"},
+                                                                       {PipelineVersion::v2, "v2"}};
+
+        // clang-format off
+        str << "DeviceGemmDpp"
+            << "<"
+            << BlockSize << ", "
+            << MPerBlock << ", "
+            << NPerBlock << ", "
+            << KPerBlock << ", "
+            << AK1 << ", "
+            << BK1 << ", "
+            << MPerDpp << ", "
+            << NPerDpp << ", "
+            << MDppPerWave << ", "
+            << MDppPerWave << ", "
+            << ABlockTransferSrcScalarPerVector << ", "
+            << ABlockTransferDstScalarPerVector_K1 << ", "
+            << BBlockTransferSrcScalarPerVector << ", "
+            << BBlockTransferDstScalarPerVector_K1
+            << ">"
+            << " NumPrefetch: "
+            << NumPrefetch << ", "
+            << "PipelineVersion: "
+            << PipelineVersionToString[PipelineVer];
+        // clang-format on
+
+        return str.str();
+    }
+};
+
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

include/ck/tensor_operation/gpu/device/impl/device_gemm_multiple_abd_xdl_cshuffle.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include <iostream>
+#include <sstream>
+
+#include "ck/utility/common_header.hpp"
+#include "ck/tensor_description/tensor_descriptor.hpp"
+#include "ck/tensor_description/tensor_descriptor_helper.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_gemm_multiple_abd.hpp"
+#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
+#include "ck/tensor_operation/gpu/device/matrix_padder.hpp"
+#include "ck/tensor_operation/gpu/grid/gridwise_gemm_multiple_abd_xdl_cshuffle.hpp"
+#include "ck/host_utility/device_prop.hpp"
+#include "ck/host_utility/kernel_launch.hpp"
+
+namespace ck {
+
+template <typename GridwiseGemm,
+          typename AsPointer,
+          typename BsPointer,
+          typename DsPointer,
+          typename EDataType,
+          typename AElementwiseOperation,
+          typename BElementwiseOperation,
+          typename CDEElementwiseOperation,
+          typename AsGridDesc_AK0_M_AK1,
+          typename BsGridDesc_BK0_N_BK1,
+          typename DsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
+          typename EGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock,
+          typename Block2ETileMap,
+          bool HasMainKBlockLoop>
+__global__ void
+#if CK_USE_LAUNCH_BOUNDS
+    __launch_bounds__(CK_MAX_THREAD_PER_BLOCK, CK_MIN_BLOCK_PER_CU)
+#endif
+        kernel_gemm_multiple_abd_xdl_cshuffle(
+            AsPointer p_as_grid,
+            BsPointer p_bs_grid,
+            DsPointer p_ds_grid,
+            EDataType* __restrict__ p_e_grid,
+            const AElementwiseOperation a_element_op,
+            const BElementwiseOperation b_element_op,
+            const CDEElementwiseOperation cde_element_op,
+            const AsGridDesc_AK0_M_AK1 as_grid_desc_ak0_m_ak1,
+            const BsGridDesc_BK0_N_BK1 bs_grid_desc_bk0_n_bk1,
+            const DsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
+                ds_grid_desc_mblock_mperblock_nblock_nperblock,
+            const EGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock
+                e_grid_desc_mblock_mperblock_nblock_nperblock,
+            const Block2ETileMap block_2_etile_map)
+{
+#if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__) || \
+    defined(__gfx94__))
+    __shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()];
+
+    GridwiseGemm::template Run<HasMainKBlockLoop>(p_as_grid,
+                                                  p_bs_grid,
+                                                  p_ds_grid,
+                                                  p_e_grid,
+                                                  p_shared,
+                                                  a_element_op,
+                                                  b_element_op,
+                                                  cde_element_op,
+                                                  as_grid_desc_ak0_m_ak1,
+                                                  bs_grid_desc_bk0_n_bk1,
+                                                  ds_grid_desc_mblock_mperblock_nblock_nperblock,
+                                                  e_grid_desc_mblock_mperblock_nblock_nperblock,
+                                                  block_2_etile_map);
+#else
+    ignore = p_as_grid;
+    ignore = p_bs_grid;
+    ignore = p_ds_grid;
+    ignore = p_e_grid;
+    ignore = a_element_op;
+    ignore = b_element_op;
+    ignore = cde_element_op;
+    ignore = as_grid_desc_ak0_m_ak1;
+    ignore = bs_grid_desc_bk0_n_bk1;
+    ignore = ds_grid_desc_mblock_mperblock_nblock_nperblock;
+    ignore = e_grid_desc_mblock_mperblock_nblock_nperblock;
+    ignore = block_2_etile_map;
+#endif
+}
+
+} // namespace ck
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+
+// GEMM:
+//   input : A[M, K]
+//   input : B[N, K]
+//   input : D0[M, N], D1[M, N], ...
+//   output : E[M, N]
+//   C = a_op(A) * b_op(B)
+//   E = cde_op(C, D0, D1, ...)
+// Assume:
+//   D0, D1, ... and E have the same layout
+template <typename AsLayout,
+          typename BsLayout,
+          typename DsLayout,
+          typename ELayout,
+          typename AsDataType,
+          typename BsDataType,
+          typename AccDataType,
+          typename CShuffleDataType,
+          typename DsDataType,
+          typename EDataType,
+          typename AElementwiseOperation,
+          typename BElementwiseOperation,
+          typename CDEElementwiseOperation,
+          GemmSpecialization GemmSpec,
+          index_t NumGemmKPrefetchStage,
+          index_t BlockSize,
+          index_t MPerBlock,
+          index_t NPerBlock,
+          index_t KPerBlock,
+          index_t AK1,
+          index_t BK1,
+          index_t MPerXDL,
+          index_t NPerXDL,
+          index_t MXdlPerWave,
+          index_t NXdlPerWave,
+          typename ABlockTransferThreadClusterLengths_AK0_M_AK1,
+          typename ABlockTransferThreadClusterArrangeOrder,
+          typename ABlockTransferSrcAccessOrder,
+          index_t ABlockTransferSrcVectorDim,
+          index_t ABlockTransferSrcScalarPerVector,
+          index_t ABlockTransferDstScalarPerVector_AK1,
+          index_t ABlockLdsExtraM,
+          typename BBlockTransferThreadClusterLengths_BK0_N_BK1,
+          typename BBlockTransferThreadClusterArrangeOrder,
+          typename BBlockTransferSrcAccessOrder,
+          index_t BBlockTransferSrcVectorDim,
+          index_t BBlockTransferSrcScalarPerVector,
+          index_t BBlockTransferDstScalarPerVector_BK1,
+          index_t BBlockLdsExtraN,
+          index_t CShuffleMXdlPerWavePerShuffle,
+          index_t CShuffleNXdlPerWavePerShuffle,
+          typename CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
+          index_t CDEBlockTransferScalarPerVector_NPerBlock,
+          LoopScheduler LoopSched     = make_default_loop_scheduler(),
+          PipelineVersion PipelineVer = PipelineVersion::v1>
+struct DeviceGemmMultipleABD_Xdl_CShuffle : public DeviceGemmMultipleABD<AsLayout,
+                                                                         BsLayout,
+                                                                         DsLayout,
+                                                                         ELayout,
+                                                                         AsDataType,
+                                                                         BsDataType,
+                                                                         DsDataType,
+                                                                         EDataType,
+                                                                         AElementwiseOperation,
+                                                                         BElementwiseOperation,
+                                                                         CDEElementwiseOperation>
+{
+    using DeviceOp = DeviceGemmMultipleABD_Xdl_CShuffle;
+
+    static constexpr index_t NumATensor = AsDataType::Size();
+    static constexpr index_t NumBTensor = BsDataType::Size();
+    static constexpr index_t NumDTensor = DsDataType::Size();
+
+    static constexpr auto I0 = Number<0>{};
+    static constexpr auto I1 = Number<1>{};
+    static constexpr auto I2 = Number<2>{};
+    static constexpr auto I3 = Number<3>{};
+
+#if 0
+    static constexpr auto matrix_padder =
+        MatrixPadder<GemmSpec, index_t, index_t, index_t>{MPerBlock, NPerBlock, KPerBlock};
+
+    static auto MakeAGridDescriptor_M_K(index_t MRaw, index_t KRaw, index_t StrideAs)
+    {
+        const auto a_grid_desc_mraw_kraw = [&]() {
+            if constexpr(is_same_v<tensor_layout::gemm::RowMajor, AsLayout>)
+            {
+                return make_naive_tensor_descriptor(make_tuple(MRaw, KRaw),
+                                                    make_tuple(StrideAs, I1));
+            }
+            else if constexpr(is_same_v<tensor_layout::gemm::ColumnMajor, AsLayout>)
+            {
+                return make_naive_tensor_descriptor(make_tuple(MRaw, KRaw),
+                                                    make_tuple(I1, StrideAs));
+            }
+        }();
+
+        return matrix_padder.PadADescriptor_M_K(a_grid_desc_mraw_kraw);
+    }
+
+    static auto MakeBGridDescriptor_N_K(index_t KRaw, index_t NRaw, index_t StrideBs)
+    {
+        const auto b_grid_desc_nraw_kraw = [&]() {
+            if constexpr(is_same<tensor_layout::gemm::RowMajor, BsLayout>::value)
+            {
+                return make_naive_tensor_descriptor(make_tuple(NRaw, KRaw),
+                                                    make_tuple(I1, StrideBs));
+            }
+            else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, BsLayout>::value)
+            {
+                return make_naive_tensor_descriptor(make_tuple(NRaw, KRaw),
+                                                    make_tuple(StrideBs, I1));
+            }
+        }();
+
+        return matrix_padder.PadBDescriptor_N_K(b_grid_desc_nraw_kraw);
+    }
+
+    template <typename ELay>
+    static auto MakeEGridDescriptor_M_N(index_t MRaw, index_t NRaw, index_t StrideE)
+    {
+        const auto e_grid_desc_mraw_nraw = [&]() {
+            if constexpr(is_same<tensor_layout::gemm::RowMajor, ELay>::value)
+            {
+                return make_naive_tensor_descriptor(make_tuple(MRaw, NRaw),
+                                                    make_tuple(StrideE, I1));
+            }
+            else if constexpr(is_same<tensor_layout::gemm::ColumnMajor, ELay>::value)
+            {
+                return make_naive_tensor_descriptor(make_tuple(MRaw, NRaw),
+                                                    make_tuple(I1, StrideE));
+            }
+        }();
+
+        return matrix_padder.PadCDescriptor_M_N(e_grid_desc_mraw_nraw);
+    }
+
+    static auto MakeDsGridDescriptor_M_N(const std::array<index_t, NumDTensor>& MRaws,
+                                         const std::array<index_t, NumDTensor>& NRaws,
+                                         const std::array<index_t, NumDTensor>& DsStride)
+    {
+        return generate_tuple(
+            [&](auto i) {
+                using DLayout = remove_cvref_t<tuple_element_t<i.value, DsLayout>>;
+
+                return DeviceOp::MakeEGridDescriptor_M_N<DLayout>(MRaws[i], NRaws[i], DsStride[i]);
+            },
+            Number<NumDTensor>{});
+    }
+#endif
+    using ComputeDataType = EDataType;
+
+    // GridwiseGemm
+    using GridwiseGemm = GridwiseGemmMultipleABD_xdl_cshuffle<
+        AsDataType,
+        BsDataType,
+        ComputeDataType,
+        AccDataType,
+        CShuffleDataType,
+        DsDataType,
+        EDataType,
+        AElementwiseOperation,
+        BElementwiseOperation,
+        CDEElementwiseOperation,
+        InMemoryDataOperationEnum::Set,
+        NumGemmKPrefetchStage,
+        BlockSize,
+        MPerBlock,
+        NPerBlock,
+        KPerBlock,
+        AK1,
+        BK1,
+        MPerXDL,
+        NPerXDL,
+        MXdlPerWave,
+        NXdlPerWave,
+        ABlockTransferThreadClusterLengths_AK0_M_AK1,
+        ABlockTransferThreadClusterArrangeOrder,
+        ABlockTransferSrcAccessOrder,
+        ABlockTransferSrcVectorDim,
+        ABlockTransferSrcScalarPerVector,
+        ABlockTransferDstScalarPerVector_AK1,
+        false,
+        ABlockLdsExtraM,
+        BBlockTransferThreadClusterLengths_BK0_N_BK1,
+        BBlockTransferThreadClusterArrangeOrder,
+        BBlockTransferSrcAccessOrder,
+        BBlockTransferSrcVectorDim,
+        BBlockTransferSrcScalarPerVector,
+        BBlockTransferDstScalarPerVector_BK1,
+        false,
+        BBlockLdsExtraN,
+        CShuffleMXdlPerWavePerShuffle,
+        CShuffleNXdlPerWavePerShuffle,
+        CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
+        CDEBlockTransferScalarPerVector_NPerBlock,
+        LoopSched,
+        PipelineVer>;
+
+    // desc for problem definition
+    using AsGridDesc_M_K =
+        remove_cvref_t<decltype(GridwiseGemm::template MakeAsGridDescriptor_M_K<AsLayout, GemmSpec>(
+            {}, {}, {}))>;
+    using BsGridDesc_N_K =
+        remove_cvref_t<decltype(GridwiseGemm::template MakeBsGridDescriptor_N_K<BsLayout, GemmSpec>(
+            {}, {}, {}))>;
+    using DsGridDesc_M_N =
+        remove_cvref_t<decltype(GridwiseGemm::template MakeDsGridDescriptor_M_N<DsLayout, GemmSpec>(
+            {}, {}, {}))>;
+    using EGridDesc_M_N =
+        decltype(GridwiseGemm::template MakeEGridDescriptor_M_N<ELayout, GemmSpec>(1, 1, 1));
+
+    // desc for blockwise copy
+    using AsGridDesc_AK0_M_AK1 =
+        remove_cvref_t<decltype(GridwiseGemm::MakeDefaultAsGridDescriptor_AK0_M_AK1(
+            AsGridDesc_M_K{}))>;
+    using BsGridDesc_BK0_N_BK1 =
+        remove_cvref_t<decltype(GridwiseGemm::MakeDefaultBsGridDescriptor_BK0_N_BK1(
+            BsGridDesc_N_K{}))>;
+    using DsGridDesc_MBlock_MPerBlock_NBlock_NPerBlock = remove_cvref_t<
+        decltype(GridwiseGemm::MakeDsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
+            DsGridDesc_M_N{}))>;
+    using EGridDesc_MBlock_MPerBlock_NBlock_NPerBlock =
+        remove_cvref_t<decltype(GridwiseGemm::MakeEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
+            EGridDesc_M_N{}))>;
+
+    // block-to-e-tile map
+    using Block2ETileMap =
+        remove_cvref_t<decltype(GridwiseGemm::MakeDefaultBlock2ETileMap(EGridDesc_M_N{}))>;
+
+    // Argument
+    struct Argument : public BaseArgument
+    {
+        Argument(std::array<const void*, NumATensor> p_as_grid,
+                 std::array<const void*, NumBTensor> p_bs_grid,
+                 std::array<const void*, NumDTensor> p_ds_grid,
+                 void* p_e_grid,
+                 index_t MRaw,
+                 index_t NRaw,
+                 index_t KRaw,
+                 std::array<index_t, NumATensor> StrideAs,
+                 std::array<index_t, NumBTensor> StrideBs,
+                 std::array<index_t, NumDTensor> StrideDs,
+                 index_t StrideE,
+                 AElementwiseOperation a_element_op,
+                 BElementwiseOperation b_element_op,
+                 CDEElementwiseOperation cde_element_op)
+            : p_as_grid_{},
+              p_bs_grid_{},
+              p_ds_grid_{},
+              p_e_grid_{static_cast<EDataType*>(p_e_grid)},
+              as_grid_desc_m_k_{},
+              bs_grid_desc_n_k_{},
+              ds_grid_desc_m_n_{},
+              e_grid_desc_m_n_{GridwiseGemm::template MakeEGridDescriptor_M_N<ELayout, GemmSpec>(
+                  MRaw, NRaw, StrideE)},
+              as_grid_desc_ak0_m_ak1_{},
+              bs_grid_desc_bk0_n_bk1_{},
+              ds_grid_desc_mblock_mperblock_nblock_nperblock_{},
+              e_grid_desc_mblock_mperblock_nblock_nperblock_{},
+              block_2_etile_map_{GridwiseGemm::MakeDefaultBlock2ETileMap(e_grid_desc_m_n_)},
+              a_element_op_{a_element_op},
+              b_element_op_{b_element_op},
+              cde_element_op_{cde_element_op},
+              MRaw_{MRaw},
+              NRaw_{NRaw},
+              KRaw_{KRaw}
+        {
+            // populate pointer, desc for As
