Merge branch 'develop' into uif2-migraphx

example/62_convnd_activ/multi_AB/CMakeLists.txt

+list(APPEND gpu_list gfx908 gfx90a gfx940 gfx941 gfx942)
+set(target 0)
+foreach(gpu IN LISTS GPU_TARGETS)
+ if(gpu IN_LIST gpu_list AND target EQUAL 0)
+      add_custom_target(example_convnd_activ_multi_ab_xdl)
+      # ScaleAdd on A and B
+      add_example_executable(example_conv_fwd_xdl_scaleadd_ab_fp16 conv_fwd_xdl_scaleadd_ab_fp16.cpp)
+      add_example_dependencies(example_convnd_activ_multi_ab_xdl example_conv_fwd_xdl_scaleadd_ab_fp16)
+      add_example_executable(example_conv_fwd_xdl_scaleadd_ab_fp32 conv_fwd_xdl_scaleadd_ab_fp32.cpp)
+      add_example_dependencies(example_convnd_activ_multi_ab_xdl example_conv_fwd_xdl_scaleadd_ab_fp32)
+      add_example_executable(example_conv_fwd_xdl_scaleadd_ab_bf16 conv_fwd_xdl_scaleadd_ab_bf16.cpp)
+      add_example_dependencies(example_convnd_activ_multi_ab_xdl example_conv_fwd_xdl_scaleadd_ab_bf16)
+      add_example_executable(example_conv_fwd_xdl_scaleadd_ab_int8 conv_fwd_xdl_scaleadd_ab_int8.cpp)
+      add_example_dependencies(example_convnd_activ_multi_ab_xdl example_conv_fwd_xdl_scaleadd_ab_int8)
+   set(target 1)
+ endif()
+endforeach()

example/62_convnd_activ/multi_AB/conv_fwd_xdl_scaleadd_ab_bf16.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "convnd_fwd_activ_multi_ab_common.hpp"
+
+using DataType    = ck::bhalf_t;
+using AccDataType = float;
+using InDataType  = DataType;
+using WeiDataType = DataType;
+using OutDataType = DataType;
+using ADataTypes  = ck::Tuple<DataType, DataType>;
+using BDataTypes  = ck::Tuple<DataType, DataType>;
+
+using InElementOp  = ck::tensor_operation::element_wise::ScaleAdd;
+using WeiElementOp = ck::tensor_operation::element_wise::ScaleAdd;
+
+using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDMultiABFwdInstance<DataType,
+                                                                               AccDataType,
+                                                                               ADataTypes,
+                                                                               BDataTypes,
+                                                                               InElementOp,
+                                                                               WeiElementOp>;
+
+#include "../run_convnd_activ_example.inc"
+
+int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }

example/62_convnd_activ/multi_AB/conv_fwd_xdl_scaleadd_ab_fp16.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "convnd_fwd_activ_multi_ab_common.hpp"
+
+using DataType    = ck::half_t;
+using AccDataType = float;
+using InDataType  = DataType;
+using WeiDataType = DataType;
+using OutDataType = DataType;
+using ADataTypes  = ck::Tuple<DataType, DataType>;
+using BDataTypes  = ck::Tuple<DataType, DataType>;
+
+using InElementOp  = ck::tensor_operation::element_wise::ScaleAdd;
+using WeiElementOp = ck::tensor_operation::element_wise::ScaleAdd;
+
+using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDMultiABFwdInstance<DataType,
+                                                                               AccDataType,
+                                                                               ADataTypes,
+                                                                               BDataTypes,
+                                                                               InElementOp,
+                                                                               WeiElementOp>;
+
+#include "../run_convnd_activ_example.inc"
+
+int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }

example/62_convnd_activ/multi_AB/conv_fwd_xdl_scaleadd_ab_fp32.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "convnd_fwd_activ_multi_ab_common.hpp"
+
+using DataType    = float;
+using AccDataType = float;
+using InDataType  = DataType;
+using WeiDataType = DataType;
+using OutDataType = DataType;
+using ADataTypes  = ck::Tuple<DataType, DataType>;
+using BDataTypes  = ck::Tuple<DataType, DataType>;
+
+using InElementOp  = ck::tensor_operation::element_wise::ScaleAdd;
+using WeiElementOp = ck::tensor_operation::element_wise::ScaleAdd;
+
+using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDMultiABFwdInstance<DataType,
+                                                                               AccDataType,
+                                                                               ADataTypes,
+                                                                               BDataTypes,
+                                                                               InElementOp,
+                                                                               WeiElementOp>;
+
+#include "../run_convnd_activ_example.inc"
+
+int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }

example/62_convnd_activ/multi_AB/conv_fwd_xdl_scaleadd_ab_int8.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "convnd_fwd_activ_multi_ab_common.hpp"
+
+using DataType    = int8_t;
+using AccDataType = int32_t;
+using InDataType  = DataType;
+using WeiDataType = DataType;
+using OutDataType = DataType;
+using ADataTypes  = ck::Tuple<DataType, DataType>;
+using BDataTypes  = ck::Tuple<DataType, DataType>;
+
+using InElementOp  = ck::tensor_operation::element_wise::ScaleAdd;
+using WeiElementOp = ck::tensor_operation::element_wise::ScaleAdd;
+
+using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDMultiABFwdInstance<DataType,
+                                                                               AccDataType,
+                                                                               ADataTypes,
+                                                                               BDataTypes,
+                                                                               InElementOp,
+                                                                               WeiElementOp>;
+
+#include "../run_convnd_activ_example.inc"
+
+int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }

example/62_convnd_activ/multi_AB/convnd_fwd_activ_multi_ab_common.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#include <cstdlib>
+#include <iostream>
+#include <numeric>
+#include <type_traits>
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_fwd_multiple_abd_xdl_cshuffle.hpp"
+
+#include "ck/library/utility/algorithm.hpp"
+#include "ck/library/utility/check_err.hpp"
+#include "ck/library/utility/device_memory.hpp"
+#include "ck/library/utility/host_tensor.hpp"
+#include "ck/library/utility/host_tensor_generator.hpp"
+#include "ck/library/utility/convolution_parameter.hpp"
+#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
+#include "ck/library/reference_tensor_operation/cpu/reference_conv_fwd.hpp"
+#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
+
+constexpr ck::index_t NDimSpatial = 3;
+
+template <ck::index_t... Is>
+using S = ck::Sequence<Is...>;
+
+using InLayout  = ck::tensor_layout::convolution::GNDHWC;
+using WeiLayout = ck::tensor_layout::convolution::GKZYXC;
+using OutLayout = ck::tensor_layout::convolution::GNDHWK;
+
+using OutElementOp = ck::tensor_operation::element_wise::PassThrough;
+
+static constexpr auto ConvSpec =
+    ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
+
+static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
+
+template <typename DataType,
+          typename AccDataType,
+          typename InDataTypes,
+          typename WeiDataTypes,
+          typename InElementOp,
+          typename WeiElementOp>
+using DeviceGroupedConvNDMultiABFwdInstance =
+    ck::tensor_operation::device::DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<
+        NDimSpatial,
+        InLayout,
+        WeiLayout,
+        ck::Tuple<>,
+        OutLayout,
+        InDataTypes,
+        WeiDataTypes,
+        AccDataType,
+        DataType,
+        ck::Tuple<>,
+        DataType,
+        InElementOp,
+        WeiElementOp,
+        OutElementOp,
+        ConvSpec,    // ConvForwardSpecialization
+        GemmSpec,    // GemmSpecialization
+        1,           //
+        256,         // BlockSize
+        128,         // MPerBlock
+        256,         // NPerBlock
+        32,          // KPerBlock
+        8,           // AK1
+        8,           // BK1
+        32,          // MPerXdl
+        32,          // NPerXdl
+        2,           // MXdlPerWave
+        4,           // NXdlPerWave
+        S<4, 64, 1>, // ABlockTransferThreadClusterLengths_AK0_M_AK1
+        S<1, 0, 2>,  // ABlockTransferThreadClusterArrangeOrder
+        S<1, 0, 2>,  // ABlockTransferSrcAccessOrder
+        2,           // ABlockTransferSrcVectorDim
+        8,           // ABlockTransferSrcScalarPerVector
+        8,           // ABlockTransferDstScalarPerVector_AK1
+        1,           // ABlockLdsExtraM
+        S<4, 64, 1>, // BBlockTransferThreadClusterLengths_BK0_N_BK1
+        S<1, 0, 2>,  // BBlockTransferThreadClusterArrangeOrder
+        S<1, 0, 2>,  // BBlockTransferSrcAccessOrder
+        2,           // BBlockTransferSrcVectorDim
+        8,           // BBlockTransferSrcScalarPerVector
+        8,           // BBlockTransferDstScalarPerVector_BK1
+        1,           // BBlockLdsExtraN
+        1,
+        1,
+        S<1, 32, 1, 8>,
+        8>;
+
+namespace {
+template <ck::index_t NDimSpatial,
+          typename InDataType,
+          typename WeiDataType,
+          typename OutDataType,
+          typename InElementOp,
+          typename WeiElementOp,
+          typename OutElementOp,
+          typename DeviceConvNDFwdInstance>
+bool run_grouped_conv(bool do_verification,
+                      int init_method,
+                      bool time_kernel,
+                      const ck::utils::conv::ConvParam& conv_param,
+                      const HostTensorDescriptor& in_g_n_c_wis_desc,
+                      const HostTensorDescriptor& wei_g_k_c_xs_desc,
+                      const HostTensorDescriptor& out_g_n_k_wos_desc,
+                      const InElementOp& in_element_op,
+                      const WeiElementOp& wei_element_op,
+                      const OutElementOp& out_element_op)
+{
+    constexpr ck::index_t NumAs = 2;
+    constexpr ck::index_t NumBs = 2;
+    Tensor<InDataType> in(in_g_n_c_wis_desc);
+    Tensor<InDataType> in_bias(in_g_n_c_wis_desc);
+    Tensor<WeiDataType> wei(wei_g_k_c_xs_desc);
+    Tensor<WeiDataType> wei_bias(wei_g_k_c_xs_desc);
+    Tensor<OutDataType> out_host(out_g_n_k_wos_desc);
+    Tensor<OutDataType> out_device(out_g_n_k_wos_desc);
+
+    std::cout << "in: " << in.mDesc << std::endl;
+    std::cout << "wei: " << wei.mDesc << std::endl;
+    std::cout << "out: " << out_host.mDesc << std::endl;
+
+    switch(init_method)
+    {
+    case 0: break;
+    case 1:
+        in.GenerateTensorValue(GeneratorTensor_2<InDataType>{-2, 2});
+        in_bias.GenerateTensorValue(GeneratorTensor_2<InDataType>{-2, 2});
+        wei.GenerateTensorValue(GeneratorTensor_2<WeiDataType>{-2, 2});
+        wei_bias.GenerateTensorValue(GeneratorTensor_2<WeiDataType>{-2, 2});
+        break;
+    default:
+        in.GenerateTensorValue(GeneratorTensor_3<InDataType>{-1.0, 1.0});
+        in_bias.GenerateTensorValue(GeneratorTensor_3<InDataType>{-1.0, 1.0});
+        wei.GenerateTensorValue(GeneratorTensor_3<WeiDataType>{-0.05, 0.05});
+        wei_bias.GenerateTensorValue(GeneratorTensor_3<WeiDataType>{-1.0, 1.0});
+    }
+
+    DeviceMem in_device_buf(sizeof(InDataType) * in.mDesc.GetElementSpaceSize());
+    DeviceMem in_bias_device_buf(sizeof(InDataType) * in_bias.mDesc.GetElementSpaceSize());
+    DeviceMem wei_device_buf(sizeof(WeiDataType) * wei.mDesc.GetElementSpaceSize());
+    DeviceMem wei_bias_device_buf(sizeof(WeiDataType) * wei_bias.mDesc.GetElementSpaceSize());
+    DeviceMem out_device_buf(sizeof(OutDataType) * out_device.mDesc.GetElementSpaceSize());
+
+    in_device_buf.ToDevice(in.mData.data());
+    in_bias_device_buf.ToDevice(in_bias.mData.data());
+    wei_device_buf.ToDevice(wei.mData.data());
+    wei_bias_device_buf.ToDevice(wei_bias.mData.data());
