| /* |
| * 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/operators/ClMatMul.h" |
| |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/Utils.h" |
| #include "arm_compute/runtime/CL/CLScheduler.h" |
| |
| #include "src/common/utils/Log.h" |
| #include "src/gpu/cl/kernels/ClMatMulLowpNativeKernel.h" |
| #include "src/gpu/cl/kernels/ClMatMulLowpNativeMMULKernel.h" |
| #include "src/gpu/cl/kernels/ClMatMulNativeKernel.h" |
| #include "src/gpu/cl/kernels/ClMatMulNativeMMULKernel.h" |
| #include "src/runtime/heuristics/matmul_native/ClMatMulNativeDefaultConfigValhall.h" |
| #include "src/runtime/heuristics/matmul_native/ClMatMulNativeKernelConfig.h" |
| #include "src/runtime/heuristics/matmul_native/IClMatMulNativeKernelConfig.h" |
| |
| using namespace arm_compute::cl_matmul; |
| |
| namespace arm_compute |
| { |
| namespace opencl |
| { |
| namespace |
| { |
| enum class MatMulKernelType |
| { |
| /** Native matrix multiplication for FP types */ |
| NATIVE_FP, |
| |
| /** Native matrix multiplication for quantized types */ |
| NATIVE_QUANTIZED, |
| |
| /** Native matrix multiplication using MMUL extension for FP types */ |
| NATIVE_MMUL_FP, |
| |
| /** Native matrix multiplication using MMUL extension for Quantized types */ |
| NATIVE_MMUL_QUANTIZED |
| }; |
| |
| MatMulKernelType get_matmul_kernel(const ITensorInfo *lhs, |
| const ITensorInfo *rhs, |
| const MatMulInfo &matmul_info, |
| const ActivationLayerInfo &act_info) |
| { |
| ARM_COMPUTE_UNUSED(lhs, rhs, matmul_info, act_info); |
| |
| const bool is_quantized = is_data_type_quantized_asymmetric(lhs->data_type()); |
| const bool is_mmul_supported = arm_matrix_multiply_supported(CLKernelLibrary::get().get_device()); |
| |
| const int k = matmul_info.adj_lhs() ? lhs->tensor_shape().y() : lhs->tensor_shape().x(); |
| |
| if (is_quantized) |
| { |
| // MMUL kernel works only when K is a multiple of 16 |
| if (is_mmul_supported && !act_info.enabled() && k % 16 == 0) |
| { |
| return MatMulKernelType::NATIVE_MMUL_QUANTIZED; |
| } |
| |
| return MatMulKernelType::NATIVE_QUANTIZED; |
| } |
| else |
| { |
| // MMUL kernel works only when K is a multiple of 4 |
| if (is_mmul_supported && !act_info.enabled() && k % 4 == 0) |
| { |
| return MatMulKernelType::NATIVE_MMUL_FP; |
| } |
| |
| return MatMulKernelType::NATIVE_FP; |
| } |
| } |
| } // namespace |
| using namespace arm_compute::opencl::kernels; |
| |
| ClMatMul::ClMatMul() |
| { |
| } |
| |
| Status ClMatMul::validate(const ITensorInfo *lhs, |
| const ITensorInfo *rhs, |
| const ITensorInfo *dst, |
| const MatMulInfo &matmul_info, |
| const ActivationLayerInfo &act_info) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(lhs, rhs, dst); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(lhs, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, |
| DataType::F16, DataType::F32); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(rhs, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, |
| DataType::F16, DataType::F32); |
| |
| const GPUTarget gpu_target = CLScheduler::get().target(); |
| |
| std::unique_ptr<IClMatMulNativeKernelConfig> t = ClMatMulNativeKernelConfigurationFactory::create(gpu_target); |