+            static_for<0, NumATensor, 1>{}([&](auto i) {
+                using ALayout   = remove_cvref_t<tuple_element_t<i.value, AsLayout>>;
+                using ADataType = remove_cvref_t<tuple_element_t<i.value, AsDataType>>;
+
+                // A pointer
+                p_as_grid_(i) = static_cast<const ADataType*>(p_as_grid[i]);
+
+                // A desc
+                as_grid_desc_m_k_(i) =
+                    GridwiseGemm::template MakeAGridDescriptor_M_K<ALayout, GemmSpec>(
+                        MRaw, KRaw, StrideAs[i]);
+            });
+
+            // populate pointer, desc for Bs
+            static_for<0, NumBTensor, 1>{}([&](auto i) {
+                using BLayout   = remove_cvref_t<tuple_element_t<i.value, BsLayout>>;
+                using BDataType = remove_cvref_t<tuple_element_t<i.value, BsDataType>>;
+
+                // B pointer
+                p_bs_grid_(i) = static_cast<const BDataType*>(p_bs_grid[i]);
+
+                // B desc
+                bs_grid_desc_n_k_(i) =
+                    GridwiseGemm::template MakeBGridDescriptor_N_K<BLayout, GemmSpec>(
+                        KRaw, NRaw, StrideBs[i]);
+            });
+
+            // populate pointer, desc for Ds
+            static_for<0, NumDTensor, 1>{}([&](auto i) {
+                using DLayout   = remove_cvref_t<tuple_element_t<i.value, DsLayout>>;
+                using DDataType = remove_cvref_t<tuple_element_t<i.value, DsDataType>>;
+
+                // D pointer
+                p_ds_grid_(i) = static_cast<const DDataType*>(p_ds_grid[i]);
+
+                // D desc
+                ds_grid_desc_m_n_(i) =
+                    GridwiseGemm::template MakeEGridDescriptor_M_N<DLayout, GemmSpec>(
+                        MRaw, NRaw, StrideDs[i]);
+            });
+
+            // populate desc for Ds/E
+            if(GridwiseGemm::CheckValidity(as_grid_desc_m_k_,
+                                           bs_grid_desc_n_k_,
+                                           ds_grid_desc_m_n_,
+                                           e_grid_desc_m_n_,
+                                           block_2_etile_map_))
+            {
+                as_grid_desc_ak0_m_ak1_ =
+                    GridwiseGemm::MakeDefaultAsGridDescriptor_AK0_M_AK1(as_grid_desc_m_k_);
+
+                bs_grid_desc_bk0_n_bk1_ =
+                    GridwiseGemm::MakeDefaultBsGridDescriptor_BK0_N_BK1(bs_grid_desc_n_k_);
+
+                ds_grid_desc_mblock_mperblock_nblock_nperblock_ =
+                    GridwiseGemm::MakeDsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
+                        ds_grid_desc_m_n_);
+
+                e_grid_desc_mblock_mperblock_nblock_nperblock_ =
+                    GridwiseGemm::MakeEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
+                        e_grid_desc_m_n_);
+            }
+        }
+
+        void Print() const
+        {
+            // std::cout << "A[M, K]: " << as_grid_desc_m_k_ << std::endl;
+            // std::cout << "B[N, K]: " << bs_grid_desc_n_k_ << std::endl;
+            // static_for<0, NumDTensor, 1>{}(
+            //[&](auto i) { std::cout << "Ds[M, N]: " << ds_grid_desc_m_n_[i] << std::endl; });
+            // std::cout << "E[M, N]: " << e_grid_desc_m_n_ << std::endl;
+        }
+
+        //  private:
+        // pointers
+        typename GridwiseGemm::AsGridPointer p_as_grid_;
+        typename GridwiseGemm::BsGridPointer p_bs_grid_;
+        typename GridwiseGemm::DsGridPointer p_ds_grid_;
+        EDataType* p_e_grid_;
+
+        // tensor descriptors for problem definiton
+        AsGridDesc_M_K as_grid_desc_m_k_;
+        BsGridDesc_N_K bs_grid_desc_n_k_;
+        DsGridDesc_M_N ds_grid_desc_m_n_;
+        EGridDesc_M_N e_grid_desc_m_n_;
+
+        // tensor descriptors for block/thread-wise copy
+        AsGridDesc_AK0_M_AK1 as_grid_desc_ak0_m_ak1_;
+        BsGridDesc_BK0_N_BK1 bs_grid_desc_bk0_n_bk1_;
+        DsGridDesc_MBlock_MPerBlock_NBlock_NPerBlock
+            ds_grid_desc_mblock_mperblock_nblock_nperblock_;
+        EGridDesc_MBlock_MPerBlock_NBlock_NPerBlock e_grid_desc_mblock_mperblock_nblock_nperblock_;
+
+        // block-to-e-tile map
+        Block2ETileMap block_2_etile_map_;
+
+        // element-wise op
+        AElementwiseOperation a_element_op_;
+        BElementwiseOperation b_element_op_;
+        CDEElementwiseOperation cde_element_op_;
+
+        // for checking vector load/store
+        index_t MRaw_;
+        index_t NRaw_;
+        index_t KRaw_;
+    };
+
+    // Invoker
+    struct Invoker : public BaseInvoker
+    {
+        using Argument = DeviceOp::Argument;
+
+        float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
+        {
+            if(!GridwiseGemm::CheckValidity(arg.as_grid_desc_m_k_,
+                                            arg.bs_grid_desc_n_k_,
+                                            arg.ds_grid_desc_m_n_,
+                                            arg.e_grid_desc_m_n_,
+                                            arg.block_2_etile_map_))
+            {
+                throw std::runtime_error("wrong! GridwiseGemm has invalid setting");
+            }
+
+            const index_t grid_size =
+                arg.block_2_etile_map_.CalculateGridSize(arg.e_grid_desc_m_n_);
+
+            auto launch_kernel = [&](auto has_main_k_block_loop) {
+                constexpr bool has_main_loop = has_main_k_block_loop.value;
+
+                const auto kernel = kernel_gemm_multiple_abd_xdl_cshuffle<
+                    GridwiseGemm,
+                    typename GridwiseGemm::AsGridPointer,
+                    typename GridwiseGemm::BsGridPointer,
+                    typename GridwiseGemm::DsGridPointer,
+                    EDataType,
+                    AElementwiseOperation,
+                    BElementwiseOperation,
+                    CDEElementwiseOperation,
+                    DeviceOp::AsGridDesc_AK0_M_AK1,
+                    DeviceOp::BsGridDesc_BK0_N_BK1,
+                    DeviceOp::DsGridDesc_MBlock_MPerBlock_NBlock_NPerBlock,
+                    DeviceOp::EGridDesc_MBlock_MPerBlock_NBlock_NPerBlock,
+                    DeviceOp::Block2ETileMap,
+                    has_main_loop>;
+
+                return launch_and_time_kernel(stream_config,
+                                              kernel,
+                                              dim3(grid_size),
+                                              dim3(BlockSize),
+                                              0,
+                                              arg.p_as_grid_,
+                                              arg.p_bs_grid_,
+                                              arg.p_ds_grid_,
+                                              arg.p_e_grid_,
+                                              arg.a_element_op_,
+                                              arg.b_element_op_,
+                                              arg.cde_element_op_,
+                                              arg.as_grid_desc_ak0_m_ak1_,
+                                              arg.bs_grid_desc_bk0_n_bk1_,
+                                              arg.ds_grid_desc_mblock_mperblock_nblock_nperblock_,
+                                              arg.e_grid_desc_mblock_mperblock_nblock_nperblock_,
+                                              arg.block_2_etile_map_);
+            };
+
+            const auto K = arg.as_grid_desc_m_k_[I0].GetLength(I1);
+
+            if(GridwiseGemm::CalculateHasMainKBlockLoop(K))
+            {
+                return launch_kernel(integral_constant<bool, true>{});
+            }
+            else
+            {
+                return launch_kernel(integral_constant<bool, false>{});
+            }
+        }
+
+        // polymorphic
+        float Run(const BaseArgument* p_arg,
+                  const StreamConfig& stream_config = StreamConfig{}) override
+        {
+            return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
+        }
+    };
+
+    static bool IsSupportedArgument(const Argument& arg)
+    {
+        if(!ck::is_xdl_supported())
+        {
+            return false;
+        }
+
+        // check vector load/store
+        {
+            using Row = ck::tensor_layout::gemm::RowMajor;
+            using Col = ck::tensor_layout::gemm::ColumnMajor;
+
+            bool all_valid = true;
+
+            static_for<0, NumATensor, 1>{}([&](auto i) {
+                using ALayout = remove_cvref_t<tuple_element_t<i.value, AsLayout>>;
+                // check vector load of A
+                if constexpr(is_same_v<ALayout, Row> && ABlockTransferSrcVectorDim == 2)
+                {
+                    if(arg.KRaw_ % ABlockTransferSrcScalarPerVector != 0)
+                    {
+                        all_valid = false;
+                    }
+                }
+                else if constexpr(is_same_v<ALayout, Col> && ABlockTransferSrcVectorDim == 1)
+                {
+                    // FIXME: not rigorous
+                    if(arg.MRaw_ % ABlockTransferSrcScalarPerVector != 0)
+                    {
+                        all_valid = false;
+                    }
+                }
+                else
+                {
+                    all_valid = false;
+                }
+            });
+
+            static_for<0, NumBTensor, 1>{}([&](auto i) {
+                using BLayout = remove_cvref_t<tuple_element_t<i.value, BsLayout>>;
+                // check vector laod of B
+                if constexpr(is_same_v<BLayout, Col> && BBlockTransferSrcVectorDim == 2)
+                {
+                    if(arg.KRaw_ % BBlockTransferSrcScalarPerVector != 0)
+                    {
+                        all_valid = false;
+                    }
+                }
+                else if constexpr(is_same_v<BLayout, Row> && BBlockTransferSrcVectorDim == 1)
+                {
+                    // FIXME: not rigorous
+                    if(arg.NRaw_ % BBlockTransferSrcScalarPerVector != 0)
+                    {
+                        all_valid = false;
+                    }
+                }
+                else
+                {
+                    all_valid = false;
+                }
+            });
+
+            // check vector load of Ds
+            // only support RowMajor for now
+
+            static_for<0, NumDTensor, 1>{}([&](auto i) {
+                using DLayout = remove_cvref_t<tuple_element_t<i.value, DsLayout>>;
+
+                if constexpr(!is_same_v<DLayout, Row>)
+                {
+                    all_valid = false;
+                }
+            });
+
+            if(!all_valid)
+            {
+                return false;
+            }
+
+            // check vector store of E
+            // only support RowMajor for now
+            if constexpr(is_same_v<ELayout, Row>)
+            {
+                if(arg.NRaw_ % CDEBlockTransferScalarPerVector_NPerBlock != 0)
+                {
+                    return false;
+                }
+            }
+            else
+            {
+                return false;
+            }
+        }
+
+        return GridwiseGemm::CheckValidity(arg.as_grid_desc_m_k_,
+                                           arg.bs_grid_desc_n_k_,
+                                           arg.ds_grid_desc_m_n_,
+                                           arg.e_grid_desc_m_n_,
+                                           arg.block_2_etile_map_);
+    }
+
+    // polymorphic
+    bool IsSupportedArgument(const BaseArgument* p_arg) override
+    {
+        return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
+    }
+
+    static auto MakeArgument(std::array<const void*, NumATensor> p_as,
+                             std::array<const void*, NumBTensor> p_bs,
+                             std::array<const void*, NumDTensor> p_ds,
+                             void* p_e,
+                             index_t MRaw,
+                             index_t NRaw,
+                             index_t KRaw,
+                             std::array<index_t, NumATensor> StrideAs,
+                             std::array<index_t, NumBTensor> StrideBs,
+                             std::array<index_t, NumDTensor> StrideDs,
+                             index_t StrideE,
+                             AElementwiseOperation a_element_op,
+                             BElementwiseOperation b_element_op,
+                             CDEElementwiseOperation cde_element_op)
+    {
+        return Argument{p_as,
+                        p_bs,
+                        p_ds,
+                        p_e,
+                        MRaw,
+                        NRaw,
+                        KRaw,
+                        StrideAs,
+                        StrideBs,
+                        StrideDs,
+                        StrideE,
+                        a_element_op,
+                        b_element_op,
+                        cde_element_op};
+    }
+
+    static auto MakeInvoker() { return Invoker{}; }
+
+    // polymorphic
+    std::unique_ptr<BaseArgument>
+    MakeArgumentPointer(std::array<const void*, NumATensor> p_as,
+                        std::array<const void*, NumBTensor> p_bs,
+                        std::array<const void*, NumDTensor> p_ds,
+                        void* p_e,
+                        index_t MRaw,
+                        index_t NRaw,
+                        index_t KRaw,
+                        std::array<ck::index_t, NumATensor> StrideAs,
+                        std::array<ck::index_t, NumBTensor> StrideBs,
+                        std::array<ck::index_t, NumDTensor> StrideDs,
+                        index_t StrideE,
+                        AElementwiseOperation a_element_op,
+                        BElementwiseOperation b_element_op,
+                        CDEElementwiseOperation cde_element_op) override
+    {
+        return std::make_unique<Argument>(p_as,
+                                          p_bs,
+                                          p_ds,
+                                          p_e,
+                                          MRaw,
+                                          NRaw,
+                                          KRaw,
+                                          StrideAs,
+                                          StrideBs,
+                                          StrideDs,
+                                          StrideE,
+                                          a_element_op,
+                                          b_element_op,
+                                          cde_element_op);
+    }
+
+    // polymorphic
+    std::unique_ptr<BaseInvoker> MakeInvokerPointer() override
+    {
+        return std::make_unique<Invoker>(Invoker{});
+    }
+
+    // polymorphic
+    std::string GetTypeString() const override
+    {
+        auto str = std::stringstream();
+
+        std::map<LoopScheduler, std::string> LoopSchedToString{
+            {LoopScheduler::Default, "Default"}, {LoopScheduler::Interwave, "Interwave"}};
+
+        std::map<PipelineVersion, std::string> PipelineVersionToString{{PipelineVersion::v1, "v1"},
+                                                                       {PipelineVersion::v2, "v2"}};
+
+        // clang-format off
+        str << "DeviceGemmMultipleABD_Xdl_CShuffle"
+            << "<"
+            << BlockSize << ", "
+            << MPerBlock << ", "
+            << NPerBlock << ", "
+            << KPerBlock << ", "
+            << AK1 << ", "
+            << BK1 << ", "
+            << MPerXDL << ", "
+            << NPerXDL << ", "
+            << MXdlPerWave << ", "
+            << NXdlPerWave << ", "
+            << ABlockTransferSrcScalarPerVector << ", "
+            << BBlockTransferSrcScalarPerVector << ", "
+            << CShuffleMXdlPerWavePerShuffle << ", "
+            << CShuffleNXdlPerWavePerShuffle << ", "
+            << getGemmSpecializationString(GemmSpec)
+            << ">"
+            << " LoopScheduler: "
+            << LoopSchedToString[LoopSched] << ", "
+            << "PipelineVersion: "
+            << PipelineVersionToString[PipelineVer];
+        // clang-format on
+
+        return str.str();
+    }
+};
+
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

