From 06be6f8d2a316a307fa623150f8adf8f9c3416c5 Mon Sep 17 00:00:00 2001 From: Gian Marco Iodice Date: Mon, 24 Jun 2019 17:47:51 +0100 Subject: COMPMID-2096: Refactor the CLGEMMLowp function selection (heuristic) Change-Id: I15a8b39e0354d3b6686ed4cc8c361782c0512037 Signed-off-by: Gian Marco Iodice Reviewed-on: https://review.mlplatform.org/c/1410 Comments-Addressed: Arm Jenkins Tested-by: Arm Jenkins Reviewed-by: VidhyaSudhan Loganathan --- .../CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp | 201 ++++++--------------- 1 file changed, 56 insertions(+), 145 deletions(-) (limited to 'src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp') diff --git a/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp b/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp index 1a1a4b7c3d..cda7a83de7 100644 --- a/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp +++ b/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp @@ -55,63 +55,38 @@ namespace { using ElementsProcessed = Steps; -Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info) +Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, const GEMMReshapeInfo &gemm_info) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input0, input1, output); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::QASYMM8); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1); ARM_COMPUTE_RETURN_ERROR_ON_MSG(input0->num_dimensions() > 4, "The number of dimensions for the matrix A must be <= 4"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(input1->num_dimensions() > 3, "The number of dimensions for the matrix B must be <= 3"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(is_interleaved_transposed && reshape_info.reinterpret_input_as_3d(), "The input tensor cannot be reinterpreted as 3D if is_interleaved_transposed is true"); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(input1->num_dimensions() > 2 && reshape_info.reinterpret_input_as_3d(), "The input1 tensor cannot have more than 2 dimensions if input0 has to be reinterpreted as 3D"); + ARM_COMPUTE_RETURN_ERROR_ON_MSG(input1->num_dimensions() > 2 && gemm_info.reinterpret_input_as_3d(), "The input1 tensor cannot have more than 2 dimensions if input0 has to be reinterpreted as 3D"); - if(!is_interleaved_transposed) + const int m = gemm_info.m(); + const int n = gemm_info.n(); + const int k = gemm_info.k(); + + ARM_COMPUTE_UNUSED(m); + ARM_COMPUTE_UNUSED(n); + ARM_COMPUTE_UNUSED(k); + + ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(0) != static_cast(k)); + ARM_COMPUTE_RETURN_ERROR_ON(input1->dimension(0) != static_cast(n)); + ARM_COMPUTE_RETURN_ERROR_ON(input1->dimension(1) != static_cast(k)); + if(gemm_info.reinterpret_input_as_3d()) { - ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(0) != input1->dimension(1)); + ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(1) * input0->dimension(2) != static_cast(m)); } else { - GEMMRHSMatrixInfo rhs_info; - GEMMLHSMatrixInfo lhs_info; - const int m = reshape_info.m(); - const int n = reshape_info.n(); - const int k = reshape_info.k(); - const int mult_transpose1xW_width = reshape_info.mult_transpose1xW_width(); - const int mult_interleave4x4_height = reshape_info.mult_interleave4x4_height(); - const bool unroll_block = dot8_supported(CLKernelLibrary::get().get_device()); - - rhs_info.n0 = 16 / input1->element_size(); - rhs_info.k0 = 1; - rhs_info.h0 = mult_transpose1xW_width; - rhs_info.interleave = false; - rhs_info.transpose = false; - lhs_info.m0 = 4; - lhs_info.k0 = 4; - lhs_info.v0 = mult_interleave4x4_height; - lhs_info.interleave = true; - lhs_info.transpose = !unroll_block; - - TensorShape tensor_shape0{ input0->tensor_shape() }; - tensor_shape0.set(0, k); - tensor_shape0.set(1, m); - - TensorShape tensor_shape1{ input1->tensor_shape() }; - tensor_shape1.set(0, n); - tensor_shape1.set(1, k); - - const TensorInfo tensor_info0 = input0->clone()->set_tensor_shape(tensor_shape0); - const TensorInfo tensor_info1 = input1->clone()->set_tensor_shape(tensor_shape1); - - const TensorInfo tensor_info_reshaped0 = input0->clone()->set_tensor_shape(compute_lhs_reshaped_shape(tensor_info0, lhs_info)); - const TensorInfo tensor_info_reshaped1 = input1->clone()->set_tensor_shape(compute_rhs_reshaped_shape(tensor_info1, rhs_info)); - - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input0, &tensor_info_reshaped0); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input1, &tensor_info_reshaped1); + ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(1) != static_cast(m)); } if(output->total_size() != 