From a2ea75360b1193318dc8441bbd9120eb747041ae Mon Sep 17 00:00:00 2001 From: Anthony Barbier Date: Tue, 28 Nov 2017 10:33:22 +0000 Subject: COMPMID-661 Add Bifrost lws heuristics for several depthwise_convolution kernels #49 Change-Id: Ibfa1c1cc9fc8501b22a18ecd519758f4aeb301eb Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/110880 Tested-by: BSG Visual Compute Jenkins server to access repositories on http://mpd-gerrit.cambridge.arm.com Reviewed-by: Anthony Barbier Reviewed-by: Gian Marco Iodice Reviewed-by: Georgios Pinitas --- .../CL/kernels/CLDepthwiseConvolution3x3Kernel.cpp | 57 +++++++++++++++------- src/core/CL/kernels/CLDepthwiseIm2ColKernel.cpp | 10 +++- .../kernels/CLGEMMMatrixVectorMultiplyKernel.cpp | 10 +++- .../CL/functions/CLDepthwiseConvolution.cpp | 6 ++- 4 files changed, 62 insertions(+), 21 deletions(-) (limited to 'src') diff --git a/src/core/CL/kernels/CLDepthwiseConvolution3x3Kernel.cpp b/src/core/CL/kernels/CLDepthwiseConvolution3x3Kernel.cpp index 63586b0f0f..be8fae2885 100644 --- a/src/core/CL/kernels/CLDepthwiseConvolution3x3Kernel.cpp +++ b/src/core/CL/kernels/CLDepthwiseConvolution3x3Kernel.cpp @@ -93,9 +93,47 @@ void CLDepthwiseConvolution3x3Kernel::configure(const ICLTensor *input, const IC build_opts.add_option("-DCONV_STRIDE_X=" + support::cpp11::to_string(_conv_stride_x)); build_opts.add_option_if(_biases != nullptr, "-DHAS_BIAS"); + // Create kernel std::string kernel_name = is_data_type_quantized_asymmetric(_input->info()->data_type()) ? "depthwise_convolution_3x3_quantized" : "depthwise_convolution_3x3"; _kernel = static_cast(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options())); + // Set static arguments + if(is_data_type_quantized_asymmetric(_input->info()->data_type())) + { + float multiplier = _input->info()->quantization_info().scale * _weights->info()->quantization_info().scale / _output->info()->quantization_info().scale; + int output_multiplier = 0; + int output_shift = 0; + quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); + + unsigned int idx = 3 * num_arguments_per_3D_tensor() + ((_biases != nullptr) ? num_arguments_per_1D_tensor() : 0); + + _kernel.setArg(idx++, -_input->info()->quantization_info().offset); + _kernel.setArg(idx++, -_weights->info()->quantization_info().offset); + _kernel.setArg(idx++, _output->info()->quantization_info().offset); + _kernel.setArg(idx++, output_multiplier); + _kernel.setArg(idx++, output_shift); + } + + // Configure the local work size for Bifrost with a value obtained + // via exhaustive autotuning for the MobileNets tensor shapes. + const GPUTarget gpu_target = get_arch_from_target(get_target()); + if(gpu_target == GPUTarget::BIFROST) + { + const size_t width = input->info()->dimension(0); + if(width >= 56) // 56 or 112 + { + _lws_hint = cl::NDRange(8, 5, 2); + } + else if(width >= 14) // 14 or 28 + { + _lws_hint = cl::NDRange(1, 5, 2); + } + else // 7 + { + _lws_hint = cl::NDRange(1, 1, 2); + } + } + // Configure kernel window const unsigned int num_elems_processed_per_iteration = 2; const unsigned int num_elems_written_per_iteration = 2; @@ -113,23 +151,6 @@ void CLDepthwiseConvolution3x3Kernel::configure(const ICLTensor *input, const IC output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape())); ICLKernel::configure(win); - - // Set static arguments - if(is_data_type_quantized_asymmetric(_input->info()->data_type())) - { - float multiplier = _input->info()->quantization_info().scale * _weights->info()->quantization_info().scale / _output->info()->quantization_info().scale; - int output_multiplier = 0; - int output_shift = 0; - quantization::calculate_quantized_multiplier_less_than_one(multiplier, &output_multiplier, &output_shift); - - unsigned int idx = 3 * num_arguments_per_3D_tensor() + ((_biases != nullptr) ? num_arguments_per_1D_tensor() : 0); - - _kernel.setArg(idx++, -_input->info()->quantization_info().offset); - _kernel.setArg(idx++, -_weights->info()->quantization_info().offset); - _kernel.setArg(idx++, _output->info()->quantization_info().offset); - _kernel.setArg(idx++, output_multiplier); - _kernel.setArg(idx++, output_shift); - } } void CLDepthwiseConvolution3x3Kernel::run(const Window &window, cl::CommandQueue &queue) @@ -166,7 +187,7 @@ void CLDepthwiseConvolution3x3Kernel::run(const Window &window, cl::CommandQueue add_3D_tensor_argument(idx, _output, slice_out); add_3D_tensor_argument(idx, _weights, slice_weights); - enqueue(queue, *this, slice_out); + enqueue(queue, *this, slice_out, _lws_hint); } while(window.slide_window_slice_3D(slice_out) && win_in.slide_window_slice_3D(slice_in)); } diff --git