include/ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_dl.hpp

@@ -50,9 +50,8 @@ __global__ void
             const CGridDesc_M0_M10_M11_N0_N10_N11 e_grid_desc_m0_m10_m11_n0_n10_n11,
             const Block2CTileMap block_2_ctile_map)
 {
-#if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx906__) || defined(__gfx908__) ||             \
-    defined(__gfx90a__) || defined(__gfx940__) || defined(__gfx1030__) || defined(__gfx1100__) || \
-    defined(__gfx1101__) || defined(__gfx1102__))
+#if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx906__) || defined(__gfx908__) || \
+    defined(__gfx90a__) || defined(__gfx94__) || defined(__gfx103__) || defined(__gfx11__))
 
     constexpr index_t shared_block_size =
         GridwiseGemm::GetSharedMemoryNumberOfByte() / sizeof(ABDataType);
@@ -552,10 +551,8 @@ struct DeviceGemmMultipleD_Dl : public DeviceGemmMultipleD<ALayout,
 
     static bool IsSupportedArgument(const Argument& arg)
     {
-        if(ck::get_device_name() == "gfx906" || ck::get_device_name() == "gfx908" ||
-           ck::get_device_name() == "gfx90a" || ck::get_device_name() == "gfx1030" ||
-           ck::get_device_name() == "gfx940" || ck::get_device_name() == "gfx1100" ||
-           ck::get_device_name() == "gfx1101" || ck::get_device_name() == "gfx1102")
+        if(ck::get_device_name() == "gfx906" || ck::is_xdl_supported() ||
+           ck::is_navi2_supported() || ck::is_navi3_supported())
         {
             return GridwiseGemm::CheckValidity(
                 arg.a_grid_desc_k0_m_k1_, arg.b_grid_desc_k0_n_k1_, arg.e_grid_desc_m_n_);

include/ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_layernorm_xdl_cshuffle.hpp