0) { - const TensorInfo tensor_info_output = output->clone()->set_tensor_shape(compute_mm_shape(*input0, *input1, is_interleaved_transposed, reshape_info)); + const TensorInfo tensor_info_output = output->clone()->set_tensor_shape(compute_mm_shape(*input0, *input1, false, gemm_info)); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &tensor_info_output); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::S32); } @@ -119,14 +94,12 @@ Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *input1, return Status{}; } -std::pair validate_and_configure_window(ITensorInfo *input0, ITensorInfo *input1, ITensorInfo *output, bool is_interleaved_transposed, - const GEMMReshapeInfo &reshape_info, ElementsProcessed &num_elements_processed) +std::pair validate_and_configure_window(ITensorInfo *input0, ITensorInfo *input1, ITensorInfo *output, const GEMMReshapeInfo &gemm_info, ElementsProcessed &num_elements_processed) { - const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device()); unsigned int &num_elems_processed_per_iteration_x = num_elements_processed[0]; unsigned int &num_elems_processed_per_iteration_y = num_elements_processed[1]; - bool reinterpret_input_as_3d = reshape_info.reinterpret_input_as_3d(); - bool reinterpret_output_as_3d = (reshape_info.depth_output_gemm3d() != 0); + bool reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d(); + bool reinterpret_output_as_3d = (gemm_info.depth_output_gemm3d() != 0); Window win{}; Window win_out{}; @@ -141,7 +114,7 @@ std::pair validate_and_configure_window(ITensorInfo *input0, ITe } // Output tensor auto inizialitation if not yet initialized - auto_init_if_empty(*output, input0->clone()->set_tensor_shape(compute_mm_shape(*input0, *input1, is_interleaved_transposed, reshape_info)).set_data_type(DataType::S32)); + auto_init_if_empty(*output, input0->clone()->set_tensor_shape(compute_mm_shape(*input0, *input1, false, gemm_info)).set_data_type(DataType::S32)); TensorInfo tmp_info(*output); @@ -154,66 +127,32 @@ std::pair validate_and_configure_window(ITensorInfo *input0, ITe tmp_info.set_tensor_shape(tmp_shape); } - // Check if the output tensor is a vector. If so,the kernel runs the vector-matrix multiplication - if(is_interleaved_transposed) - { - // reinterpret_input_as_3d is not supported if is_interleaved_transposed is set - ARM_COMPUTE_ERROR_ON(reshape_info.reinterpret_input_as_3d()); + // Special case for 1xN, 2xN, 3xN and 4xN input0 tensor. num_elems_processed_per_iteration_x + // Note: if the dot product instruction is available, the 8x2 tile has to be used + num_elems_processed_per_iteration_x = 4; + num_elems_processed_per_iteration_y = std::min(static_cast(output->dimension(1)), 4); - // Configure kernel window - num_elems_processed_per_iteration_x = 4; - num_elems_processed_per_iteration_y = 4; + // Note: bottom paddings are calculated manually as the output can be reinterpreted as 3D tensor + // The only way to set properly the paddings, it is to set those explicitly through the AccessWindowStatic + const int m = reinterpret_input_as_3d ? input0->tensor_shape()[1] * input0->tensor_shape()[2] : input0->tensor_shape()[1]; + const int bottom_pad = (num_elems_processed_per_iteration_y - (m % num_elems_processed_per_iteration_y)) % num_elems_processed_per_iteration_y; - // Note: bottom paddings are calculated manually as the output can be reinterpreted as 3D tensor - // The only way to set properly the paddings, it is to set those explicitly through the AccessWindowStatic - const int m = reshape_info.m(); - const int bottom_pad = (num_elems_processed_per_iteration_y - (m % num_elems_processed_per_iteration_y)) % num_elems_processed_per_iteration_y; + // Configure window + win = calculate_max_window(tmp_info, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); + win_out = calculate_max_window(*output, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); - win = calculate_max_window(tmp_info, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); - win_out = calculate_max_window(*output, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); + AccessWindowStatic input0_access(input0, 0, 0, input0->dimension(0), input0->dimension(1) + bottom_pad); + AccessWindowStatic input1_access(input1, 0, 0, ceil_to_multiple(input1->dimension(0), num_elems_processed_per_iteration_x), input1->dimension(1)); + AccessWindowStatic output_access(output, 0, 0, + ceil_to_multiple(output->dimension(0), num_elems_processed_per_iteration_x), + output->dimension(1) + bottom_pad); - AccessWindowRectangle