+
+    std::array<ck::index_t, NDimSpatial + 3> a_g_n_c_wis_lengths{};
+    std::array<ck::index_t, NDimSpatial + 3> a_g_n_c_wis_strides{};
+    std::array<ck::index_t, NDimSpatial + 3> b_g_k_c_xs_lengths{};
+    std::array<ck::index_t, NDimSpatial + 3> b_g_k_c_xs_strides{};
+    std::array<ck::index_t, NDimSpatial + 3> e_g_n_k_wos_lengths{};
+    std::array<ck::index_t, NDimSpatial + 3> e_g_n_k_wos_strides{};
+    std::array<ck::index_t, NDimSpatial> conv_filter_strides{};
+    std::array<ck::index_t, NDimSpatial> conv_filter_dilations{};
+    std::array<ck::index_t, NDimSpatial> input_left_pads{};
+    std::array<ck::index_t, NDimSpatial> input_right_pads{};
+
+    auto copy = [](const auto& x, auto& y) { ck::ranges::copy(x, y.begin()); };
+
+    copy(in_g_n_c_wis_desc.GetLengths(), a_g_n_c_wis_lengths);
+    copy(in_g_n_c_wis_desc.GetStrides(), a_g_n_c_wis_strides);
+    copy(wei_g_k_c_xs_desc.GetLengths(), b_g_k_c_xs_lengths);
+    copy(wei_g_k_c_xs_desc.GetStrides(), b_g_k_c_xs_strides);
+    copy(out_g_n_k_wos_desc.GetLengths(), e_g_n_k_wos_lengths);
+    copy(out_g_n_k_wos_desc.GetStrides(), e_g_n_k_wos_strides);
+    copy(conv_param.conv_filter_strides_, conv_filter_strides);
+    copy(conv_param.conv_filter_dilations_, conv_filter_dilations);
+    copy(conv_param.input_left_pads_, input_left_pads);
+    copy(conv_param.input_right_pads_, input_right_pads);
+
+    std::array<const void*, NumAs> as{in_device_buf.GetDeviceBuffer(),
+                                      in_bias_device_buf.GetDeviceBuffer()};
+    std::array<const void*, NumBs> bs{wei_device_buf.GetDeviceBuffer(),
+                                      wei_bias_device_buf.GetDeviceBuffer()};
+    std::array<const void*, 0> ds{};
+
+    // do Conv
+    auto conv     = DeviceConvNDFwdInstance{};
+    auto invoker  = conv.MakeInvoker();
+    auto argument = conv.MakeArgument(as,
+                                      bs,
+                                      ds,
+                                      out_device_buf.GetDeviceBuffer(),
+                                      a_g_n_c_wis_lengths,
+                                      a_g_n_c_wis_strides,
+                                      b_g_k_c_xs_lengths,
+                                      b_g_k_c_xs_strides,
+                                      {},
+                                      {},
+                                      e_g_n_k_wos_lengths,
+                                      e_g_n_k_wos_strides,
+                                      conv_filter_strides,
+                                      conv_filter_dilations,
+                                      input_left_pads,
+                                      input_right_pads,
+                                      in_element_op,
+                                      wei_element_op,
+                                      out_element_op);
+
+    if(!conv.IsSupportedArgument(argument))
+    {
+        throw std::runtime_error(
+            "wrong! device_conv with the specified compilation parameters does "
+            "not support this Conv problem");
+    }
+
+    float avg_time = invoker.Run(argument, StreamConfig{nullptr, time_kernel});
+
+    std::size_t flop = conv_param.GetFlops() +
+                       2 * conv_param.GetOutputByte<InDataType>() / sizeof(InDataType) +
+                       2 * conv_param.GetOutputByte<WeiDataType>() / sizeof(WeiDataType);
+    std::size_t num_btype = conv_param.GetByte<InDataType, WeiDataType, OutDataType>() +
+                            conv_param.GetInputByte<InDataType>() +
+                            conv_param.GetWeightByte<WeiDataType>();
+
+    float tflops     = static_cast<float>(flop) / 1.E9 / avg_time;
+    float gb_per_sec = num_btype / 1.E6 / avg_time;
+    std::cout << "Perf: " << avg_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s, "
+              << conv.GetTypeString() << std::endl;
+
+    if(do_verification)
+    {
+        const std::array<Tensor<InDataType>, NumAs - 1> elementwise_a_tensors  = {in_bias};
+        const std::array<Tensor<WeiDataType>, NumBs - 1> elementwise_b_tensors = {wei_bias};
+        auto ref_conv = ck::tensor_operation::host::ReferenceConvFwd<NDimSpatial,
+                                                                     InDataType,
+                                                                     WeiDataType,
+                                                                     OutDataType,
+                                                                     InElementOp,
+                                                                     WeiElementOp,
+                                                                     OutElementOp,
+                                                                     NumAs - 1,
+                                                                     NumBs - 1>();
+
+        auto ref_invoker  = ref_conv.MakeInvoker();
+        auto ref_argument = ref_conv.MakeArgument(in,
+                                                  wei,
+                                                  out_host,
+                                                  conv_param.conv_filter_strides_,
+                                                  conv_param.conv_filter_dilations_,
+                                                  conv_param.input_left_pads_,
+                                                  conv_param.input_right_pads_,
+                                                  in_element_op,
+                                                  wei_element_op,
+                                                  out_element_op,
+                                                  elementwise_a_tensors,
+                                                  elementwise_b_tensors);
+
+        ref_invoker.Run(ref_argument);
+
+        out_device_buf.FromDevice(out_device.mData.data());
+
+        return ck::utils::check_err(out_device, out_host, "Error: incorrect results!");
+    }
+
+    return true;
+}
+
+} // namespace