@@ -64,7 +64,7 @@ __global__ void
             index_t NRaw)
 {
 #if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__) || \
-    defined(__gfx940__))
+    defined(__gfx94__))
     __shared__ char p_shared[GridwiseGemmWelford::GetSharedMemoryNumberOfByte()];
 
     GridwiseGemmWelford::template Run<HasMainKBlockLoop>(
@@ -364,11 +364,13 @@ struct DeviceGemmMultipleDLayernorm_Xdl_CShuffle
     using DsGridDesc_M_N = remove_cvref_t<decltype(MakeDsGridDescriptor_M_N({}, {}, {}))>;
     // We have to separate mean var descriptor for gemm and layernorm bacause of different grid
     // layout(different padding)
-    using GemmMeanVarGridDesc_M_NBlock = decltype(
-        MakeMeanVarDescriptor_M_N<Sequence<true, false>, GemmMPerBlock, GemmNPerBlock>(1, 1));
+    using GemmMeanVarGridDesc_M_NBlock =
+        decltype(MakeMeanVarDescriptor_M_N<Sequence<true, false>, GemmMPerBlock, GemmNPerBlock>(1,
+                                                                                                1));
 
-    using GemmCountGridDesc_M_NBlock = decltype(
-        MakeCountDescriptor_M_N<Sequence<true, false>, GemmMPerBlock, GemmNPerBlock>(1, 1));
+    using GemmCountGridDesc_M_NBlock =
+        decltype(MakeCountDescriptor_M_N<Sequence<true, false>, GemmMPerBlock, GemmNPerBlock>(1,
+                                                                                              1));
 
     using LayernormMeanVarGridDesc_M_NBlock =
         decltype(MakeMeanVarDescriptor_M_N<Sequence<true, true>,
@@ -819,7 +821,9 @@ struct DeviceGemmMultipleDLayernorm_Xdl_CShuffle
         return (workspace_size);
     };
 
-    void SetWorkSpacePointer(BaseArgument* pArg, void* p_workspace) const override
+    void SetWorkSpacePointer(BaseArgument* pArg,
+                             void* p_workspace,
+                             const StreamConfig& = StreamConfig{}) const override
     {
         Argument* pArg_ = dynamic_cast<Argument*>(pArg);
 
@@ -855,8 +859,7 @@ struct DeviceGemmMultipleDLayernorm_Xdl_CShuffle
 
     static bool IsSupportedArgument(const Argument& arg)
     {
-        if(!(ck::get_device_name() == "gfx908" || ck::get_device_name() == "gfx90a" ||
-             ck::get_device_name() == "gfx940"))
+        if(!ck::is_xdl_supported())
         {
             return false;
         }

include/ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_multiple_r_xdl_cshuffle.hpp

@@ -61,7 +61,7 @@ __global__ void
             const Block2ETileMap block_2_etile_map)
 {
 #if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__) || \
-    defined(__gfx940__))
+    defined(__gfx94__))
     __shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()];
 
     GridwiseGemm::template Run<HasMainKBlockLoop>(p_a_grid,
@@ -337,10 +337,12 @@ struct DeviceGemmMultipleDMultipleR_Xdl_CShuffle
         RThreadTransferDstScalarPerVector_MPerBlock,
         LoopSched>;
 
-    using AGridDesc_AK0_M_AK1 = remove_cvref_t<decltype(
-        GridwiseGemm::MakeDefaultAGridDescriptor_AK0_M_AK1(AGridDesc_M_K{}))>;
-    using BGridDesc_BK0_N_BK1 = remove_cvref_t<decltype(
-        GridwiseGemm::MakeDefaultBGridDescriptor_BK0_N_BK1(BGridDesc_N_K{}))>;
+    using AGridDesc_AK0_M_AK1 =
+        remove_cvref_t<decltype(GridwiseGemm::MakeDefaultAGridDescriptor_AK0_M_AK1(
+            AGridDesc_M_K{}))>;
+    using BGridDesc_BK0_N_BK1 =
+        remove_cvref_t<decltype(GridwiseGemm::MakeDefaultBGridDescriptor_BK0_N_BK1(
+            BGridDesc_N_K{}))>;
 
     using Block2ETileMap = typename GridwiseGemm::DefaultBlock2ETileMap;
 
@@ -555,8 +557,7 @@ struct DeviceGemmMultipleDMultipleR_Xdl_CShuffle
 
     static bool IsSupportedArgument(const Argument& arg)
     {
-        if(!(ck::get_device_name() == "gfx908" || ck::get_device_name() == "gfx90a" ||
-             ck::get_device_name() == "gfx940"))
+        if(!ck::is_xdl_supported())
         {
             return false;
         }

include/ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_wmma_cshuffle.hpp

@@ -513,8 +513,7 @@ struct DeviceGemmMultipleD_Wmma_CShuffle : public DeviceGemmMultipleD<ALayout,
 
     static bool IsSupportedArgument(const Argument& arg)
     {
-        if(ck::get_device_name() == "gfx1100" || ck::get_device_name() == "gfx1101" ||
-           ck::get_device_name() == "gfx1102")
+        if(ck::is_navi3_supported())
         {
             if constexpr(!(is_same_v<AccDataType, float> || is_same_v<AccDataType, int32_t>))
             {

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

@@ -20,7 +20,8 @@
 namespace ck {
 
 template <typename GridwiseGemm,
-          typename ABDataType,
+          typename ADataType,
+          typename BDataType,
           typename DsPointer,
           typename EDataType,
           typename AElementwiseOperation,
@@ -36,8 +37,8 @@ __global__ void
 #if CK_USE_LAUNCH_BOUNDS
     __launch_bounds__(CK_MAX_THREAD_PER_BLOCK, CK_MIN_BLOCK_PER_CU)
 #endif
-        kernel_gemm_multiple_d_xdl_cshuffle(const ABDataType* __restrict__ p_a_grid,
-                                            const ABDataType* __restrict__ p_b_grid,
+        kernel_gemm_multiple_d_xdl_cshuffle(const ADataType* __restrict__ p_a_grid,
+                                            const BDataType* __restrict__ p_b_grid,
                                             DsPointer p_ds_grid,
                                             EDataType* __restrict__ p_e_grid,
                                             const AElementwiseOperation a_element_op,
@@ -52,7 +53,7 @@ __global__ void
                                             const Block2ETileMap block_2_etile_map)
 {
 #if(!defined(__HIP_DEVICE_COMPILE__) || defined(__gfx908__) || defined(__gfx90a__) || \
-    defined(__gfx940__))
+    defined(__gfx94__))
     __shared__ char p_shared[GridwiseGemm::GetSharedMemoryNumberOfByte()];
 
     GridwiseGemm::template Run<HasMainKBlockLoop>(p_a_grid,
@@ -143,7 +144,8 @@ template <typename ALayout,
           typename CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
           index_t CDEBlockTransferScalarPerVector_NPerBlock,
           LoopScheduler LoopSched     = make_default_loop_scheduler(),
-          PipelineVersion PipelineVer = PipelineVersion::v1>
+          PipelineVersion PipelineVer = PipelineVersion::v1,
+          typename ComputeDataType    = EDataType>
 struct DeviceGemmMultipleD_Xdl_CShuffle : public DeviceGemmMultipleD<ALayout,
                                                                      BLayout,
                                                                      DsLayout,
@@ -244,7 +246,9 @@ struct DeviceGemmMultipleD_Xdl_CShuffle : public DeviceGemmMultipleD<ALayout,
 
     // GridwiseGemm
     using GridwiseGemm = GridwiseGemmMultipleD_xdl_cshuffle<
-        ADataType, // TODO: distinguish A/B datatype
+        ADataType,
+        BDataType,
+        ComputeDataType,
         AccDataType,
         CShuffleDataType,
         DsDataType,
@@ -288,14 +292,18 @@ struct DeviceGemmMultipleD_Xdl_CShuffle : public DeviceGemmMultipleD<ALayout,
         PipelineVer>;
 
     // desc for blockwise copy
-    using AGridDesc_AK0_M_AK1                          = remove_cvref_t<decltype(
-        GridwiseGemm::MakeDefaultAGridDescriptor_AK0_M_AK1(AGridDesc_M_K{}))>;
-    using BGridDesc_BK0_N_BK1                          = remove_cvref_t<decltype(
-        GridwiseGemm::MakeDefaultBGridDescriptor_BK0_N_BK1(BGridDesc_N_K{}))>;
-    using DsGridDesc_MBlock_MPerBlock_NBlock_NPerBlock = remove_cvref_t<decltype(
-        GridwiseGemm::MakeDsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(DsGridDesc_M_N{}))>;
-    using EGridDesc_MBlock_MPerBlock_NBlock_NPerBlock  = remove_cvref_t<decltype(
-        GridwiseGemm::MakeEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(EGridDesc_M_N{}))>;
+    using AGridDesc_AK0_M_AK1 =
+        remove_cvref_t<decltype(GridwiseGemm::MakeDefaultAGridDescriptor_AK0_M_AK1(
+            AGridDesc_M_K{}))>;
+    using BGridDesc_BK0_N_BK1 =
+        remove_cvref_t<decltype(GridwiseGemm::MakeDefaultBGridDescriptor_BK0_N_BK1(
+            BGridDesc_N_K{}))>;
+    using DsGridDesc_MBlock_MPerBlock_NBlock_NPerBlock = remove_cvref_t<
+        decltype(GridwiseGemm::MakeDsGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
+            DsGridDesc_M_N{}))>;
+    using EGridDesc_MBlock_MPerBlock_NBlock_NPerBlock =
+        remove_cvref_t<decltype(GridwiseGemm::MakeEGridDescriptor_MBlock_MPerBlock_NBlock_NPerBlock(
+            EGridDesc_M_N{}))>;
 