a/src/core/CL/kernels/CLDepthwiseIm2ColKernel.cpp b/src/core/CL/kernels/CLDepthwiseIm2ColKernel.cpp index c23941426e..ad9ac0ecd6 100644 --- a/src/core/CL/kernels/CLDepthwiseIm2ColKernel.cpp +++ b/src/core/CL/kernels/CLDepthwiseIm2ColKernel.cpp @@ -73,6 +73,14 @@ void CLDepthwiseIm2ColKernel::configure(const ICLTensor *input, ICLTensor *outpu } _kernel = static_cast(CLKernelLibrary::get().create_kernel("depthwise_im2col", build_opts)); + // Configure the local work size for Bifrost with a value obtained + // via exhaustive autotuning for the MobileNets tensor shapes. + const GPUTarget gpu_target = get_arch_from_target(get_target()); + if(gpu_target == GPUTarget::BIFROST) + { + _lws_hint = cl::NDRange(1, 2, 1); + } + // Configure kernel window Window win = calculate_max_window(*input->info(), Steps()); // The CLDepthwiseIm2ColKernel doesn't need padding so update_window_and_padding() can be skipped @@ -105,7 +113,7 @@ void CLDepthwiseIm2ColKernel::run(const Window &window, cl::CommandQueue &queue) unsigned int idx = 0; add_3D_tensor_argument(idx, _input, slice_in); add_3D_tensor_argument(idx, _output, slice); - enqueue(queue, *this, slice); + enqueue(queue, *this, slice, _lws_hint); } while(window.slide_window_slice_3D(slice) && window.slide_window_slice_3D(slice_in)); } diff --git a/src/core/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.cpp index 70af5d63cf..951bc144aa 100644 --- a/src/core/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.cpp +++ b/src/core/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.cpp @@ -63,6 +63,14 @@ void CLGEMMMatrixVectorMultiplyKernel::configure(const ICLTensor *input0, const _kernel = static_cast(CLKernelLibrary::get().create_kernel("gemm_mv", build_opts)); + // Configure the local work size for Bifrost with a value obtained + // via exhaustive autotuning for the MobileNets tensor shapes. + const GPUTarget gpu_target = get_arch_from_target(get_target()); + if(gpu_target == GPUTarget::BIFROST) + { + _lws_hint = cl::NDRange(1, 1, 1); + } + // Configure kernel window const unsigned int num_elems_read_per_iteration = 4; @@ -119,7 +127,7 @@ void CLGEMMMatrixVectorMultiplyKernel::run(const Window &window, cl::CommandQueu unsigned int idx_2 = num_arguments_per_3D_tensor() + num_arguments_per_2D_tensor(); add_3D_tensor_argument(idx_0, _input0, slice_in); add_1D_tensor_argument(idx_2, _output, slice_out); - enqueue(queue, *this, slice_in); + enqueue(queue, *this, slice_in, _lws_hint); } while(window.slide_window_slice_3D(slice_in) && window.slide_window_slice_3D(slice_out)); } diff --git a/src/runtime/CL/functions/CLDepthwiseConvolution.cpp b/src/runtime/CL/functions/CLDepthwiseConvolution.cpp index 23a20a3011..baa05b921a 100644 --- a/src/runtime/CL/functions/CLDepthwiseConvolution.cpp +++ b/src/runtime/CL/functions/CLDepthwiseConvolution.cpp @@ -41,6 +41,7 @@ void CLDepthwiseConvolution3x3::configure(ICLTensor *input, const ICLTensor *wei ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8, DataType::F32); ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, weights); + _kernel.set_target(CLScheduler::get().target()); _kernel.configure(input, weights, biases, output, conv_info); _border_handler.configure(input, _kernel.border_size(), BorderMode::CONSTANT, PixelValue(0)); } @@ -67,7 +68,8 @@ void CLDepthwiseConvolution::configure(ICLTensor *input, const ICLTensor *weight const size_t weights_h = weights->info()->dimension(1); const size_t weights_z = weights->info()->dimension(2); - bool has_bias = (biases != nullptr); + const bool has_bias = (biases != nullptr); + const GPUTarget gpu_target = CLScheduler::get().target(); unsigned int conv_w = 0; unsigned int conv_h = 0; @@ -84,6 +86,7 @@ void CLDepthwiseConvolution::configure(ICLTensor *input, const ICLTensor *weight shape_im2col.set(2, weights_z); const TensorInfo info_im2col(shape_im2col, 1, input->info()->data_type(), input->info()->fixed_point_position()); _input_reshaped.allocator()->init(info_im2col); + _im2col_kernel.set_target(gpu_target); _im2col_kernel.configure(input, &_input_reshaped, Size2D(weights_w, weights_h), conv_info, has_bias); // Weights reshape configuration @@ -99,6 +102,7 @@ void CLDepthwiseConvolution::configure(ICLTensor *input, const ICLTensor *weight shape_v2mm_out.set(2, 1); const TensorInfo info_v2mm_out(shape_v2mm_out, 1, input->info()->data_type(), input->info()->fixed_point_position()); _v2mm_output.allocator()->init(info_v2mm_out); + _v2mm_kernel.set_target(gpu_target); _v2mm_kernel.configure(&_input_reshaped, &_weights_reshaped, &_v2mm_output); _vector_to_tensor_kernel.configure(&_v2mm_output, output, conv_w, conv_h); -- cgit v1.2.1