| /* |
| * Copyright (c) 2022 Arm Limited. |
| * |
| * SPDX-License-Identifier: MIT |
| * |
| * Permission is hereby granted, free of charge, to any person obtaining a copy |
| * of this software and associated documentation files (the "Software"), to |
| * deal in the Software without restriction, including without limitation the |
| * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or |
| * sell copies of the Software, and to permit persons to whom the Software is |
| * furnished to do so, subject to the following conditions: |
| * |
| * The above copyright notice and this permission notice shall be included in all |
| * copies or substantial portions of the Software. |
| * |
| * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR |
| * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, |
| * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE |
| * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER |
| * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, |
| * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE |
| * SOFTWARE. |
| */ |
| #include "ClKernelRuntime.h" |
| #include "arm_compute/core/CL/ICLTensor.h" |
| #include "src/core/CL/CLUtils.h" |
| #include "src/dynamic_fusion/sketch/gpu/GpuKernelSourceCode.h" |
| #include "src/gpu/cl/ClKernelLibrary.h" |
| |
| #include "support/Cast.h" |
| namespace arm_compute |
| { |
| namespace experimental |
| { |
| namespace dynamic_fusion |
| { |
| using namespace arm_compute::opencl; |
| |
| void ClKernelRuntime::configure(const ClCompileContext &compile_ctx, const GpuKernelSourceCode &code) |
| { |
| // Create kernel from kernel source string |
| opencl::ClKernelLibrary &klib = opencl::ClKernelLibrary::get(); |
| _kernel = static_cast<cl::Kernel>(compile_ctx.create_kernel(code.name(), |
| "" /* Program name: Used to as part of a unique string for built kernel cache. Not needed */, |
| code.code(), |
| klib.kernel_path() /* Kernel path: Used in cases of embedded kernels */, |
| code.build_options().options(), |
| false /* Is source binary */)); |
| |
| // Configure execution window |
| IClKernel::configure_internal(code.window()); |
| |
| // Set config id for lws tuning |
| _config_id = code.config_id(); |
| |
| // Set kernel arguments |
| _arguments = code.arguments(); |
| } |
| |
| inline void ClKernelRuntime::add_tensor_argument(unsigned int &idx, const GpuKernelArgumentInfo &arg, const ICLTensor *tensor, const Window &arg_slice, std::vector<cl::Image2D> &cl_images) |
| { |
| switch(arg.type) |
| { |
| case GpuKernelArgumentInfo::Type::Scalar: |
| { |
| ARM_COMPUTE_ERROR("Unsupported yet"); |
| break; |
| } |
| |
| case GpuKernelArgumentInfo::Type::Vector: |
| { |
| add_1D_tensor_argument(idx, tensor, arg_slice); |
| break; |
| } |
| |
| case GpuKernelArgumentInfo::Type::Image: |
| { |
| add_2D_tensor_argument(idx, tensor, arg_slice); |
| break; |
| } |
| case GpuKernelArgumentInfo::Type::Image_Reinterpret_As_3D: |
| { |
| add_2D_tensor_argument(idx, tensor, arg_slice); |
| const unsigned int total_cross_plane_pad = tensor->info()->padding().top + tensor->info()->padding().bottom; |
| _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(total_cross_plane_pad)); |
| break; |
| } |
| case GpuKernelArgumentInfo::Type::Image_Export_To_ClImage2D: |
| { |
| const TensorShape shape2d(tensor->info()->dimension(0) / 4, tensor->info()->dimension(1) * tensor->info()->dimension(2) * tensor->info()->dimension(3)); |
| const size_t image_row_pitch = tensor->info()->strides_in_bytes()[1]; |
| cl::Image2D tensor_image2d = create_image2d_from_buffer(CLKernelLibrary::get().context(), tensor->cl_buffer(), shape2d, tensor->info()->data_type(), image_row_pitch); |
| cl_images.push_back(tensor_image2d); |
| _kernel.setArg(idx++, tensor_image2d); |
| break; |
| } |
| |
| case GpuKernelArgumentInfo::Type::Image_3D: |
| { |
| add_2D_tensor_argument(idx, tensor, arg_slice); |
