COMPMID-1687: Optimize CLGEMMMatrixMultiplyKernel for Mali-G76 - Part1
The current implementation is limited just to FP32
Change-Id: I185ab57e483e879d7c301e9cc3033efc8b41e244
Reviewed-on: https://review.mlplatform.org/389
Reviewed-by: Anthony Barbier <Anthony.barbier@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.cpp
new file mode 100644
index 0000000..1ecde3e
--- /dev/null
+++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.cpp
@@ -0,0 +1,308 @@
+/*
+ * Copyright (c) 2018 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 "arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyReshapedKernel.h"
+
+#include "arm_compute/core/AccessWindowStatic.h"
+#include "arm_compute/core/CL/CLHelpers.h"
+#include "arm_compute/core/CL/CLKernelLibrary.h"
+#include "arm_compute/core/CL/ICLTensor.h"
+#include "arm_compute/core/CL/OpenCL.h"
+#include "arm_compute/core/Error.h"
+#include "arm_compute/core/Helpers.h"
+#include "arm_compute/core/TensorInfo.h"
+#include "arm_compute/core/Types.h"
+#include "arm_compute/core/Utils.h"
+#include "arm_compute/core/Validate.h"
+#include "arm_compute/core/Window.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
+#include "support/ToolchainSupport.h"
+
+#include <cstddef>
+#include <cstdint>
+#include <tuple>
+
+using namespace arm_compute;
+using namespace arm_compute::misc::shape_calculator;
+
+namespace arm_compute
+{
+class Coordinates;
+} // namespace arm_compute
+
+namespace
+{
+using ElementsProcessed = Steps;
+
+Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, float alpha, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info,
+ const GEMMReshapeInfo &gemm_info)
+{
+ ARM_COMPUTE_UNUSED(alpha);
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input0, input1, output);
+ ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::F32, DataType::F16);
+ 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 LHS matrix must be <= 4");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG(input1->num_dimensions() > 3, "The number of dimensions for the RHS matrix must be <= 3");
+ ARM_COMPUTE_RETURN_ERROR_ON(lhs_info.transpose);
+ ARM_COMPUTE_RETURN_ERROR_ON(!rhs_info.transpose);
+ ARM_COMPUTE_RETURN_ERROR_ON(lhs_info.k0 != rhs_info.k0);
+ ARM_COMPUTE_RETURN_ERROR_ON(lhs_info.m0 < 2 || lhs_info.m0 > 8);
+
+ const int m = gemm_info.m();
+ const int n = gemm_info.n();
+ const int k = gemm_info.k();
+
+ 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);
+
+ if(output->total_size() != 0)
+ {
+ const TensorInfo tensor_info_output = output->clone()->set_tensor_shape(compute_mm_shape(*input0, *input1, gemm_info));
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &tensor_info_output);
+ ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, output);
+ }
+
+ return Status{};
+}
+
+std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input0, ITensorInfo *input1, ITensorInfo *output, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info,
+ const GEMMReshapeInfo &gemm_info, ElementsProcessed &num_elements_processed)
+{
+ 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_output_as_3d = (gemm_info.depth_output_gemm3d() != 0);
+
+ Window win{};
+ Window win_out{};
+ bool window_changed = false;
+
+ // Output tensor auto initialization if not yet initialized
+ auto_init_if_empty(*output, input0->clone()->set_tensor_shape(compute_mm_shape(*input0, *input1, gemm_info)));
+
+ TensorInfo tmp_info(*output);
+
+ if(reinterpret_output_as_3d)
+ {
+ // Since the output tensor has to be reinterpreted as 3D and the execute window is based on a 2D GEMM,
+ // the window needs to be constructed on the 2D collapsed version of the tensor
+ TensorShape tmp_shape(output->tensor_shape());
+ tmp_shape.collapse(2U, 1U);
+ tmp_info.set_tensor_shape(tmp_shape);
+ }
+
+ // Configure kernel window
+ num_elems_processed_per_iteration_x = rhs_info.n0;
+ num_elems_processed_per_iteration_y = lhs_info.m0;
+
+ // 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 = gemm_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;
+
+ 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,
+ ceil_to_multiple(input0->dimension(0), num_elems_processed_per_iteration_y),
+ input0->dimension(1));
+ 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
+
+ output_access.set_valid_region(win_out, ValidRegion(Coordinates(0, 0), output->tensor_shape()));
+
+ // Collapse along the Z direction
+ // This collapse needs to be here in order to tune the Z dimension of LWS
+ Window collapsed = win;
+ const unsigned int dimension_to_collapse = std::min(static_cast<unsigned int>(output->num_dimensions()), 2u);
+ collapsed = win.collapse(win, dimension_to_collapse);
+
+ Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{};
+ return std::make_pair(err, collapsed);
+}
+} // namespace
+
+CLGEMMMatrixMultiplyReshapedKernel::CLGEMMMatrixMultiplyReshapedKernel()
+ : _input0(nullptr), _input1(nullptr), _output(nullptr), _slide_matrix_b(true), _reinterpret_output_as_3d(false)
+{
+}
+
+void CLGEMMMatrixMultiplyReshapedKernel::configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, float alpha, const GEMMLHSMatrixInfo &lhs_info,
+ const GEMMRHSMatrixInfo &rhs_info, 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(), alpha, lhs_info, rhs_info, gemm_info));
+
+ _input0 = input0;
+ _input1 = input1;
+ _output = output;
+ _reinterpret_output_as_3d = (gemm_info.depth_output_gemm3d() != 0);
+
