diff options
Diffstat (limited to 'src/core/CL/kernels')
-rw-r--r-- | src/core/CL/kernels/CLDepthwiseConvolution3x3Kernel.cpp | 57 | ||||
-rw-r--r-- | src/core/CL/kernels/CLDepthwiseIm2ColKernel.cpp | 10 | ||||
-rw-r--r-- | src/core/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.cpp | 10 |
3 files changed, 57 insertions, 20 deletions
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<cl::Kernel>(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<cl::Kernel>(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<cl::Kernel>(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)); } |