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Diffstat (limited to 'src/gpu/cl/kernels/ClMatMulNativeKernel.cpp')
| -rw-r--r-- | src/gpu/cl/kernels/ClMatMulNativeKernel.cpp | 284 |
1 files changed, 284 insertions, 0 deletions
diff --git a/src/gpu/cl/kernels/ClMatMulNativeKernel.cpp b/src/gpu/cl/kernels/ClMatMulNativeKernel.cpp new file mode 100644 index 0000000000..a1fa9fa9ab --- /dev/null +++ b/src/gpu/cl/kernels/ClMatMulNativeKernel.cpp @@ -0,0 +1,284 @@ +/* + * Copyright (c) 2023 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 "src/gpu/cl/kernels/ClMatMulNativeKernel.h" + +#include "arm_compute/core/CL/CLHelpers.h" +#include "arm_compute/core/CL/ICLTensor.h" +#include "arm_compute/core/ITensorPack.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/utils/ActivationFunctionUtils.h" +#include "arm_compute/core/utils/helpers/AdjustVecSize.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" +#include "arm_compute/core/utils/StringUtils.h" + +#include "src/common/utils/Log.h" +#include "src/core/CL/CLUtils.h" +#include "src/core/helpers/AutoConfiguration.h" +#include "src/core/helpers/WindowHelpers.h" +#include "src/gpu/cl/kernels/gemm/ClGemmHelpers.h" +#include "src/gpu/cl/kernels/helpers/MatMulKernelHelpers.h" +#include "support/Cast.h" +#include "support/StringSupport.h" + +namespace arm_compute +{ +namespace opencl +{ +namespace kernels +{ +namespace +{ +Status validate_matmul_kernel_info(const MatMulKernelInfo &matmul_kernel_info) +{ + const bool adj_lhs = matmul_kernel_info.adj_lhs; + const bool adj_rhs = matmul_kernel_info.adj_rhs; + const int m0 = matmul_kernel_info.m0; + const int n0 = matmul_kernel_info.n0; + const int k0 = matmul_kernel_info.k0; + + // Validate M0 + ARM_COMPUTE_RETURN_ERROR_ON_MSG(m0 < 1, "Only positive integers are supported for M0"); + + if (adj_lhs) + { + ARM_COMPUTE_RETURN_ERROR_ON_MSG(((m0 & (m0 - 1)) && (m0 != 3)) || (m0 > 16), + "Only 1,2,3,4,8,16 are supported for M0 for Lhs transposed"); + } + + // Validate N0 + ARM_COMPUTE_RETURN_ERROR_ON_MSG(n0 < 1, "Only positive integers are supported for N0"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(((n0 & (n0 - 1)) && (n0 != 3)) || (n0 > 16), + "Only 1,2,3,4,8,16 are supported for N0"); + + // Validate K0 + ARM_COMPUTE_RETURN_ERROR_ON_MSG(k0 < 1, "Only positive integers are supported for K0"); + if (!adj_lhs || adj_rhs) + { + ARM_COMPUTE_RETURN_ERROR_ON_MSG(((k0 & (k0 - 1)) && (k0 != 3)) || (k0 > 16), + "Only 1,2,3,4,8,16 are supported for K0"); + } + + return Status{}; +} + +Status validate_export_to_cl_image(const ITensorInfo *rhs, const MatMulKernelInfo &matmul_kernel_info) +{ + ARM_COMPUTE_RETURN_ERROR_ON(matmul_kernel_info.export_rhs_to_cl_image && rhs->lock_paddings()); + if (matmul_kernel_info.export_rhs_to_cl_image) + { + if (matmul_kernel_info.adj_rhs) + { + const int k0 = matmul_kernel_info.k0; + ARM_COMPUTE_RETURN_ERROR_ON_MSG(k0 != 4 && k0 != 8 && k0 != 16, + "K0 can only be: 4, 8, and 16 for Rhs transposed"); + } + else + { + const int n0 = matmul_kernel_info.n0; + ARM_COMPUTE_RETURN_ERROR_ON_MSG(n0 != 4 && n0 != 8 && n0 != 16, + "N0 can only be: 4, 8, and 16 for Rhs non-transposed"); + } + ARM_COMPUTE_RETURN_ERROR_ON_MSG(!export_to_cl_image(rhs), + "Export to CLImage is not supported for this device/configuration"); + } + + return Status{}; +} +} // namespace +ClMatMulNativeKernel::ClMatMulNativeKernel() +{ + _type = CLKernelType::GEMM; +} + +Status ClMatMulNativeKernel::validate(const ITensorInfo *lhs, + const ITensorInfo *rhs, + const ITensorInfo *bias, + const ITensorInfo *dst, + const MatMulKernelInfo &matmul_kernel_info, + const ActivationLayerInfo &act_info) +{ + ARM_COMPUTE_UNUSED(act_info); + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(lhs, rhs, dst); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(lhs, 1, DataType::F32, DataType::F16); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, rhs); + ARM_COMPUTE_RETURN_ON_ERROR(validate_matmul_kernel_info(matmul_kernel_info)); + ARM_COMPUTE_RETURN_ON_ERROR( + validate_matmul_input_shapes(lhs->tensor_shape(), rhs->tensor_shape(), matmul_kernel_info)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_export_to_cl_image(rhs, matmul_kernel_info)); + + const TensorShape expected_output_shape = + misc::shape_calculator::compute_matmul_shape(lhs->tensor_shape(), rhs->tensor_shape(), matmul_kernel_info); + + if (dst->total_size() != 0) + { + const TensorInfo tensor_info_dst = dst->clone()->set_tensor_shape(expected_output_shape); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(dst, &tensor_info_dst); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, dst); + } + + if (bias != nullptr) + { + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(bias, lhs); + ARM_COMPUTE_RETURN_ERROR_ON_MSG((bias->num_dimensions() > 1), "Multi dimensional bias is unsupported."); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(bias->dimension(0) != expected_output_shape[0], + "First dimension of bias and output tensors must match."); + } + + return Status{}; +} +void ClMatMulNativeKernel::configure(const ClCompileContext &compile_context, + ITensorInfo *lhs, + ITensorInfo *rhs, + ITensorInfo *bias, + ITensorInfo *dst, + const MatMulKernelInfo &matmul_kernel_info, + const ActivationLayerInfo &act_info) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(lhs, rhs, dst, &compile_context, &matmul_kernel_info); + ARM_COMPUTE_LOG_PARAMS(lhs, rhs, bias, dst, matmul_kernel_info); + ARM_COMPUTE_ERROR_THROW_ON(validate(lhs, rhs, bias, dst, matmul_kernel_info)); + + // dst tensor auto initialization if not yet initialized + auto_init_if_empty(*dst, lhs->clone()->set_tensor_shape(misc::shape_calculator::compute_matmul_shape( + lhs->tensor_shape(), rhs->tensor_shape(), matmul_kernel_info))); + + const int m = dst->dimension(1); + const int n = dst->dimension(0); + const int k = matmul_kernel_info.adj_lhs ? lhs->tensor_shape().y() : lhs->tensor_shape().x(); + const bool adj_lhs = matmul_kernel_info.adj_lhs; + + int m0 = adj_lhs ? adjust_vec_size(matmul_kernel_info.m0, m) : std::min(matmul_kernel_info.m0, m); + int n0 = adjust_vec_size(matmul_kernel_info.n0, n); + + _export_rhs_to_cl_image = matmul_kernel_info.export_rhs_to_cl_image && !rhs->lock_paddings(); + + // Configure kernel window + Window win = calculate_max_window(*dst, Steps(n0, m0)); + win = win.collapse(win, Window::DimZ); + IClKernel::configure_internal(win); + + // Calculate partial (store instead of load) M0 and partial N0 for the partial blocks at the end of a row/column if any. This is to avoid padding. + const unsigned int partial_store_m0 = m % m0; + const unsigned int partial_store_n0 = n % n0; + + CLBuildOptions build_opts; + build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(lhs->data_type())); + build_opts.add_option("-DM0=" + support::cpp11::to_string(m0)); + build_opts.add_option("-DN0=" + support::cpp11::to_string(n0)); + build_opts.add_option("-DK0=" + support::cpp11::to_string(matmul_kernel_info.k0)); + build_opts.add_option("-DPARTIAL_STORE_M0=" + support::cpp11::to_string(partial_store_m0)); + build_opts.add_option("-DPARTIAL_STORE_N0=" + support::cpp11::to_string(partial_store_n0)); + build_opts.add_option("-DK=" + support::cpp11::to_string(k)); + build_opts.add_option_if(bias != nullptr, "-DBIAS"); + build_opts.add_option_if_else(_export_rhs_to_cl_image, "-DRHS_TENSOR_TYPE=IMAGE", "-DRHS_TENSOR_TYPE=BUFFER"); + + // Define values for activation function + build_opts.add_option(("-DA_VAL=" + float_to_string_with_full_precision(act_info.a()))); + build_opts.add_option(("-DB_VAL=" + float_to_string_with_full_precision(act_info.b()))); + build_opts.add_option("-DACTIVATION_TYPE=" + lower_string(string_from_activation_func(act_info.activation()))); + + std::string kernel_name("mat_mul_native"); + kernel_name += matmul_kernel_info.adj_lhs ? "_t" : "_nt"; + kernel_name += matmul_kernel_info.adj_rhs ? "_t" : "_nt"; + + // A macro guard to compile ONLY the kernel of interest + build_opts.add_option("-D" + upper_string(kernel_name)); + + if (_export_rhs_to_cl_image) + { + gemm::update_padding_for_cl_image(rhs); + } + + // Create kernel + _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); + + // Set config_id for enabling LWS tuning + _config_id = kernel_name; + _config_id += "_"; + _config_id += lower_string(string_from_data_type(lhs->data_type())); + _config_id += "_"; + _config_id += support::cpp11::to_string(m); + _config_id += "_"; + _config_id += support::cpp11::to_string(n); + _config_id += "_"; + _config_id += support::cpp11::to_string(k); + _config_id += "_"; + _config_id += support::cpp11::to_string(dst->dimension(2)); + _config_id += "_"; + _config_id += support::cpp11::to_string(_export_rhs_to_cl_image); + _config_id += "_"; + _config_id += support::cpp11::to_string(m0); + _config_id += "_"; + _config_id += support::cpp11::to_string(n0); + _config_id += "_"; + _config_id += support::cpp11::to_string(matmul_kernel_info.k0); +} + +void ClMatMulNativeKernel::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); + + const ICLTensor *lhs = + utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_0)); + const ICLTensor *rhs = + utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC_1)); + const ICLTensor *bias = utils::cast::polymorphic_downcast<const ICLTensor *>( + tensors.get_const_tensor(TensorType::ACL_SRC_2)); // nullptr if bias is not present + ICLTensor *dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST)); + ARM_COMPUTE_ERROR_ON_NULLPTR(lhs, rhs, dst); + ARM_COMPUTE_LOG_PARAMS(lhs, rhs, bias, dst); + + unsigned int idx = 0; + Window window_collapsed = window.collapse(ICLKernel::window(), Window::DimZ); + + add_3d_tensor_nhw_argument(idx, lhs); + + cl::Image2D rhs_cl_image; + if (_export_rhs_to_cl_image) + { + const size_t image_w = rhs->info()->dimension(0) / 4; + const size_t image_h = rhs->info()->tensor_shape().total_size() / rhs->info()->dimension(0); + const TensorShape shape2d(image_w, image_h); + const size_t image_row_pitch = rhs->info()->strides_in_bytes()[1]; + + // Export cl_buffer to cl_image + rhs_cl_image = create_image2d_from_buffer(CLKernelLibrary::get().context(), rhs->cl_buffer(), shape2d, + rhs->info()->data_type(), image_row_pitch, CLImage2DType::ReadOnly); + _kernel.setArg(idx++, rhs_cl_image); + } + + add_3d_tensor_nhw_argument(idx, rhs); + if (bias != nullptr) + { + add_3d_tensor_nhw_argument(idx, bias); + } + add_3d_tensor_nhw_argument(idx, dst); + + enqueue(queue, *this, window_collapsed, lws_hint()); +} + +} // namespace kernels +} // namespace opencl +} // namespace arm_compute |