input0_access(input0, 0, 0, num_elems_processed_per_iteration_y, 1, 1.f, 0.25f); - AccessWindowStatic input1_access(input1, 0, 0, - ceil_to_multiple(input1->dimension(0), num_elems_processed_per_iteration_x), - ceil_to_multiple(input1->dimension(1), num_elems_processed_per_iteration_y)); - AccessWindowStatic output_access(output, 0, 0, - ceil_to_multiple(output->dimension(0), num_elems_processed_per_iteration_x), - output->dimension(1) + bottom_pad); + window_changed = update_window_and_padding(win, input0_access, input1_access) || // window used by the execute_window_loop + update_window_and_padding(win_out, output_access); // window used to update the padding requirements of output tensor - window_changed = update_window_and_padding(win, input0_access, input1_access) || // window used by the execute_window_loop - update_window_and_padding(win_out, output_access); // window used to update the padding requirements of output tensor - - output_access.set_valid_region(win_out, ValidRegion(Coordinates(0, 0), output->tensor_shape())); - } - else - { - // Special case for 1xN, 2xN, 3xN and 4xN input0 tensor. num_elems_processed_per_iteration_x - // Note: if the dot product instruction is available, the 8x2 tile has to be used - num_elems_processed_per_iteration_x = is_dot8_supported ? 8 : 4; - num_elems_processed_per_iteration_y = std::min(static_cast(output->dimension(1)), is_dot8_supported ? 2 : 4); - - // Note: bottom paddings are calculated manually as the output can be reinterpreted as 3D tensor - // The only way to set properly the paddings, it is to set those explicitly through the AccessWindowStatic - const int m = reinterpret_input_as_3d ? input0->tensor_shape()[1] * input0->tensor_shape()[2] : input0->tensor_shape()[1]; - const int bottom_pad = (num_elems_processed_per_iteration_y - (m % num_elems_processed_per_iteration_y)) % num_elems_processed_per_iteration_y; - - // Configure window - win = calculate_max_window(tmp_info, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); - win_out = calculate_max_window(*output, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); - - AccessWindowStatic input0_access(input0, 0, 0, input0->dimension(0), input0->dimension(1) + bottom_pad); - AccessWindowStatic input1_access(input1, 0, 0, ceil_to_multiple(input1->dimension(0), num_elems_processed_per_iteration_x), input1->dimension(1)); - AccessWindowStatic output_access(output, 0, 0, - ceil_to_multiple(output->dimension(0), num_elems_processed_per_iteration_x), - output->dimension(1) + bottom_pad); - - window_changed = update_window_and_padding(win, input0_access, input1_access) || // window used by the execute_window_loop - update_window_and_padding(win_out, output_access); // window used to update the padding requirements of output tensor - - Coordinates coord; - coord.set_num_dimensions(output->num_dimensions()); - output_access.set_valid_region(win_out, ValidRegion(coord, output->tensor_shape())); - } + Coordinates coord; + coord.set_num_dimensions(output->num_dimensions()); + output_access.set_valid_region(win_out, ValidRegion(coord, output->tensor_shape())); // Collapse along the Z direction // This collapse needs to be here in order to tune the Z dimension of LWS @@ -231,17 +170,17 @@ CLGEMMLowpMatrixMultiplyKernel::CLGEMMLowpMatrixMultiplyKernel() { } -void CLGEMMLowpMatrixMultiplyKernel::configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info) +void CLGEMMLowpMatrixMultiplyKernel::configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, const GEMMReshapeInfo &gemm_info) { ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output); - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), output->info(), is_interleaved_transposed, reshape_info)); + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), output->info(), gemm_info)); _input0 = input0; _input1 = input1; _output = output; - _reinterpret_input_as_3d = reshape_info.reinterpret_input_as_3d(); - _reinterpret_output_as_3d = (reshape_info.depth_output_gemm3d() != 0); + _reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d(); + _reinterpret_output_as_3d = (gemm_info.depth_output_gemm3d() != 0); // In case both input and output have to be reinterpreted as 3D tensors, // force reinterpret_input_as_3d and reinterpret_output_as_3d to be false. @@ -257,16 +196,11 @@ void CLGEMMLowpMatrixMultiplyKernel::configure(const ICLTensor *input0, const IC ElementsProcessed num_elements_processed{}; - // Get target architecture - GPUTarget arch_target = get_arch_from_target(get_target()); - // Configure kernel window - auto win_config = validate_and_configure_window(input0->info(), input1->info(), output->info(), is_interleaved_transposed, reshape_info, num_elements_processed); + auto win_config = validate_and_configure_window(input0->info(), input1->info(), output->info(), gemm_info, num_elements_processed); ARM_COMPUTE_ERROR_THROW_ON(win_config.first); ICLKernel::configure_internal(win_config.second); - const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device()); - // Create build options std::string kernel_name(" "); CLBuildOptions build_opts; @@ -275,38 +209,18 @@ void CLGEMMLowpMatrixMultiplyKernel::configure(const ICLTensor *input0, const IC build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(output->info()->dimension(1))); build_opts.add_option_if(_reinterpret_input_as_3d || _reinterpret_output_as_3d, "-DDEPTH_GEMM3D=" + support::cpp11::to_string(output->info()->dimension(2))); build_opts.add_option_if(!_slide_matrix_b, "-DMATRIX_B_DEPTH=" + support::cpp11::to_string(input1->info()->dimension(2))); + build_opts.add_option("-DCOLS_A=" + support::cpp11::to_string(input0->info()->dimension(0))); + build_opts.add_option("-DNUM_ELEMS_PROCESSED_PER_THREAD_X=" + support::cpp11::to_string(num_elements_processed.x())); + build_opts.add_option("-DNUM_ELEMS_PROCESSED_PER_THREAD_Y=" + support::cpp11::to_string(num_elements_processed.y())); - if(is_interleaved_transposed) - { - const int mult_transpose1xW_width = reshape_info.mult_transpose1xW_width(); - const int mult_interleave4x4_height = reshape_info.mult_interleave4x4_height(); - - // Note: The computation tile has the x dimension equal to 4 which is less than the transpose_width (16) - // In order to access correctly the elements from the transposed matrix B, we need to pass - // the correct step which is calculated as (16 * mult_transpose1xW_width) / 4) - - build_opts.add_option("-DCOLS_B=" + support::cpp11::to_string(input1->info()->dimension(0))); - build_opts.add_option("-DMULT_TRANSPOSE1XW_WIDTH=" + support::cpp11::to_string(mult_transpose1xW_width)); - build_opts.add_option("-DTRANSPOSE1XW_WIDTH_STEP=" + support::cpp11::to_string(4 * mult_transpose1xW_width)); - build_opts.add_option("-DMULT_INTERLEAVE4X4_HEIGHT=" + support::cpp11::to_string(mult_interleave4x4_height)); - - kernel_name = "gemmlowp_mm_interleaved_transposed_" + string_from_target(arch_target) + (is_dot8_supported ? "_dot8" : ""); - } - else - { - build_opts.add_option("-DCOLS_A=" + support::cpp11::to_string(input0->info()->dimension(0))); - build_opts.add_option("-DNUM_ELEMS_PROCESSED_PER_THREAD_X=" + support::cpp11::to_string(num_elements_processed.x())); - build_opts.add_option("-DNUM_ELEMS_PROCESSED_PER_THREAD_Y=" + support::cpp11::to_string(num_elements_processed.y())); - - kernel_name = "gemmlowp_mm_" + string_from_target(arch_target) + (is_dot8_supported ? "_dot8" : ""); - } + kernel_name = "gemmlowp_mm_midgard"; // Create kernel _kernel = static_cast(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options())); // Set config_id for enabling LWS tuning - _config_id = "gemmlowp_"; - _config_id += (is_interleaved_transposed ? "reshaped_" : ""); + _config_id = kernel_name; + _config_id += "_"; _config_id += (_reinterpret_input_as_3d ? "3di_" : ""); _config_id += (_reinterpret_output_as_3d ? "3do_" : ""); _config_id += lower_string(string_from_data_type(input0->info()->data_type())); @@ -314,19 +228,16 @@ void CLGEMMLowpMatrixMultiplyKernel::configure(const ICLTensor *input0, const IC _config_id += support::cpp11::to_string(output->info()->dimension(1)); _config_id += "_"; _config_id += support::cpp11::to_string(output->info()->dimension(0)); - _config_id += "_"; - _config_id += (is_interleaved_transposed ? support::cpp11::to_string(input1->info()->dimension(0)) : support::cpp11::to_string(input1->info()->dimension(1))); } -Status CLGEMMLowpMatrixMultiplyKernel::validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info) +Status CLGEMMLowpMatrixMultiplyKernel::validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, const GEMMReshapeInfo &gemm_info) { ElementsProcessed num_elements_processed{}; - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input0, input1, output, is_interleaved_transposed, reshape_info)); + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input0, input1, output, gemm_info)); ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input0->clone().get(), input1->clone().get(), output->clone().get(), - is_interleaved_transposed, - reshape_info, + gemm_info, num_elements_processed) .first); -- cgit v1.2.1