example/62_convnd_activ/run_convnd_activ_example.inc

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+void print_helper_msg()
+{
+    std::cout << "arg1: verification (0=no, 1=yes)\n"
+              << "arg2: initialization (0=no init, 1=integer value, 2=decimal value)\n"
+              << "arg3: time kernel (0=no, 1=yes)\n"
+              << ck::utils::conv::get_conv_param_parser_helper_msg() << std::endl;
+}
+
+bool run_convnd_example(int argc, char* argv[])
+{
+    print_helper_msg();
+
+    bool do_verification = true;
+    // Use floats for SoftRelu by default to avoid overflow after e^x.
+    int init_method =
+        std::is_same_v<OutElementOp, ck::tensor_operation::element_wise::SoftRelu> ? 2 : 1;
+    bool time_kernel = false;
+
+    // Following shapes are selected to avoid overflow. Expect inf in case of
+    // size increase for some elementwise ops.
+    ck::utils::conv::ConvParam conv_param{
+        3, 2, 16, 128, 8, {3, 3, 3}, {17, 17, 17}, {2, 2, 2}, {1, 1, 1}, {1, 1, 1}, {1, 1, 1}};
+
+    if(argc == 1)
+    {
+        // use default
+    }
+    else if(argc == 4)
+    {
+        do_verification = std::stoi(argv[1]);
+        init_method     = std::stoi(argv[2]);
+        time_kernel     = std::stoi(argv[3]);
+    }
+    else
+    {
+        do_verification                   = std::stoi(argv[1]);
+        init_method                       = std::stoi(argv[2]);
+        time_kernel                       = std::stoi(argv[3]);
+        const ck::index_t num_dim_spatial = std::stoi(argv[4]);
+
+        conv_param = ck::utils::conv::parse_conv_param(num_dim_spatial, 5, argv);
+    }
+
+    const auto in_element_op  = InElementOp{};
+    const auto wei_element_op = WeiElementOp{};
+    const auto out_element_op = OutElementOp{};
+
+    const auto run = [&]() {
+        const auto in_g_n_c_wis_desc =
+            ck::utils::conv::make_input_host_tensor_descriptor_g_n_c_wis_packed<InLayout>(
+                conv_param);
+
+        const auto wei_g_k_c_xs_desc =
+            ck::utils::conv::make_weight_host_tensor_descriptor_g_k_c_xs_packed<WeiLayout>(
+                conv_param);
+
+        const auto out_g_n_k_wos_desc =
+            ck::utils::conv::make_output_host_tensor_descriptor_g_n_k_wos_packed<OutLayout>(
+                conv_param);
+
+        return run_grouped_conv<NDimSpatial,
+                                InDataType,
+                                WeiDataType,
+                                OutDataType,
+                                InElementOp,
+                                WeiElementOp,
+                                OutElementOp,
+                                DeviceGroupedConvNDActivInstance>(do_verification,
+                                                                  init_method,
+                                                                  time_kernel,
+                                                                  conv_param,
+                                                                  in_g_n_c_wis_desc,
+                                                                  wei_g_k_c_xs_desc,
+                                                                  out_g_n_k_wos_desc,
+                                                                  in_element_op,
+                                                                  wei_element_op,
+                                                                  out_element_op);
+    };
+
+    if(conv_param.num_dim_spatial_ == 3)
+    {
+        return run();
+    }
+
+    return false;
+}