+ // Check if we need to slide the matrix B
+ const unsigned int num_dimensions_input0 = _input0->info()->num_dimensions();
+ _slide_matrix_b = (_input1->info()->num_dimensions() >= num_dimensions_input0);
+
+ ElementsProcessed num_elements_processed{};
+
+ // Configure kernel window
+ auto win_config = validate_and_configure_window(input0->info(), input1->info(), output->info(), lhs_info, rhs_info, gemm_info, num_elements_processed);
+ ARM_COMPUTE_ERROR_THROW_ON(win_config.first);
+ ICLKernel::configure_internal(win_config.second);
+
+ // Create build options
+ CLBuildOptions build_opts;
+ build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input0->info()->data_type()));
+ build_opts.add_option_if(std::abs(1.0f - alpha) > 0.00001f, "-DALPHA=" + float_to_string_with_full_precision(alpha));
+ build_opts.add_option_if(_reinterpret_output_as_3d, "-DREINTERPRET_OUTPUT_AS_3D");
+ build_opts.add_option_if(_reinterpret_output_as_3d, "-DHEIGHT_GEMM3D=" + support::cpp11::to_string(output->info()->dimension(1)));
+ build_opts.add_option_if(_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_if(lhs_info.interleave, "-DLHS_INTERLEAVE");
+ build_opts.add_option_if(rhs_info.interleave, "-DRHS_INTERLEAVE");
+ build_opts.add_option("-DK=" + support::cpp11::to_string(gemm_info.k()));
+ build_opts.add_option("-DM0=" + support::cpp11::to_string(lhs_info.m0));
+ build_opts.add_option("-DN0=" + support::cpp11::to_string(rhs_info.n0));
+ build_opts.add_option("-DK0=" + support::cpp11::to_string(lhs_info.k0));
+ build_opts.add_option("-DV0=" + support::cpp11::to_string(lhs_info.v0));
+ build_opts.add_option("-DH0=" + support::cpp11::to_string(rhs_info.h0));
+
+ std::string kernel_name("gemm_mm_reshaped_");
+ kernel_name += lhs_info.transpose ? "lhs_t_" : "lhs_nt_";
+ kernel_name += rhs_info.transpose ? "rhs_t" : "rhs_nt";
+
+ // Create kernel
+ _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts.options()));
+
+ // Set config_id for enabling LWS tuning
+ _config_id = kernel_name;
+ _config_id += "_";
+ _config_id += (_reinterpret_output_as_3d ? "3do_" : "");
+ _config_id += lower_string(string_from_data_type(input0->info()->data_type()));
+ _config_id += "_";
+ _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 += support::cpp11::to_string(gemm_info.k());
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(output->info()->dimension(2));
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(lhs_info.m0);
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(rhs_info.n0);
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(lhs_info.k0);
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(lhs_info.v0);
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(rhs_info.h0);
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(lhs_info.interleave);
+ _config_id += "_";
+ _config_id += support::cpp11::to_string(rhs_info.interleave);
+}
+
+Status CLGEMMMatrixMultiplyReshapedKernel::validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, float alpha, const GEMMLHSMatrixInfo &lhs_info,
+ const GEMMRHSMatrixInfo &rhs_info, const GEMMReshapeInfo &gemm_info)
+{
+ ElementsProcessed num_elements_processed{};
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input0, input1, output, alpha, lhs_info, rhs_info, gemm_info));
+ ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input0->clone().get(),
+ input1->clone().get(),
+ output->clone().get(),
+ lhs_info,
+ rhs_info,
+ gemm_info,
+ num_elements_processed)
+ .first);
+
+ return Status{};
+}
+
+void CLGEMMMatrixMultiplyReshapedKernel::run(const Window &window, cl::CommandQueue &queue)
+{
+ ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
+ ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window);
+
+ if(_input1->info()->num_dimensions() < 3)
+ {
+ // The stride_z for matrix B must be zero if we do not slice
+ ARM_COMPUTE_ERROR_ON(_input1->info()->strides_in_bytes()[3] != 0);
+ }
+
+ Window slice = window.first_slice_window_3D();
+ Window slice_matrix_b = slice;
+
+ slice_matrix_b.set(Window::DimX, Window::Dimension(0, 1, 1));
+ slice_matrix_b.set(Window::DimY, Window::Dimension(0, 1, 1));
+
+ if(_reinterpret_output_as_3d)
+ {
+ // Pass bottom paddings to the kernel if the output has to be reinterpreted as 3D tensor
+ const unsigned int idx0 = 3 * num_arguments_per_2D_tensor() + 3;
+ const unsigned int total_cross_plane_pad = _output->info()->padding().top + _output->info()->padding().bottom;
+ _kernel.setArg<cl_uint>(idx0, static_cast<unsigned int>(total_cross_plane_pad));
+ }
+
+ do
+ {
+ Window slice_b = slice;
+ // Don't slice matrix B along the z dimension if matrix B has just 2 dimensions and matrix A more than 2
+ // This scenario can happen when the matrix multiplication is used to perform a convolution operation
+ if(!_slide_matrix_b)
+ {
+ slice_b = slice_matrix_b;
+ }
+
+ unsigned int idx = 0;
+ add_2D_tensor_argument(idx, _input0, slice);
+ add_2D_tensor_argument(idx, _input1, slice_b);
+ add_2D_tensor_argument(idx, _output, slice);
+ _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input0->info()->strides_in_bytes()[2]));
+ _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_input1->info()->strides_in_bytes()[2]));
+ _kernel.setArg<cl_uint>(idx++, static_cast<unsigned int>(_output->info()->strides_in_bytes()[2]));
+ enqueue(queue, *this, slice, lws_hint());
+ }
+ while(window.slide_window_slice_3D(slice));
+}
\ No newline at end of file