     // block-to-e-tile map
     using Block2ETileMap =
@@ -438,6 +446,7 @@ struct DeviceGemmMultipleD_Xdl_CShuffle : public DeviceGemmMultipleD<ALayout,
                 const auto kernel = kernel_gemm_multiple_d_xdl_cshuffle<
                     GridwiseGemm,
                     ADataType, // TODO: distiguish A/B datatype
+                    BDataType, // TODO: distiguish A/B datatype
                     typename GridwiseGemm::DsGridPointer,
                     EDataType,
                     AElementwiseOperation,
@@ -491,8 +500,7 @@ struct DeviceGemmMultipleD_Xdl_CShuffle : public DeviceGemmMultipleD<ALayout,
 
     static bool IsSupportedArgument(const Argument& arg)
     {
-        if(!(ck::get_device_name() == "gfx908" || ck::get_device_name() == "gfx90a" ||
-             ck::get_device_name() == "gfx940"))
+        if(!ck::is_xdl_supported())
         {
             return false;
         }

include/ck/tensor_operation/gpu/device/impl/device_gemm_multiple_d_xdl_cshuffle_lds_direct_load.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include <iostream>
+#include <sstream>
+
+#include "ck/utility/common_header.hpp"
+#include "ck/tensor_description/tensor_descriptor.hpp"
+#include "ck/tensor_description/tensor_descriptor_helper.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_gemm_multiple_d.hpp"
+#include "ck/tensor_operation/gpu/grid/gridwise_gemm_multiple_d_xdl_cshuffle_lds_direct_load.hpp"
+#include "ck/host_utility/device_prop.hpp"
+#include "ck/host_utility/kernel_launch.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+
+template <typename ALayout,
+          typename BLayout,
+          typename DsLayout,
+          typename ELayout,
+          typename ADataType,
+          typename BDataType,
+          typename AccDataType,
+          typename CShuffleDataType,
+          typename DsDataType,
+          typename EDataType,
+          typename AElementwiseOperation,
+          typename BElementwiseOperation,
+          typename CDEElementwiseOperation,
+          GemmSpecialization GemmSpec,
+          index_t NumGemmKPrefetchStage,
+          index_t BlockSize,
+          index_t MPerBlock,
+          index_t NPerBlock,
+          index_t KPerBlock,
+          index_t AK1,
+          index_t BK1,
+          index_t MPerXDL,
+          index_t NPerXDL,
+          index_t MXdlPerWave,
+          index_t NXdlPerWave,
+          typename ABlockTransferThreadClusterLengths_AK0_M_AK1,
+          typename ABlockTransferSrcAccessOrder,
+          index_t ABlockTransferSrcVectorDim,
+          index_t ABlockTransferScalarPerVector,
+          index_t ABlockLdsExtraM,
+          typename BBlockTransferThreadClusterLengths_BK0_N_BK1,
+          typename BBlockTransferSrcAccessOrder,
+          index_t BBlockTransferSrcVectorDim,
+          index_t BBlockTransferScalarPerVector,
+          index_t BBlockLdsExtraN,
+          index_t CShuffleMXdlPerWavePerShuffle,
+          index_t CShuffleNXdlPerWavePerShuffle,
+          typename CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
+          index_t CDEBlockTransferScalarPerVector_NPerBlock,
+          LoopScheduler LoopSched     = make_default_loop_scheduler(),
+          PipelineVersion PipelineVer = PipelineVersion::v4,
+          typename ComputeDataType    = EDataType>
+struct DeviceGemmMultipleD_Xdl_CShuffle_LdsDirectLoad
+    : public DeviceGemmMultipleD<ALayout,
+                                 BLayout,
+                                 DsLayout,
+                                 ELayout,
+                                 ADataType,
+                                 BDataType,
+                                 DsDataType,
+                                 EDataType,
+                                 AElementwiseOperation,
+                                 BElementwiseOperation,
+                                 CDEElementwiseOperation>
+{
+    static constexpr auto I1            = Number<1>{};
+    static constexpr index_t NumDTensor = DsDataType::Size();
+
+    using GridwiseGemm = GridwiseGemmMultipleD_Xdl_CShuffle_LdsDirectLoad<
+        ALayout,
+        BLayout,
+        DsLayout,
+        ELayout,
+        ADataType,
+        BDataType,
+        ComputeDataType,
+        AccDataType,
+        CShuffleDataType,
+        DsDataType,
+        EDataType,
+        AElementwiseOperation,
+        BElementwiseOperation,
+        CDEElementwiseOperation,
+        InMemoryDataOperationEnum::Set,
+        GemmSpec,
+        NumGemmKPrefetchStage,
+        BlockSize,
+        MPerBlock,
+        NPerBlock,
+        KPerBlock,
+        AK1,
+        BK1,
+        MPerXDL,
+        NPerXDL,
+        MXdlPerWave,
+        NXdlPerWave,
+        ABlockTransferThreadClusterLengths_AK0_M_AK1,
+        ABlockTransferSrcAccessOrder,
+        ABlockTransferSrcVectorDim,
+        ABlockTransferScalarPerVector,
+        ABlockLdsExtraM,
+        BBlockTransferThreadClusterLengths_BK0_N_BK1,
+        BBlockTransferSrcAccessOrder,
+        BBlockTransferSrcVectorDim,
+        BBlockTransferScalarPerVector,
+        BBlockLdsExtraN,
+        CShuffleMXdlPerWavePerShuffle,
+        CShuffleNXdlPerWavePerShuffle,
+        CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
+        CDEBlockTransferScalarPerVector_NPerBlock,
+        LoopSched,
+        PipelineVer>;
+
+    using Argument = typename GridwiseGemm::Argument;
+
+    struct Invoker : public BaseInvoker
+    {
+
+        float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
+        {
+            if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_m_k_,
+                                            arg.b_grid_desc_n_k_,
+                                            arg.ds_grid_desc_m_n_,
+                                            arg.e_grid_desc_m_n_,
+                                            arg.block_2_etile_map_))
+            {
+                throw std::runtime_error("wrong! GridwiseGemm has invalid setting");
+            }
+
+            const index_t grid_size =
+                arg.block_2_etile_map_.CalculateGridSize(arg.e_grid_desc_m_n_);
+
+            auto launch_kernel = [&](auto has_main_k_block_loop) {
+                constexpr bool has_main_loop = has_main_k_block_loop.value;
+
+                const auto kernel = kernel_gemm_multiple_d_xdl_cshuffle_lds_direct_load<
+                    GridwiseGemm,
+                    ADataType,
+                    BDataType,
+                    typename GridwiseGemm::DsGridPointer,
+                    EDataType,
+                    AElementwiseOperation,
+                    BElementwiseOperation,
+                    CDEElementwiseOperation,
+                    typename GridwiseGemm::AGridDesc_AK0_M_AK1,
+                    typename GridwiseGemm::BGridDesc_BK0_N_BK1,
+                    typename GridwiseGemm::DsGridDesc_MBlock_MPerBlock_NBlock_NPerBlock,
+                    typename GridwiseGemm::EGridDesc_MBlock_MPerBlock_NBlock_NPerBlock,
+                    typename GridwiseGemm::Block2ETileMap,
+                    has_main_loop>;
+
+                return launch_and_time_kernel(stream_config,
+                                              kernel,
+                                              dim3(grid_size),
+                                              dim3(BlockSize),
+                                              0,
+                                              arg.p_a_grid_,
+                                              arg.p_b_grid_,
+                                              arg.p_ds_grid_,
+                                              arg.p_e_grid_,
+                                              arg.a_element_op_,
+                                              arg.b_element_op_,
+                                              arg.cde_element_op_,
+                                              arg.a_grid_desc_ak0_m_ak1_,
+                                              arg.b_grid_desc_bk0_n_bk1_,
+                                              arg.ds_grid_desc_mblock_mperblock_nblock_nperblock_,
+                                              arg.e_grid_desc_mblock_mperblock_nblock_nperblock_,
+                                              arg.block_2_etile_map_);
+            };
+
+            const auto K = arg.a_grid_desc_m_k_.GetLength(I1);
+
+            if(GridwiseGemm::CalculateHasMainKBlockLoop(K))
+            {
+                return launch_kernel(integral_constant<bool, true>{});
+            }
+            else
+            {
+                return launch_kernel(integral_constant<bool, false>{});
+            }
+        }
+
+        float Run(const BaseArgument* p_arg,
+                  const StreamConfig& stream_config = StreamConfig{}) override
+        {
+            return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
+        }
+    };
+
+    static bool IsSupportedArgument(const Argument& arg)
+    {
+        if(!ck::is_xdl_supported())
+        {
+            return false;
+        }
+
+        if(!ck::is_lds_direct_load_supported())
+        {
+            return false;
+        }
+
+        // Check vector load/store.
+        {
+            using Row = ck::tensor_layout::gemm::RowMajor;
+            using Col = ck::tensor_layout::gemm::ColumnMajor;
+
+            // Check vector load of A.
+            if constexpr(is_same_v<ALayout, Row> && ABlockTransferSrcVectorDim == 2)
+            {
+                if(arg.KRaw_ % ABlockTransferScalarPerVector != 0)
+                {
+                    return false;
+                }
+            }
+            else if constexpr(is_same_v<ALayout, Col> && ABlockTransferSrcVectorDim == 1)
+            {
+                if(arg.MRaw_ % ABlockTransferScalarPerVector != 0)
+                {
+                    return false;
+                }
+            }
+            else
+            {
+                return false;
+            }
+
+            // Check vector load of B.
+            if constexpr(is_same_v<BLayout, Col> && BBlockTransferSrcVectorDim == 2)
+            {
+                if(arg.KRaw_ % BBlockTransferScalarPerVector != 0)
+                {
+                    return false;
+                }
+            }
+            else if constexpr(is_same_v<BLayout, Row> && BBlockTransferSrcVectorDim == 1)
+            {
+                if(arg.NRaw_ % BBlockTransferScalarPerVector != 0)
+                {
+                    return false;
+                }
+            }
+            else
+            {
+                return false;
+            }
+
+            // Check vector load of Ds.
+            // For now, only the RowMajor layout is supported.
+            bool all_valid = true;
+
+            static_for<0, NumDTensor, 1>{}([&](auto i) {
+                using DLayout = remove_cvref_t<tuple_element_t<i.value, DsLayout>>;
+
+                if constexpr(!is_same_v<DLayout, Row>)
+                {
+                    all_valid = false;
+                }
+            });
+
+            if(!all_valid)
+            {
+                return false;
+            }
+
+            // Check vector load of E.
+            // For now, only the RowMajor layout is supported.
+            if constexpr(is_same_v<ELayout, Row>)
+            {
+                if(arg.NRaw_ % CDEBlockTransferScalarPerVector_NPerBlock != 0)
+                {
+                    return false;
+                }
+            }
+            else
+            {
+                return false;
+            }
+        }
+
+        return GridwiseGemm::CheckValidity(arg.a_grid_desc_m_k_,
+                                           arg.b_grid_desc_n_k_,
+                                           arg.ds_grid_desc_m_n_,
+                                           arg.e_grid_desc_m_n_,
+                                           arg.block_2_etile_map_);
+    }
+
+    bool IsSupportedArgument(const BaseArgument* p_arg) override
+    {
+        return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
+    }
+
+    static auto MakeArgument(const void* p_a,
+                             const void* p_b,
+                             std::array<const void*, NumDTensor> p_ds,
+                             void* p_e,
+                             index_t MRaw,
+                             index_t NRaw,
+                             index_t KRaw,
+                             index_t StrideA,
+                             index_t StrideB,
+                             std::array<index_t, NumDTensor> StrideDs,
+                             index_t StrideE,
+                             AElementwiseOperation a_element_op,
+                             BElementwiseOperation b_element_op,
+                             CDEElementwiseOperation cde_element_op)
+    {
+        return Argument{p_a,
+                        p_b,
+                        p_ds,
+                        p_e,
+                        MRaw,
+                        NRaw,
+                        KRaw,
+                        StrideA,
+                        StrideB,
+                        StrideDs,
+                        StrideE,
+                        a_element_op,
+                        b_element_op,
+                        cde_element_op};
+    }
+
+    static auto MakeInvoker() { return Invoker{}; }
+
+    std::unique_ptr<BaseArgument>
+    MakeArgumentPointer(const void* p_a,
+                        const void* p_b,
+                        std::array<const void*, NumDTensor> p_ds,
+                        void* p_e,
+                        index_t MRaw,
+                        index_t NRaw,
+                        index_t KRaw,
+                        index_t StrideA,
+                        index_t StrideB,
+                        std::array<ck::index_t, NumDTensor> StrideDs,
+                        index_t StrideE,
+                        AElementwiseOperation a_element_op,
+                        BElementwiseOperation b_element_op,
+                        CDEElementwiseOperation cde_element_op) override
+    {
+        return std::make_unique<Argument>(p_a,
+                                          p_b,
+                                          p_ds,
+                                          p_e,
+                                          MRaw,
+                                          NRaw,
+                                          KRaw,
+                                          StrideA,
+                                          StrideB,
+                                          StrideDs,
+                                          StrideE,
+                                          a_element_op,
+                                          b_element_op,
+                                          cde_element_op);
+    }
+
+    std::unique_ptr<BaseInvoker> MakeInvokerPointer() override
+    {
+        return std::make_unique<Invoker>(Invoker{});
+    }
+
+    std::string GetTypeString() const override
+    {
+        auto str = std::stringstream();
+
+        std::map<LoopScheduler, std::string> LoopSchedToString{
+            {LoopScheduler::Default, "Default"}, {LoopScheduler::Interwave, "Interwave"}};
+
+        std::map<PipelineVersion, std::string> PipelineVersionToString{
+            {PipelineVersion::v1, "v1"}, {PipelineVersion::v2, "v2"}, {PipelineVersion::v4, "v4"}};
+
+        // clang-format off
+        str << "DeviceGemmMultipleD_Xdl_CShuffle_LdsDirectLoad"
+            << "<"
+            << BlockSize << ", "
+            << MPerBlock << ", "
+            << NPerBlock << ", "
+            << KPerBlock << ", "
+            << AK1 << ", "
+            << BK1 << ", "
+            << MPerXDL << ", "
+            << NPerXDL << ", "
+            << MXdlPerWave << ", "
+            << NXdlPerWave << ", "
+            << ABlockTransferScalarPerVector << ", "
+            << BBlockTransferScalarPerVector << ", "
+            << CShuffleMXdlPerWavePerShuffle << ", "
+            << CShuffleNXdlPerWavePerShuffle << ", "
+            << getGemmSpecializationString(GemmSpec)
+            << ">"
+            << " LoopScheduler: "
+            << LoopSchedToString[LoopSched] << ", "
+            << "PipelineVersion: "
+            << PipelineVersionToString[PipelineVer];
+        // clang-format on
+
+        return str.str();
+    }
+};
+
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