example/62_convnd_activ/unary/CMakeLists.txt

+list(APPEND gpu_list gfx908 gfx90a gfx940 gfx941 gfx942)
+set(target 0)
+foreach(gpu IN LISTS GPU_TARGETS)
+ if(gpu IN_LIST gpu_list AND target EQUAL 0)
+      add_custom_target(example_convnd_activ_unary_xdl)
+      # Sigmoid
+      add_example_executable(example_convnd_fwd_xdl_sigmoid_fp16 convnd_fwd_xdl_sigmoid_fp16.cpp)
+      add_example_dependencies(example_convnd_activ_unary_xdl example_convnd_fwd_xdl_sigmoid_fp16)
+      # Tanh
+      add_example_executable(example_convnd_fwd_xdl_tanh_fp16 convnd_fwd_xdl_tanh_fp16.cpp)
+      add_example_dependencies(example_convnd_activ_unary_xdl example_convnd_fwd_xdl_tanh_fp16)
+      # Relu
+      add_example_executable(example_convnd_fwd_xdl_relu_fp16 convnd_fwd_xdl_relu_fp16.cpp)
+      add_example_dependencies(example_convnd_activ_unary_xdl example_convnd_fwd_xdl_relu_fp16)
+      # SoftRelu
+      add_example_executable(example_convnd_fwd_xdl_softrelu_fp16 convnd_fwd_xdl_softrelu_fp16.cpp)
+      add_example_dependencies(example_convnd_activ_unary_xdl example_convnd_fwd_xdl_softrelu_fp16)
+      # Abs
+      add_example_executable(example_convnd_fwd_xdl_abs_fp16 convnd_fwd_xdl_abs_fp16.cpp)
+      add_example_dependencies(example_convnd_activ_unary_xdl example_convnd_fwd_xdl_abs_fp16)
+      # Pow
+      add_example_executable(example_convnd_fwd_xdl_pow_fp16 convnd_fwd_xdl_pow_fp16.cpp)
+      add_example_dependencies(example_convnd_activ_unary_xdl example_convnd_fwd_xdl_pow_fp16)
+      # Clipped Relu
+      add_example_executable(example_convnd_fwd_xdl_clippedrelu_fp16 convnd_fwd_xdl_clippedrelu_fp16.cpp)
+      add_example_dependencies(example_convnd_activ_unary_xdl example_convnd_fwd_xdl_clippedrelu_fp16)
+      # Leaky Relu
+      add_example_executable(example_convnd_fwd_xdl_leakyrelu_fp16 convnd_fwd_xdl_leakyrelu_fp16.cpp)
+      add_example_dependencies(example_convnd_activ_unary_xdl example_convnd_fwd_xdl_leakyrelu_fp16)
+      # Elu
+      add_example_executable(example_convnd_fwd_xdl_elu_fp16 convnd_fwd_xdl_elu_fp16.cpp)
+      add_example_dependencies(example_convnd_activ_unary_xdl example_convnd_fwd_xdl_elu_fp16)
+   set(target 1)
+ endif()
+endforeach()

