From 5cb4d6a1d0f39bf800edb43c0ec7c96dae10e132 Mon Sep 17 00:00:00 2001 From: Gian Marco Iodice Date: Tue, 8 Aug 2017 10:53:00 +0100 Subject: COMPMID-477 - Optimizing CLDirectConvolution 3x3 on OpenCL and added the auto configuration Change-Id: I3c8384dcbc9d7786943134bb658dafb35356d90d Reviewed-on: http://mpd-gerrit.cambridge.arm.com/83253 Reviewed-by: Steven Niu Tested-by: Kaizen --- .../CL/kernels/CLDirectConvolutionLayerKernel.cpp | 81 +++++++++++++--------- 1 file changed, 47 insertions(+), 34 deletions(-) (limited to 'src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp') diff --git a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp b/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp index 1f481de921..5f14d16ff4 100644 --- a/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp +++ b/src/core/CL/kernels/CLDirectConvolutionLayerKernel.cpp @@ -32,6 +32,7 @@ #include "arm_compute/core/IAccessWindow.h" #include "arm_compute/core/ITensor.h" #include "arm_compute/core/Types.h" +#include "arm_compute/core/Utils.h" #include "arm_compute/core/Validate.h" #include "support/ToolchainSupport.h" @@ -49,20 +50,17 @@ BorderSize CLDirectConvolutionLayerKernel::border_size() const void CLDirectConvolutionLayerKernel::configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info) { - const unsigned int kernel_size = weights->info()->dimension(0); - ARM_COMPUTE_ERROR_ON_MSG(kernel_size != 1 && kernel_size != 3, - "Kernel sizes other than 1x1 or 3x3 are not supported"); ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F16, DataType::F32); - ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights, output); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, weights); + ARM_COMPUTE_ERROR_ON_MSG(weights->info()->dimension(0) != weights->info()->dimension(1), + "Only kernel sizes 1x1 and 3x3 are supported"); + ARM_COMPUTE_ERROR_ON_MSG(weights->info()->dimension(0) != 1 && weights->info()->dimension(0) != 3, + "Only kernel sizes 1x1 and 3x3 are supported"); ARM_COMPUTE_ERROR_ON(weights->info()->dimension(2) != input->info()->dimension(2)); ARM_COMPUTE_ERROR_ON(weights->info()->dimension(0) != weights->info()->dimension(1)); ARM_COMPUTE_ERROR_ON(weights->info()->num_dimensions() > 4); - ARM_COMPUTE_ERROR_ON_MSG(weights->info()->dimension(0) == 1 && (std::get<0>(conv_info.pad()) || std::get<1>(conv_info.pad())), - "Pad > 0 not supported for 1x1 weights"); - ARM_COMPUTE_ERROR_ON_MSG(weights->info()->dimension(0) == 3 && (std::get<0>(conv_info.pad()) > 1 || std::get<1>(conv_info.pad()) > 1), - "Pad > 1 not supported for 3x3 weights"); - ARM_COMPUTE_ERROR_ON_MSG(std::get<0>(conv_info.stride()) > 3, "Strides larger than 3 not supported."); - ARM_COMPUTE_ERROR_ON_MSG((kernel_size == 3 && std::get<0>(conv_info.stride()) > 2), "Strides larger than 2 not supported in 3x3 direct convolution!"); + ARM_COMPUTE_ERROR_ON_MSG((weights->info()->dimension(0) == 1) && std::get<0>(conv_info.stride()) > 3, "Strides larger than 3 not supported for 1x1 convolution."); + ARM_COMPUTE_ERROR_ON_MSG((weights->info()->dimension(0) == 3) && std::get<0>(conv_info.stride()) > 2, "Strides larger than 2 not supported for 3x3 convolution."); if(biases != nullptr) { @@ -71,10 +69,29 @@ void CLDirectConvolutionLayerKernel::configure(const ICLTensor *input, const ICL ARM_COMPUTE_ERROR_ON(biases->info()->num_dimensions() > 1); } + const unsigned int kernel_size = weights->info()->dimension(0); + + // Get convolved dimensions + unsigned int output_width = 0; + unsigned int output_height = 0; + std::tie(output_width, output_height) = scaled_dimensions(input->info()->dimension(0), input->info()->dimension(1), kernel_size, kernel_size, conv_info); + + TensorShape output_shape = input->info()->tensor_shape(); + output_shape.set(0, output_width); + output_shape.set(1, output_height); + output_shape.set(2, weights->info()->dimension(3)); + + // Output auto inizialitation if not yet initialized + auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->fixed_point_position()); + + ARM_COMPUTE_ERROR_ON_MISMATCHING_DIMENSIONS(output->info()->tensor_shape(), output_shape); + ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); + ARM_COMPUTE_ERROR_ON_MISMATCHING_FIXED_POINT(input, output); + _conv_stride_x = std::get<0>(conv_info.stride()); _conv_stride_y = std::get<1>(conv_info.stride()); - _conv_pad_x = std::get<0>(conv_info.pad()); - _conv_pad_y = std::get<1>(conv_info.pad()); + _conv_pad_x = std::min(std::get<0>(conv_info.pad()), kernel_size / 2); + _conv_pad_y = std::min(std::get<1>(conv_info.pad()), kernel_size / 2); _input = input; _weights = weights; @@ -86,9 +103,9 @@ void CLDirectConvolutionLayerKernel::configure(const ICLTensor *input, const ICL std::set options; kernel_name << "direct_convolution" << kernel_size << "x" << kernel_size; - options.insert("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())); - options.insert("-DDATA_SIZE=" + get_data_size_from_data_type(input->info()->data_type())); - + options.emplace("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())); + options.emplace("-DDATA_SIZE=" + get_data_size_from_data_type(input->info()->data_type())); + options.emplace("-DWEIGHTS_DEPTH=" + support::cpp11::to_string(_weights->info()->dimension(2))); options.emplace("-DSTRIDE_X=" + support::cpp11::to_string(_conv_stride_x)); if(_biases != nullptr) @@ -98,33 +115,27 @@ void CLDirectConvolutionLayerKernel::configure(const ICLTensor *input, const ICL _kernel = static_cast(CLKernelLibrary::get().create_kernel(kernel_name.str(), options)); - unsigned int idx = (_biases == nullptr) ? 3 * num_arguments_per_3D_tensor() : (num_arguments_per_1D_tensor() + 3 * num_arguments_per_3D_tensor()); - _kernel.setArg(idx++, _weights->info()->strides_in_bytes()[3]); // weights_stride_w - _kernel.setArg(idx++, _weights->info()->dimension(2)); // filter depth - - // Using this local workgroup size gives better performance over others that have been tried. - _lws_hint = cl::NDRange(4, 1, 8); - // Configure kernel window Window win = calculate_max_window(*output->info()); - unsigned int num_elems_read_per_iteration = 16 * _conv_stride_x; - unsigned int num_elems_written_per_iteration = 8; + bool is_kernel3x3_stride2 = ((kernel_size == 3) && (_conv_stride_x == 2)); + + const unsigned int num_elems_read_per_iteration_x = 8 + 2 * (kernel_size / 2) + (is_kernel3x3_stride2 ? 7 : 0); + const unsigned int num_elems_read_per_iteration_y = kernel_size; + const unsigned int num_elems_written_per_iteration_x = 8; + const unsigned int num_elems_written_per_iteration_y = 1; // Calculate right and bottom border - const int input_width = input->info()->dimension(0); - const int input_height = input->info()->dimension(1); - const int upper_bound_w = ceil_to_multiple(((output->info()->dimension(0) - 1) * _conv_stride_x + kernel_size), num_elems_read_per_iteration) - _conv_pad_x - input_width; - const int upper_bound_h = ((output->info()->dimension(1) - 1) * _conv_stride_y - _conv_pad_y + kernel_size) - input_height; - const int padding_right = std::max(upper_bound_w, static_cast(kernel_size)); - const int padding_bottom = std::max(upper_bound_h, static_cast(kernel_size)); + const int input_width = input->info()->dimension(0) - kernel_size / 2 + _conv_pad_x; + const int input_height = input->info()->dimension(1) - kernel_size / 2 + _conv_pad_y; // Create window and update padding - win = calculate_max_window(*output->info(), Steps(num_elems_written_per_iteration)); - AccessWindowStatic input_access(input->info(), -_conv_pad_x, -_conv_pad_y, input_width + padding_right, input_height + padding_bottom); + win = calculate_max_window(*output->info(), Steps(num_elems_written_per_iteration_x, num_elems_written_per_iteration_y)); + + AccessWindowStatic input_access(input->info(), -_conv_pad_x, -_conv_pad_y, input_width + num_elems_read_per_iteration_x, input_height + num_elems_read_per_iteration_y); + AccessWindowStatic weights_access(weights->info(), 0, 0, kernel_size, kernel_size); + AccessWindowRectangle output_access(output->info(), 0, 0, num_elems_written_per_iteration_x, num_elems_written_per_iteration_y); - AccessWindowStatic weights_access(weights->info(), 0, 0, kernel_size, kernel_size); - AccessWindowHorizontal output_access(output->info(), 0, num_elems_written_per_iteration); update_window_and_padding(win, input_access, weights_access, output_access); output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape())); @@ -158,6 +169,8 @@ void CLDirectConvolutionLayerKernel::run(const Window &window, cl::CommandQueue add_1D_tensor_argument(idx1, _biases, slice_biases); } + _kernel.setArg(idx1++, static_cast(_weights->info()->strides_in_bytes()[3])); + do { unsigned int idx = 0; -- cgit v1.2.1