include/ck/tensor_operation/gpu/device/impl/device_gemm_reduce_xdl_cshuffle.hpp

@@ -645,6 +645,11 @@ struct DeviceGemmReduce_Xdl_CShuffle : public DeviceGemmReduce<0, ReduceOperatio
 
     static bool IsSupportedArgument(const Argument& arg)
     {
+        if(!ck::is_xdl_supported())
+        {
+            return false;
+        }
+
         return GridwiseGemm::CheckValidity(arg.a_grid_desc_ak0_m_ak1_,
                                            arg.b_grid_desc_bk0_n_bk1_,
                                            arg.c_grid_desc_m_n_,

include/ck/tensor_operation/gpu/device/impl/device_gemm_wmma.hpp

@@ -441,8 +441,7 @@ struct DeviceGemmWmma_CShuffle : public DeviceGemm<ALayout,
 
     static bool IsSupportedArgument(const Argument& arg)
     {
-        if(ck::get_device_name() == "gfx1100" || ck::get_device_name() == "gfx1101" ||
-           ck::get_device_name() == "gfx1102")
+        if(ck::is_navi3_supported())
         {
             if constexpr(!(is_same_v<AccDataType, float> || is_same_v<AccDataType, ck::half_t> ||
                            is_same_v<AccDataType, int32_t>))

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

@@ -184,7 +184,7 @@ struct DeviceGemmXdl : public DeviceGemm<ALayout,
                 return false;
             }
         }
-        else if(ck::get_device_name() == "gfx90a" || ck::get_device_name() == "gfx940")
+        else if(ck::is_lds_direct_load_supported())
         {
             if constexpr(!(is_same_v<AccDataType, float> || is_same_v<AccDataType, float> ||
                            is_same_v<AccDataType, int32_t> || is_same_v<AccDataType, double>))

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

@@ -65,7 +65,9 @@ template <typename ALayout,
           typename CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
           index_t CShuffleBlockTransferScalarPerVector_NPerBlock,
           LoopScheduler LoopSched     = make_default_loop_scheduler(),
-          PipelineVersion PipelineVer = PipelineVersion::v1>
+          PipelineVersion PipelineVer = PipelineVersion::v1,
+          typename ComputeTypeA       = CDataType,
+          typename ComputeTypeB       = ComputeTypeA>
 struct DeviceGemm_Xdl_CShuffle : public DeviceGemm<ALayout,
                                                    BLayout,
                                                    CLayout,
@@ -87,7 +89,8 @@ struct DeviceGemm_Xdl_CShuffle : public DeviceGemm<ALayout,
         ALayout,
         BLayout,
         CLayout,
-        ADataType, // TODO: distinguish A/B datatype
+        ADataType,
+        BDataType,
         GemmAccDataType,
         CShuffleDataType,
         CDataType,
@@ -128,7 +131,9 @@ struct DeviceGemm_Xdl_CShuffle : public DeviceGemm<ALayout,
         CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
         CShuffleBlockTransferScalarPerVector_NPerBlock,
         LoopSched,
-        PipelineVer>;
+        PipelineVer,
+        ComputeTypeA,
+        ComputeTypeB>;
 
     using Argument = typename GridwiseGemm::Argument;
 
@@ -188,8 +193,7 @@ struct DeviceGemm_Xdl_CShuffle : public DeviceGemm<ALayout,
 
     static bool IsSupportedArgument(const Argument& arg)
     {
-        if(!(ck::get_device_name() == "gfx908" || ck::get_device_name() == "gfx90a" ||
-             ck::get_device_name() == "gfx940"))
+        if(!ck::is_xdl_supported())
         {
             return false;
         }
@@ -274,6 +278,7 @@ struct DeviceGemm_Xdl_CShuffle : public DeviceGemm<ALayout,
         // clang-format off
         str << "DeviceGemm_Xdl_CShuffle"
             << "<"
+            << getGemmSpecializationString(GemmSpec) << ", "
             << BlockSize << ", "
             << MPerBlock << ", "
             << NPerBlock << ", "
@@ -292,7 +297,7 @@ struct DeviceGemm_Xdl_CShuffle : public DeviceGemm<ALayout,
             << " LoopScheduler: "
             << LoopSchedToString[LoopSched] << ", "
             << "PipelineVersion: "
-            << PipelineVersionToString[PipelineVer];;
+            << PipelineVersionToString[PipelineVer];
         // clang-format on
 
         return str.str();