example/62_convnd_activ/unary/convnd_fwd_activ_unary_common.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include <cstdlib>
+#include <iostream>
+#include <numeric>
+#include <type_traits>
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/tensor_layout.hpp"
+#include "ck/tensor_operation/gpu/element/element_wise_operation.hpp"
+#include "ck/tensor_operation/gpu/device/impl/device_grouped_conv_fwd_multiple_abd_xdl_cshuffle.hpp"
+
+#include "ck/library/utility/algorithm.hpp"
+#include "ck/library/utility/check_err.hpp"
+#include "ck/library/utility/device_memory.hpp"
+#include "ck/library/utility/host_tensor.hpp"
+#include "ck/library/utility/host_tensor_generator.hpp"
+#include "ck/library/utility/convolution_parameter.hpp"
+#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
+#include "ck/library/reference_tensor_operation/cpu/reference_conv_fwd.hpp"
+#include "ck/library/utility/convolution_host_tensor_descriptor_helper.hpp"
+
+constexpr ck::index_t NDimSpatial = 3;
+using InDataType                  = ck::half_t;
+using WeiDataType                 = ck::half_t;
+using AccDataType                 = float;
+using CShuffleDataType            = ck::half_t;
+using OutDataType                 = ck::half_t;
+
+template <ck::index_t... Is>
+using S = ck::Sequence<Is...>;
+
+using InLayout  = ck::tensor_layout::convolution::GNDHWC;
+using WeiLayout = ck::tensor_layout::convolution::GKZYXC;
+using OutLayout = ck::tensor_layout::convolution::GNDHWK;
+
+using InElementOp  = ck::tensor_operation::element_wise::PassThrough;
+using WeiElementOp = ck::tensor_operation::element_wise::PassThrough;
+
+static constexpr auto ConvSpec =
+    ck::tensor_operation::device::ConvolutionForwardSpecialization::Default;
+
+static constexpr auto GemmSpec = ck::tensor_operation::device::GemmSpecialization::MNKPadding;
+
+template <typename OutElementOp>
+using DeviceGroupedConvNDFwdInstance =
+    ck::tensor_operation::device::DeviceGroupedConvFwdMultipleABD_Xdl_CShuffle<
+        NDimSpatial,
+        InLayout,
+        WeiLayout,
+        ck::Tuple<>,
+        OutLayout,
+        InDataType,
+        WeiDataType,
+        AccDataType,
+        CShuffleDataType,
+        ck::Tuple<>,
+        OutDataType,
+        InElementOp,
+        WeiElementOp,
+        OutElementOp,
+        ConvSpec,    // ConvForwardSpecialization
+        GemmSpec,    // GemmSpecialization
+        1,           //
+        256,         // BlockSize
+        128,         // MPerBlock
+        256,         // NPerBlock
+        32,          // KPerBlock
+        8,           // AK1
+        8,           // BK1
+        32,          // MPerXdl
+        32,          // NPerXdl
+        2,           // MXdlPerWave
+        4,           // NXdlPerWave
+        S<4, 64, 1>, // ABlockTransferThreadClusterLengths_AK0_M_AK1
+        S<1, 0, 2>,  // ABlockTransferThreadClusterArrangeOrder
+        S<1, 0, 2>,  // ABlockTransferSrcAccessOrder
+        2,           // ABlockTransferSrcVectorDim
+        8,           // ABlockTransferSrcScalarPerVector
+        8,           // ABlockTransferDstScalarPerVector_AK1
+        1,           // ABlockLdsExtraM
+        S<4, 64, 1>, // BBlockTransferThreadClusterLengths_BK0_N_BK1
+        S<1, 0, 2>,  // BBlockTransferThreadClusterArrangeOrder
+        S<1, 0, 2>,  // BBlockTransferSrcAccessOrder
+        2,           // BBlockTransferSrcVectorDim
+        8,           // BBlockTransferSrcScalarPerVector
+        8,           // BBlockTransferDstScalarPerVector_BK1
+        1,           // BBlockLdsExtraN
+        1,
+        1,
+        S<1, 32, 1, 8>,
+        8>;
+
+template <ck::index_t NDimSpatial,
+          typename InDataType,
+          typename WeiDataType,
+          typename OutDataType,
+          typename InElementOp,
+          typename WeiElementOp,
+          typename OutElementOp,
+          typename DeviceConvNDFwdInstance>
+bool run_grouped_conv(bool do_verification,
+                      int init_method,
+                      bool time_kernel,
+                      const ck::utils::conv::ConvParam& conv_param,
+                      const HostTensorDescriptor& in_g_n_c_wis_desc,
+                      const HostTensorDescriptor& wei_g_k_c_xs_desc,
+                      const HostTensorDescriptor& out_g_n_k_wos_desc,
+                      const InElementOp& in_element_op,
+                      const WeiElementOp& wei_element_op,
+                      const OutElementOp& out_element_op)
+{
+    Tensor<InDataType> in(in_g_n_c_wis_desc);
+    Tensor<WeiDataType> wei(wei_g_k_c_xs_desc);
+    Tensor<OutDataType> out_host(out_g_n_k_wos_desc);
+    Tensor<OutDataType> out_device(out_g_n_k_wos_desc);
+
+    std::cout << "in: " << in.mDesc << std::endl;
+    std::cout << "wei: " << wei.mDesc << std::endl;
+    std::cout << "out: " << out_host.mDesc << std::endl;
+
+    switch(init_method)
+    {
+    case 0: break;
+    case 1:
+        in.GenerateTensorValue(GeneratorTensor_2<InDataType>{-2, 2});
+        wei.GenerateTensorValue(GeneratorTensor_2<WeiDataType>{-2, 2});
+        break;
+    default:
+        in.GenerateTensorValue(GeneratorTensor_3<InDataType>{-1.0, 1.0});
+        wei.GenerateTensorValue(GeneratorTensor_3<WeiDataType>{-0.05, 0.05});
+    }
+
+    DeviceMem in_device_buf(sizeof(InDataType) * in.mDesc.GetElementSpaceSize());