| |
| const MatMulKernelInfo kernel_info = t->configure(lhs, rhs, matmul_info); |
| |
| switch (get_matmul_kernel(lhs, rhs, matmul_info, act_info)) |
| { |
| case MatMulKernelType::NATIVE_FP: |
| return ClMatMulNativeKernel::validate(lhs, rhs, nullptr /* bias */, dst, kernel_info, act_info); |
| case MatMulKernelType::NATIVE_MMUL_FP: |
| return ClMatMulNativeMMULKernel::validate(lhs, rhs, nullptr /* bias */, dst, kernel_info); |
| case MatMulKernelType::NATIVE_QUANTIZED: |
| return ClMatMulLowpNativeKernel::validate(lhs, rhs, nullptr /* bias */, dst, kernel_info, act_info); |
| case MatMulKernelType::NATIVE_MMUL_QUANTIZED: |
| return ClMatMulLowpNativeMMULKernel::validate(lhs, rhs, nullptr /* bias */, dst, kernel_info, act_info); |
| default: |
| ARM_COMPUTE_ERROR("Unsupported MatMul Kernel!"); |
| } |
| } |
| |
| void ClMatMul::configure(const CLCompileContext &compile_context, |
| ITensorInfo *lhs, |
| ITensorInfo *rhs, |
| ITensorInfo *dst, |
| const MatMulInfo &matmul_info, |
| const ActivationLayerInfo &act_info) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(lhs, rhs, dst); |
| ARM_COMPUTE_LOG_PARAMS(lhs, rhs, dst, matmul_info); |
| |
| // Perform validation step |
| ARM_COMPUTE_ERROR_THROW_ON(validate(lhs, rhs, dst, matmul_info)); |
| |
| const GPUTarget gpu_target = CLScheduler::get().target(); |
| const auto kernel_config = ClMatMulNativeKernelConfigurationFactory::create(gpu_target); |
| const MatMulKernelInfo kernel_info = kernel_config->configure(lhs, rhs, matmul_info); |
| |
| switch (get_matmul_kernel(lhs, rhs, matmul_info, act_info)) |
| { |
| case MatMulKernelType::NATIVE_FP: |
| { |
| auto kernel = std::make_unique<ClMatMulNativeKernel>(); |
| kernel->set_target(gpu_target); |
| |
| kernel->configure(compile_context, lhs, rhs, nullptr /* bias */, dst, kernel_info, act_info); |
| _matmul_kernel = std::move(kernel); |
| } |
| break; |
| case MatMulKernelType::NATIVE_MMUL_FP: |
| { |
| auto kernel = std::make_unique<ClMatMulNativeMMULKernel>(); |
| kernel->set_target(gpu_target); |
| |
| kernel->configure(compile_context, lhs, rhs, nullptr /* bias */, dst, kernel_info); |
| _matmul_kernel = std::move(kernel); |
| } |
| break; |
| case MatMulKernelType::NATIVE_QUANTIZED: |
| { |
| auto kernel = std::make_unique<ClMatMulLowpNativeKernel>(); |
| kernel->set_target(gpu_target); |
| |
| kernel->configure(compile_context, lhs, rhs, nullptr /* bias */, dst, kernel_info, act_info); |
| _matmul_kernel = std::move(kernel); |
| } |
| break; |
| case MatMulKernelType::NATIVE_MMUL_QUANTIZED: |
| { |
| auto kernel = std::make_unique<ClMatMulLowpNativeMMULKernel>(); |
| kernel->set_target(gpu_target); |
| |
| kernel->configure(compile_context, lhs, rhs, nullptr /* bias */, dst, kernel_info, act_info); |
| _matmul_kernel = std::move(kernel); |
| } |
| break; |
| default: |
| ARM_COMPUTE_ERROR("Unsupported MatMul Kernel!"); |
| } |
| } |
| |
| void ClMatMul::run(ITensorPack &tensors) |
| { |
| CLScheduler::get().enqueue_op(*_matmul_kernel, tensors, /* flush */ true); |
| } |
| |
| } // namespace opencl |
| } // namespace arm_compute |