include/ck/tensor_operation/gpu/device/impl/device_gemm_xdl_cshuffle_lds_direct_load.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include <iostream>
+#include <sstream>
+
+#include "ck/utility/common_header.hpp"
+#include "ck/tensor_description/tensor_descriptor.hpp"
+#include "ck/tensor_description/tensor_descriptor_helper.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_gemm.hpp"
+#include "ck/tensor_operation/gpu/grid/gridwise_gemm_multiple_d_xdl_cshuffle_lds_direct_load.hpp"
+#include "ck/host_utility/device_prop.hpp"
+#include "ck/host_utility/kernel_launch.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+
+template <typename ALayout,
+          typename BLayout,
+          typename ELayout,
+          typename ADataType,
+          typename BDataType,
+          typename EDataType,
+          typename AccDataType,
+          typename CShuffleDataType,
+          typename AElementwiseOperation,
+          typename BElementwiseOperation,
+          typename CDEElementwiseOperation,
+          GemmSpecialization GemmSpec,
+          index_t NumGemmKPrefetchStage,
+          index_t BlockSize,
+          index_t MPerBlock,
+          index_t NPerBlock,
+          index_t KPerBlock,
+          index_t AK1,
+          index_t BK1,
+          index_t MPerXDL,
+          index_t NPerXDL,
+          index_t MXdlPerWave,
+          index_t NXdlPerWave,
+          typename ABlockTransferThreadClusterLengths_AK0_M_AK1,
+          typename ABlockTransferSrcAccessOrder,
+          index_t ABlockTransferSrcVectorDim,
+          index_t ABlockTransferScalarPerVector,
+          bool ABlockLdsExtraM,
+          typename BBlockTransferThreadClusterLengths_BK0_N_BK1,
+          typename BBlockTransferSrcAccessOrder,
+          index_t BBlockTransferSrcVectorDim,
+          index_t BBlockTransferScalarPerVector,
+          bool BBlockLdsExtraN,
+          index_t CShuffleMXdlPerWavePerShuffle,
+          index_t CShuffleNXdlPerWavePerShuffle,
+          typename CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
+          index_t CDEBlockTransferScalarPerVector_NPerBlock,
+          LoopScheduler LoopSched     = make_default_loop_scheduler(),
+          PipelineVersion PipelineVer = PipelineVersion::v4,
+          typename ComputeDataType    = EDataType>
+struct DeviceGemm_Xdl_CShuffle_LdsDirectLoad : public DeviceGemm<ALayout,
+                                                                 BLayout,
+                                                                 ELayout,
+                                                                 ADataType,
+                                                                 BDataType,
+                                                                 EDataType,
+                                                                 AElementwiseOperation,
+                                                                 BElementwiseOperation,
+                                                                 CDEElementwiseOperation>
+{
+    static constexpr auto I1 = Number<1>{};
+
+    using GridwiseGemm = GridwiseGemmMultipleD_Xdl_CShuffle_LdsDirectLoad<
+        ALayout,
+        BLayout,
+        ck::Tuple<>,
+        ELayout,
+        ADataType,
+        BDataType,
+        ComputeDataType,
+        AccDataType,
+        CShuffleDataType,
+        ck::Tuple<>,
+        EDataType,
+        AElementwiseOperation,
+        BElementwiseOperation,
+        CDEElementwiseOperation,
+        InMemoryDataOperationEnum::Set,
+        GemmSpec,
+        NumGemmKPrefetchStage,
+        BlockSize,
+        MPerBlock,
+        NPerBlock,
+        KPerBlock,
+        AK1,
+        BK1,
+        MPerXDL,
+        NPerXDL,
+        MXdlPerWave,
+        NXdlPerWave,
+        ABlockTransferThreadClusterLengths_AK0_M_AK1,
+        ABlockTransferSrcAccessOrder,
+        ABlockTransferSrcVectorDim,
+        ABlockTransferScalarPerVector,
+        ABlockLdsExtraM,
+        BBlockTransferThreadClusterLengths_BK0_N_BK1,
+        BBlockTransferSrcAccessOrder,
+        BBlockTransferSrcVectorDim,
+        BBlockTransferScalarPerVector,
+        BBlockLdsExtraN,
+        CShuffleMXdlPerWavePerShuffle,
+        CShuffleNXdlPerWavePerShuffle,
+        CDEBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
+        CDEBlockTransferScalarPerVector_NPerBlock,
+        LoopSched,
+        PipelineVer>;
+
+    using Argument = typename GridwiseGemm::Argument;
+
+    struct Invoker : public BaseInvoker
+    {
+        float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
+        {
+            if(!GridwiseGemm::CheckValidity(arg.a_grid_desc_m_k_,
+                                            arg.b_grid_desc_n_k_,
+                                            arg.ds_grid_desc_m_n_,
+                                            arg.e_grid_desc_m_n_,
+                                            arg.block_2_etile_map_))
+            {
+                throw std::runtime_error("wrong! GridwiseGemm has invalid setting");
+            }
+
+            const index_t grid_size =
+                arg.block_2_etile_map_.CalculateGridSize(arg.e_grid_desc_m_n_);
+
+            auto launch_kernel = [&](auto has_main_k_block_loop) {
+                constexpr bool has_main_loop = has_main_k_block_loop.value;
+
+                const auto kernel = kernel_gemm_multiple_d_xdl_cshuffle_lds_direct_load<
+                    GridwiseGemm,
+                    ADataType,
+                    BDataType,
+                    typename GridwiseGemm::DsGridPointer,
+                    EDataType,
+                    AElementwiseOperation,
+                    BElementwiseOperation,
+                    CDEElementwiseOperation,
+                    typename GridwiseGemm::AGridDesc_AK0_M_AK1,
+                    typename GridwiseGemm::BGridDesc_BK0_N_BK1,
+                    typename GridwiseGemm::DsGridDesc_MBlock_MPerBlock_NBlock_NPerBlock,
+                    typename GridwiseGemm::EGridDesc_MBlock_MPerBlock_NBlock_NPerBlock,
+                    typename GridwiseGemm::Block2ETileMap,
+                    has_main_loop>;
+
+                return launch_and_time_kernel(stream_config,
+                                              kernel,
+                                              dim3(grid_size),
+                                              dim3(BlockSize),
+                                              0,
+                                              arg.p_a_grid_,
+                                              arg.p_b_grid_,
+                                              //   arg.p_ds_grid_,
+                                              ck::Tuple<>{},
+                                              arg.p_e_grid_,
+                                              arg.a_element_op_,
+                                              arg.b_element_op_,
+                                              arg.cde_element_op_,
+                                              arg.a_grid_desc_ak0_m_ak1_,
+                                              arg.b_grid_desc_bk0_n_bk1_,
+                                              arg.ds_grid_desc_mblock_mperblock_nblock_nperblock_,
+                                              arg.e_grid_desc_mblock_mperblock_nblock_nperblock_,
+                                              arg.block_2_etile_map_);
+            };
+
+            const auto K = arg.a_grid_desc_m_k_.GetLength(I1);
+
+            if(GridwiseGemm::CalculateHasMainKBlockLoop(K))
+            {
+                return launch_kernel(integral_constant<bool, true>{});
+            }
+            else
+            {
+                return launch_kernel(integral_constant<bool, false>{});
+            }
+        }
+
+        float Run(const BaseArgument* p_arg,
+                  const StreamConfig& stream_config = StreamConfig{}) override
+        {
+            return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
+        }
+    };
+
+    static bool IsSupportedArgument(const Argument& arg)
+    {
+        if(!ck::is_xdl_supported())
+        {
+            return false;
+        }
+
+        if(!ck::is_lds_direct_load_supported())
+        {
+            return false;
+        }
+
+        // Check vector load/store.
+        {
+            using Row = ck::tensor_layout::gemm::RowMajor;
+            using Col = ck::tensor_layout::gemm::ColumnMajor;
+
+            // Check vector load of A.
+            if constexpr(is_same_v<ALayout, Row> && ABlockTransferSrcVectorDim == 2)
+            {
+                if(arg.KRaw_ % ABlockTransferScalarPerVector != 0)
+                {
+                    return false;
+                }
+            }
+            else if constexpr(is_same_v<ALayout, Col> && ABlockTransferSrcVectorDim == 1)
+            {
+                if(arg.MRaw_ % ABlockTransferScalarPerVector != 0)
+                {
+                    return false;
+                }
+            }
+            else
+            {
+                return false;
+            }
+
+            // Check vector load of B.
+            if constexpr(is_same_v<BLayout, Col> && BBlockTransferSrcVectorDim == 2)
+            {
+                if(arg.KRaw_ % BBlockTransferScalarPerVector != 0)
+                {
+                    return false;
+                }
+            }
+            else if constexpr(is_same_v<BLayout, Row> && BBlockTransferSrcVectorDim == 1)
+            {
+                if(arg.NRaw_ % BBlockTransferScalarPerVector != 0)
+                {
+                    return false;
+                }
+            }
+            else
+            {
+                return false;
+            }
+
+            // Check vector load of E.
+            // For now, only the RowMajor layout is supported.
+            if constexpr(is_same_v<ELayout, Row>)
+            {
+                if(arg.NRaw_ % CDEBlockTransferScalarPerVector_NPerBlock != 0)
+                {
+                    return false;
+                }
+            }
+            else
+            {
+                return false;
+            }
+        }
+
+        return GridwiseGemm::CheckValidity(arg.a_grid_desc_m_k_,
+                                           arg.b_grid_desc_n_k_,
+                                           arg.ds_grid_desc_m_n_,
+                                           arg.e_grid_desc_m_n_,
+                                           arg.block_2_etile_map_);
+    }
+
+    bool IsSupportedArgument(const BaseArgument* p_arg) override
+    {
+        return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
+    }
+
+    static auto MakeArgument(const void* p_a,
+                             const void* p_b,
+                             void* p_e,
+                             index_t MRaw,
+                             index_t NRaw,
+                             index_t KRaw,
+                             index_t StrideA,
+                             index_t StrideB,
+                             index_t StrideE,
+                             AElementwiseOperation a_element_op,
+                             BElementwiseOperation b_element_op,
+                             CDEElementwiseOperation cde_element_op)
+    {
+        using EmptyDsPointers = std::array<const void*, 0>;
+        using EmptyDsStrides  = std::array<ck::index_t, 0>;
+
+        return Argument{p_a,
+                        p_b,
+                        EmptyDsPointers{},
+                        p_e,
+                        MRaw,
+                        NRaw,
+                        KRaw,
+                        StrideA,
+                        StrideB,
+                        EmptyDsStrides{},
+                        StrideE,
+                        a_element_op,
+                        b_element_op,
+                        cde_element_op};
+    }
+
+    static auto MakeInvoker() { return Invoker{}; }
+
+    std::unique_ptr<BaseArgument>
+    MakeArgumentPointer(const void* p_a,
+                        const void* p_b,
+                        void* p_e,
+                        index_t MRaw,
+                        index_t NRaw,
+                        index_t KRaw,
+                        index_t StrideA,
+                        index_t StrideB,
+                        index_t StrideE,
+                        AElementwiseOperation a_element_op,
+                        BElementwiseOperation b_element_op,
+                        CDEElementwiseOperation cde_element_op) override
+    {
+        using EmptyDsPointers = std::array<const void*, 0>;
+        using EmptyDsStrides  = std::array<ck::index_t, 0>;
+
+        return std::make_unique<Argument>(p_a,
+                                          p_b,
+                                          EmptyDsPointers{},
+                                          p_e,
+                                          MRaw,
+                                          NRaw,
+                                          KRaw,
+                                          StrideA,
+                                          StrideB,
+                                          EmptyDsStrides{},
+                                          StrideE,
+                                          a_element_op,
+                                          b_element_op,
+                                          cde_element_op);
+    }
+
+    std::unique_ptr<BaseInvoker> MakeInvokerPointer() override
+    {
+        return std::make_unique<Invoker>(Invoker{});
+    }
+
+    std::string GetTypeString() const override
+    {
+        auto str = std::stringstream();
+
+        std::map<LoopScheduler, std::string> LoopSchedToString{
+            {LoopScheduler::Default, "Default"}, {LoopScheduler::Interwave, "Interwave"}};
+
+        std::map<PipelineVersion, std::string> PipelineVersionToString{
+            {PipelineVersion::v1, "v1"}, {PipelineVersion::v2, "v2"}, {PipelineVersion::v4, "v4"}};
+
+        // clang-format off
+        str << "DeviceGemm_Xdl_CShuffle_LdsDirectLoad"
+            << "<"
+            << BlockSize << ", "
+            << MPerBlock << ", "
+            << NPerBlock << ", "
+            << KPerBlock << ", "
+            << AK1 << ", "
+            << BK1 << ", "
+            << MPerXDL << ", "
+            << NPerXDL << ", "
+            << MXdlPerWave << ", "
+            << NXdlPerWave << ", "
+            << ABlockTransferScalarPerVector << ", "
+            << BBlockTransferScalarPerVector << ", "
+            << CShuffleMXdlPerWavePerShuffle << ", "
+            << CShuffleNXdlPerWavePerShuffle << ", "
+            << getGemmSpecializationString(GemmSpec)
+            << ">"
+            << " LoopScheduler: "
+            << LoopSchedToString[LoopSched] << ", "
+            << "PipelineVersion: "
+            << PipelineVersionToString[PipelineVer] << ", "
+            << "Prefetch: "
+            << NumGemmKPrefetchStage;
+        // clang-format on
+
+        return str.str();
+    }
+};
+
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck

include/ck/tensor_operation/gpu/device/impl/device_gemm_xdl_cshuffle_v2.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include <iostream>
+#include <sstream>
+
+#include "ck/utility/common_header.hpp"
+#include "ck/tensor_description/tensor_descriptor.hpp"
+#include "ck/tensor_description/tensor_descriptor_helper.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/device/device_gemm.hpp"
+#include "ck/tensor_operation/gpu/device/gemm_specialization.hpp"
+#include "ck/tensor_operation/gpu/grid/gridwise_gemm_xdl_cshuffle_v2.hpp"
+#include "ck/host_utility/device_prop.hpp"
+#include "ck/host_utility/kernel_launch.hpp"
+
+namespace ck {
+namespace tensor_operation {
+namespace device {
+
+// Note: inter-wave loop scheduler is rolled out to c-shuffle version first. Becuase non c-shuffle
+// version currently has compiler issues with register spill which further causes validation
+// failures.
+template <typename ALayout,
+          typename BLayout,
+          typename CLayout,
+          typename ADataType,
+          typename BDataType,
+          typename CDataType,
+          typename GemmAccDataType,
+          typename CShuffleDataType,
+          typename AElementwiseOperation,
+          typename BElementwiseOperation,
+          typename CElementwiseOperation,
+          GemmSpecialization GemmSpec,
+          index_t NumGemmKPrefetchStage,
+          index_t BlockSize,
+          index_t MPerBlock,
+          index_t NPerBlock,
+          index_t KPerBlock,
+          index_t AK1,
+          index_t BK1,
+          index_t MPerXDL,
+          index_t NPerXDL,
+          index_t MXdlPerWave,
+          index_t NXdlPerWave,
+          typename ABlockTransferThreadClusterLengths_AK0_M_AK1,
+          typename ABlockTransferThreadClusterArrangeOrder,
+          typename ABlockTransferSrcAccessOrder,
+          index_t ABlockTransferSrcVectorDim,
+          index_t ABlockTransferSrcScalarPerVector,
+          index_t ABlockTransferDstScalarPerVector_AK1,
+          bool ABlockLdsExtraM,
+          typename BBlockTransferThreadClusterLengths_BK0_N_BK1,
+          typename BBlockTransferThreadClusterArrangeOrder,
+          typename BBlockTransferSrcAccessOrder,
+          index_t BBlockTransferSrcVectorDim,
+          index_t BBlockTransferSrcScalarPerVector,
+          index_t BBlockTransferDstScalarPerVector_BK1,
+          bool BBlockLdsExtraN,
+          index_t CShuffleMXdlPerWavePerShuffle,
+          index_t CShuffleNXdlPerWavePerShuffle,
+          typename CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
+          index_t CShuffleBlockTransferScalarPerVector_NPerBlock,
+          LoopScheduler LoopSched     = make_default_loop_scheduler(),
+          PipelineVersion PipelineVer = PipelineVersion::v1,
+          typename ComputeTypeA       = CDataType,
+          typename ComputeTypeB       = ComputeTypeA>
+struct DeviceGemm_Xdl_CShuffleV2 : public DeviceGemm<ALayout,
+                                                     BLayout,
+                                                     CLayout,
+                                                     ADataType,
+                                                     BDataType,
+                                                     CDataType,
+                                                     AElementwiseOperation,
+                                                     BElementwiseOperation,
+                                                     CElementwiseOperation>
+{
+    using DeviceOp = DeviceGemm_Xdl_CShuffleV2;
+
+    static constexpr auto I0 = Number<0>{};
+    static constexpr auto I1 = Number<1>{};
+    static constexpr auto I2 = Number<2>{};
+
+    // GridwiseGemm
+    using GridwiseGemm = GridwiseGemm_xdl_cshuffle_v2<
+        ALayout,
+        BLayout,
+        CLayout,
+        ADataType,
+        BDataType,
+        GemmAccDataType,
+        CShuffleDataType,
+        CDataType,
+        AElementwiseOperation,
+        BElementwiseOperation,
+        CElementwiseOperation,
+        GemmSpec,
+        InMemoryDataOperationEnum::Set,
+        NumGemmKPrefetchStage,
+        BlockSize,
+        MPerBlock,
+        NPerBlock,
+        KPerBlock,
+        AK1,
+        BK1,
+        MPerXDL,
+        NPerXDL,
+        MXdlPerWave,
+        NXdlPerWave,
+        ABlockTransferThreadClusterLengths_AK0_M_AK1,
+        ABlockTransferThreadClusterArrangeOrder,
+        ABlockTransferSrcAccessOrder,
+        ABlockTransferSrcVectorDim,
+        ABlockTransferSrcScalarPerVector,
+        ABlockTransferDstScalarPerVector_AK1,
+        false,
+        ABlockLdsExtraM,
+        BBlockTransferThreadClusterLengths_BK0_N_BK1,
+        BBlockTransferThreadClusterArrangeOrder,
+        BBlockTransferSrcAccessOrder,
+        BBlockTransferSrcVectorDim,
+        BBlockTransferSrcScalarPerVector,
+        BBlockTransferDstScalarPerVector_BK1,
+        false,
+        BBlockLdsExtraN,
+        CShuffleMXdlPerWavePerShuffle,
+        CShuffleNXdlPerWavePerShuffle,
+        CShuffleBlockTransferClusterLengths_MBlock_MPerBlock_NBlock_NPerBlock,
+        CShuffleBlockTransferScalarPerVector_NPerBlock,
+        LoopSched,
+        PipelineVer,
+        ComputeTypeA,
+        ComputeTypeB>;
+
+    using Argument = typename GridwiseGemm::Argument;
+
+    // Invoker
+    struct Invoker : public BaseInvoker
+    {
+        float Run(const Argument& arg, const StreamConfig& stream_config = StreamConfig{})
+        {
+            if(stream_config.log_level_ > 0)
+            {
+                arg.Print();
+            }
+
+            if(!GridwiseGemm::CheckValidity(arg))
+            {
+                throw std::runtime_error("wrong! GridwiseGemm has invalid setting");
+            }
+
+            index_t gdx, gdy, gdz;
+            std::tie(gdx, gdy, gdz) = GridwiseGemm::CalculateGridSize(arg.M, arg.N);
+
+            float ave_time = 0;
+            const auto K   = GridwiseGemm::CalculateAK0(arg.K) * AK1;
+
+            if(GridwiseGemm::CalculateKBlockLoopTailNum(K) == 3)
+            {
+                const auto kernel = kernel_gemm_xdl_cshuffle_v2<GridwiseGemm, true>;
+                ave_time          = launch_and_time_kernel(
+                    stream_config, kernel, dim3(gdx, gdy, gdz), dim3(BlockSize), 0, arg);
+            }
+            else
+            {
+                const auto kernel = kernel_gemm_xdl_cshuffle_v2<GridwiseGemm, true, 2>;
+                ave_time          = launch_and_time_kernel(
+                    stream_config, kernel, dim3(gdx, gdy, gdz), dim3(BlockSize), 0, arg);
+            }
+
+            return ave_time;
+        }
+
+        // polymorphic
+        float Run(const BaseArgument* p_arg,
+                  const StreamConfig& stream_config = StreamConfig{}) override
+        {
+            return Run(*dynamic_cast<const Argument*>(p_arg), stream_config);
+        }
+    };
+
+    static constexpr bool IsValidCompilationParameter()
+    {
+        // TODO: properly implement this check
+        return true;
+    }
+
+    static bool IsSupportedArgument(const Argument& arg)
+    {
+        if(!ck::is_xdl_supported())
+        {
+            return false;
+        }
+
+        if((arg.K % AK1 != 0 || arg.K % BK1 != 0) && !(GemmSpec == GemmSpecialization::MKPadding ||
+                                                       GemmSpec == GemmSpecialization::NKPadding ||
+                                                       GemmSpec == GemmSpecialization::MNKPadding ||
+                                                       GemmSpec == GemmSpecialization::KPadding))
+        {
+            return false;
+        }
+
+        return GridwiseGemm::CheckValidity(arg);
+    }
+
+    // polymorphic
+    bool IsSupportedArgument(const BaseArgument* p_arg) override
+    {
+        return IsSupportedArgument(*dynamic_cast<const Argument*>(p_arg));
+    }
+
+    static auto MakeArgument(const ADataType* p_a,
+                             const BDataType* p_b,
+                             CDataType* p_c,
+                             index_t M,
+                             index_t N,
+                             index_t K,
+                             index_t StrideA,
+                             index_t StrideB,
+                             index_t StrideC,
+                             AElementwiseOperation,
+                             BElementwiseOperation,
+                             CElementwiseOperation)
+    {
+        return Argument{p_a, p_b, p_c, M, N, K, StrideA, StrideB, StrideC};
+    }
+
+    static auto MakeInvoker() { return Invoker{}; }
+
+    // polymorphic
+    std::unique_ptr<BaseArgument> MakeArgumentPointer(const void* p_a,
+                                                      const void* p_b,
+                                                      void* p_c,
+                                                      index_t M,
+                                                      index_t N,
+                                                      index_t K,
+                                                      index_t StrideA,
+                                                      index_t StrideB,
+                                                      index_t StrideC,
+                                                      AElementwiseOperation,
+                                                      BElementwiseOperation,
+                                                      CElementwiseOperation) override
+    {
+        return std::make_unique<Argument>(static_cast<const ADataType*>(p_a),
+                                          static_cast<const BDataType*>(p_b),
+                                          static_cast<CDataType*>(p_c),
+                                          M,
+                                          N,
+                                          K,
+                                          StrideA,
+                                          StrideB,
+                                          StrideC);
+    }
+
+    // polymorphic
+    std::unique_ptr<BaseInvoker> MakeInvokerPointer() override
+    {
+        return std::make_unique<Invoker>(Invoker{});
+    }
+
+    // polymorphic
+    std::string GetTypeString() const override
+    {
+        auto str = std::stringstream();
+
+        std::map<LoopScheduler, std::string> LoopSchedToString{
+            {LoopScheduler::Default, "Default"}, {LoopScheduler::Interwave, "Interwave"}};
+
+        std::map<PipelineVersion, std::string> PipelineVersionToString{{PipelineVersion::v1, "v1"},
+                                                                       {PipelineVersion::v2, "v2"}};
+
+        // clang-format off
+        str << "DeviceGemm_Xdl_CShuffleV2"
+            << "<"
+            << getGemmSpecializationString(GemmSpec) << ", "
+            << BlockSize << ", "
+            << MPerBlock << ", "
+            << NPerBlock << ", "
+            << KPerBlock << ", "
+            << AK1 << ", "
+            << BK1 << ", "
+            << MPerXDL << ", "
+            << NPerXDL << ", "
+            << MXdlPerWave << ", "
+            << NXdlPerWave << ", "
+            << ABlockTransferSrcScalarPerVector << ", "
+            << BBlockTransferSrcScalarPerVector << ", "
+            << CShuffleMXdlPerWavePerShuffle << ", "
+            << CShuffleNXdlPerWavePerShuffle
+            << ">"
+            << " LoopScheduler: "
+            << LoopSchedToString[LoopSched] << ", "
+            << "PipelineVersion: "
+            << PipelineVersionToString[PipelineVer];
+        // clang-format on
+
+        return str.str();
+    }
+};
+
+} // namespace device
+} // namespace tensor_operation
+} // namespace ck