+    DeviceMem wei_device_buf(sizeof(WeiDataType) * wei.mDesc.GetElementSpaceSize());
+    DeviceMem out_device_buf(sizeof(OutDataType) * out_device.mDesc.GetElementSpaceSize());
+
+    in_device_buf.ToDevice(in.mData.data());
+    wei_device_buf.ToDevice(wei.mData.data());
+
+    std::array<ck::index_t, NDimSpatial + 3> a_g_n_c_wis_lengths{};
+    std::array<ck::index_t, NDimSpatial + 3> a_g_n_c_wis_strides{};
+    std::array<ck::index_t, NDimSpatial + 3> b_g_k_c_xs_lengths{};
+    std::array<ck::index_t, NDimSpatial + 3> b_g_k_c_xs_strides{};
+    std::array<ck::index_t, NDimSpatial + 3> e_g_n_k_wos_lengths{};
+    std::array<ck::index_t, NDimSpatial + 3> e_g_n_k_wos_strides{};
+    std::array<ck::index_t, NDimSpatial> conv_filter_strides{};
+    std::array<ck::index_t, NDimSpatial> conv_filter_dilations{};
+    std::array<ck::index_t, NDimSpatial> input_left_pads{};
+    std::array<ck::index_t, NDimSpatial> input_right_pads{};
+
+    auto copy = [](const auto& x, auto& y) { ck::ranges::copy(x, y.begin()); };
+
+    copy(in_g_n_c_wis_desc.GetLengths(), a_g_n_c_wis_lengths);
+    copy(in_g_n_c_wis_desc.GetStrides(), a_g_n_c_wis_strides);
+    copy(wei_g_k_c_xs_desc.GetLengths(), b_g_k_c_xs_lengths);
+    copy(wei_g_k_c_xs_desc.GetStrides(), b_g_k_c_xs_strides);
+    copy(out_g_n_k_wos_desc.GetLengths(), e_g_n_k_wos_lengths);
+    copy(out_g_n_k_wos_desc.GetStrides(), e_g_n_k_wos_strides);
+    copy(conv_param.conv_filter_strides_, conv_filter_strides);
+    copy(conv_param.conv_filter_dilations_, conv_filter_dilations);
+    copy(conv_param.input_left_pads_, input_left_pads);
+    copy(conv_param.input_right_pads_, input_right_pads);
+
+    // do Conv
+    auto conv     = DeviceConvNDFwdInstance{};
+    auto invoker  = conv.MakeInvoker();
+    auto argument = conv.MakeArgument(in_device_buf.GetDeviceBuffer(),
+                                      wei_device_buf.GetDeviceBuffer(),
+                                      std::array<const void*, 0>{},
+                                      out_device_buf.GetDeviceBuffer(),
+                                      a_g_n_c_wis_lengths,
+                                      a_g_n_c_wis_strides,
+                                      b_g_k_c_xs_lengths,
+                                      b_g_k_c_xs_strides,
+                                      std::array<std::array<ck::index_t, NDimSpatial + 3>, 0>{{}},
+                                      std::array<std::array<ck::index_t, NDimSpatial + 3>, 0>{{}},
+                                      e_g_n_k_wos_lengths,
+                                      e_g_n_k_wos_strides,
+                                      conv_filter_strides,
+                                      conv_filter_dilations,
+                                      input_left_pads,
+                                      input_right_pads,
+                                      in_element_op,
+                                      wei_element_op,
+                                      out_element_op);
+
+    if(!conv.IsSupportedArgument(argument))
+    {
+        throw std::runtime_error("The device op with the specified compilation parameters does "
+                                 "not support this convolution problem.");
+    }
+
+    float avg_time = invoker.Run(argument, StreamConfig{nullptr, time_kernel});
+
+    std::size_t flop      = conv_param.GetFlops();
+    std::size_t num_btype = conv_param.GetByte<InDataType, WeiDataType, OutDataType>();
+
+    float tflops     = static_cast<float>(flop) / 1.E9 / avg_time;
+    float gb_per_sec = num_btype / 1.E6 / avg_time;
+    std::cout << "Perf: " << avg_time << " ms, " << tflops << " TFlops, " << gb_per_sec << " GB/s, "
+              << conv.GetTypeString() << std::endl;
+
+    if(do_verification)
+    {
+        auto ref_conv = ck::tensor_operation::host::ReferenceConvFwd<NDimSpatial,
+                                                                     InDataType,
+                                                                     WeiDataType,
+                                                                     OutDataType,
+                                                                     InElementOp,
+                                                                     WeiElementOp,
+                                                                     OutElementOp>();
+
+        auto ref_invoker  = ref_conv.MakeInvoker();
+        auto ref_argument = ref_conv.MakeArgument(in,
+                                                  wei,
+                                                  out_host,
+                                                  conv_param.conv_filter_strides_,
+                                                  conv_param.conv_filter_dilations_,
+                                                  conv_param.input_left_pads_,
+                                                  conv_param.input_right_pads_,
+                                                  in_element_op,
+                                                  wei_element_op,
+                                                  out_element_op);
+
+        ref_invoker.Run(ref_argument);
+
+        out_device_buf.FromDevice(out_device.mData.data());
+
+        return ck::utils::check_err(out_device, out_host, "Error: incorrect results!");
+    }
+
+    return true;
+}