| _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(tensor->info()->strides_in_bytes()[2])); |
| break; |
| } |
| case GpuKernelArgumentInfo::Type::Image_3D_Export_To_ClImage2D: |
| { |
| const TensorShape shape2d(tensor->info()->dimension(0) / 4, tensor->info()->dimension(1) * tensor->info()->dimension(2) * tensor->info()->dimension(3)); |
| const size_t image_row_pitch = tensor->info()->strides_in_bytes()[1]; |
| cl::Image2D tensor_image2d = create_image2d_from_buffer(CLKernelLibrary::get().context(), tensor->cl_buffer(), shape2d, tensor->info()->data_type(), image_row_pitch); |
| cl_images.push_back(tensor_image2d); |
| _kernel.setArg(idx++, tensor_image2d); |
| _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(tensor->info()->strides_in_bytes()[2])); |
| break; |
| } |
| |
| case GpuKernelArgumentInfo::Type::Tensor_3D: |
| { |
| add_3D_tensor_argument(idx, tensor, arg_slice); |
| break; |
| } |
| |
| case GpuKernelArgumentInfo::Type::Tensor_4D: |
| { |
| add_4D_tensor_argument(idx, tensor, arg_slice); |
| break; |
| } |
| case GpuKernelArgumentInfo::Type::Tensor_4D_t_Buffer: |
| { |
| add_4d_tensor_nhwc_argument(idx, tensor); |
| break; |
| } |
| case GpuKernelArgumentInfo::Type::Tensor_4D_t_Image: |
| { |
| const size_t image_w = tensor->info()->dimension(0) / 4; |
| const size_t image_h = tensor->info()->tensor_shape().total_size_upper(1); |
| const size_t image_stride_y = tensor->info()->strides_in_bytes()[1]; |
| |
| cl::Image2D tensor_image2d = create_image2d_from_buffer(CLKernelLibrary::get().context(), tensor->cl_buffer(), |
| TensorShape(image_w, image_h), tensor->info()->data_type(), image_stride_y); |
| cl_images.push_back(tensor_image2d); |
| |
| _kernel.setArg(idx++, tensor_image2d); |
| add_4d_tensor_nhwc_argument(idx, tensor); |
| break; |
| } |
| default: |
| { |
| ARM_COMPUTE_ERROR("Unsupported"); |
| } |
| } |
| } |
| |
| void ClKernelRuntime::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) |
| { |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); |
| |
| Window slice = window.first_slice_window_3D(); |
| // Don't slice matrix along the z dimension if matrix has just 2 dimensions and matrix A more than 2 |
| // This scenario can happen when the matrix multiplication is used to perform a convolution operation |
| Window slice_fixed_z = slice; |
| slice_fixed_z.set(Window::DimX, Window::Dimension(0, 1, 1)); |
| slice_fixed_z.set(Window::DimY, Window::Dimension(0, 1, 1)); |
| |
| /// NOTE: Parameters extracted from old kernels. So far they seem to be constant |
| /// but we may need to make them into another configuration passed from GpuWorkloadSourceCode if needed in the future |
| constexpr bool slide_along_dimz = true; |
| constexpr bool skip_sliding_window = false; |
| constexpr bool use_dummy_work_items = false; |
| |
| unsigned int idx = 0; |
| do |
| { |
| // Set kernel arguments |
| Window arg_slice = slice; |
| // CLImages created from tensor arguments. Need to be retained until enqueue |
| std::vector<cl::Image2D> cl_images; |
| for(auto id_arg : _arguments) |
| { |
| const auto arg = id_arg.second; |
| auto tensor = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(id_arg.first)); |
| ARM_COMPUTE_ERROR_ON_NULLPTR(tensor); |
| ARM_COMPUTE_ERROR_ON_NULLPTR(tensor->info()); |
| if(!slide_along_dimz) |
| { |
| // The stride_z for matrix must be zero if we do not slice |
| ARM_COMPUTE_ERROR_ON(tensor->info()->strides_in_bytes()[3] != 0); |
| arg_slice = slice_fixed_z; |
| } |
| add_tensor_argument(idx, *arg.kernel_argument_info(), tensor, arg_slice, cl_images); |
| } |
| |
| // Dispatch kernel |
| enqueue(queue, *this, slice, lws_hint(), use_dummy_work_items); |
| } |
| while(skip_sliding_window && window.slide_window_slice_3D(slice)); |
| } |
| |
| } // namespace dynamic_fusion |
| } // namespace experimental |
| } // namespace arm_compute |