example/62_convnd_activ/unary/convnd_fwd_xdl_abs_fp16.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "convnd_fwd_activ_unary_common.hpp"
+
+using OutElementOp = ck::tensor_operation::element_wise::UnaryAbs;
+
+using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDFwdInstance<OutElementOp>;
+#include "../run_convnd_activ_example.inc"
+
+int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }

example/62_convnd_activ/unary/convnd_fwd_xdl_clippedrelu_fp16.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "convnd_fwd_activ_unary_common.hpp"
+
+using OutElementOp = ck::tensor_operation::element_wise::ClippedRelu;
+
+using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDFwdInstance<OutElementOp>;
+#include "../run_convnd_activ_example.inc"
+
+int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }

example/62_convnd_activ/unary/convnd_fwd_xdl_elu_fp16.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "convnd_fwd_activ_unary_common.hpp"
+
+using OutElementOp = ck::tensor_operation::element_wise::Elu;
+
+using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDFwdInstance<OutElementOp>;
+#include "../run_convnd_activ_example.inc"
+
+int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }

example/62_convnd_activ/unary/convnd_fwd_xdl_leakyrelu_fp16.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "convnd_fwd_activ_unary_common.hpp"
+
+using OutElementOp = ck::tensor_operation::element_wise::LeakyRelu;
+
+using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDFwdInstance<OutElementOp>;
+#include "../run_convnd_activ_example.inc"
+
+int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }

example/62_convnd_activ/unary/convnd_fwd_xdl_pow_fp16.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "convnd_fwd_activ_unary_common.hpp"
+
+using OutElementOp = ck::tensor_operation::element_wise::Power;
+
+using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDFwdInstance<OutElementOp>;
+#include "../run_convnd_activ_example.inc"
+
+int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }

example/62_convnd_activ/unary/convnd_fwd_xdl_relu_fp16.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "convnd_fwd_activ_unary_common.hpp"
+
+using OutElementOp = ck::tensor_operation::element_wise::Relu;
+
+using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDFwdInstance<OutElementOp>;
+#include "../run_convnd_activ_example.inc"
+
+int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }

example/62_convnd_activ/unary/convnd_fwd_xdl_sigmoid_fp16.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "convnd_fwd_activ_unary_common.hpp"
+
+using OutElementOp = ck::tensor_operation::element_wise::Sigmoid;
+
+using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDFwdInstance<OutElementOp>;
+#include "../run_convnd_activ_example.inc"
+
+int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }

example/62_convnd_activ/unary/convnd_fwd_xdl_softrelu_fp16.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "convnd_fwd_activ_unary_common.hpp"
+
+using OutElementOp = ck::tensor_operation::element_wise::SoftRelu;
+
+using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDFwdInstance<OutElementOp>;
+#include "../run_convnd_activ_example.inc"
+
+int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }

example/62_convnd_activ/unary/convnd_fwd_xdl_tanh_fp16.cpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2023-2024, Advanced Micro Devices, Inc. All rights reserved.
+
+#include "convnd_fwd_activ_unary_common.hpp"
+
+using OutElementOp = ck::tensor_operation::element_wise::TanH;
+
+using DeviceGroupedConvNDActivInstance = DeviceGroupedConvNDFwdInstance<OutElementOp>;
+#include "../run_convnd_activ_example.inc"
+
+int main(int argc, char* argv[]) { return !run_convnd_example(argc, argv); }

example/63_layernorm4d_fwd/CMakeLists.txt

+add_example_executable(example_layernorm4d_fwd_fp16 layernorm4d_fwd_fp16.cpp)
+add_example_executable(example_layernorm4d_fwd_splitk_fp16 layernorm4d_fwd_splitk_fp16.cpp)

example/63_layernorm4d_fwd/common.hpp

+// SPDX-License-Identifier: MIT
+// Copyright (c) 2018-2023, Advanced Micro Devices, Inc. All rights reserved.
+
+#pragma once
+
+#include <iostream>
+#include <numeric>
+#include <initializer_list>
+#include <cstdlib>
+#include <getopt.h>
+
+#include "ck/ck.hpp"
+#include "ck/tensor_operation/gpu/device/impl/device_normalization_fwd_impl.hpp"
+#include "ck/tensor_operation/gpu/device/impl/device_normalization_fwd_splitk_impl.hpp"
+
+#include "ck/library/utility/check_err.hpp"
+#include "ck/library/utility/device_memory.hpp"
+#include "ck/library/utility/host_common_util.hpp"
+#include "ck/library/utility/host_tensor.hpp"
+#include "ck/library/utility/host_tensor_generator.hpp"
+#include "ck/library/utility/literals.hpp"
+#include "ck/library/reference_tensor_operation/cpu/reference_layernorm.hpp"