| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2018 Google Inc. All rights reserved. |
| // http://ceres-solver.org/ |
| // |
| // Redistribution and use in source and binary forms, with or without |
| // modification, are permitted provided that the following conditions are met: |
| // |
| // * Redistributions of source code must retain the above copyright notice, |
| // this list of conditions and the following disclaimer. |
| // * Redistributions in binary form must reproduce the above copyright notice, |
| // this list of conditions and the following disclaimer in the documentation |
| // and/or other materials provided with the distribution. |
| // * Neither the name of Google Inc. nor the names of its contributors may be |
| // used to endorse or promote products derived from this software without |
| // specific prior written permission. |
| // |
| // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" |
| // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE |
| // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE |
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| // POSSIBILITY OF SUCH DAMAGE. |
| // |
| // Authors: sameeragarwal@google.com (Sameer Agarwal) |
| |
| #include "Eigen/Dense" |
| #include "benchmark/benchmark.h" |
| #include "ceres/small_blas.h" |
| |
| namespace ceres { |
| |
| // Benchmarking matrix-vector multiply routines and optimizing memory |
| // access requires that we make sure that they are not just sitting in |
| // the cache. So, as the benchmarking routine iterates, we need to |
| // multiply new/different matrice and vectors. Allocating/creating |
| // these objects in the benchmarking loop is too heavy duty, so we |
| // create them before hand and cycle through them in the |
| // benchmark. This class, given the size of the matrix creates such |
| // matrix and vector objects for use in the benchmark. |
| class MatrixVectorMultiplyData { |
| public: |
| MatrixVectorMultiplyData(int rows, int cols) |
| : num_elements_(1000), |
| rows_(rows), |
| cols_(cols), |
| a_(num_elements_ * rows, 1.001), |
| b_(num_elements_ * rows * cols, 1.5), |
| c_(num_elements_ * cols, 1.00003) {} |
| |
| int num_elements() const { return num_elements_; } |
| double* GetA(int i) { return &a_[i * rows_]; } |
| double* GetB(int i) { return &b_[i * rows_ * cols_]; } |
| double* GetC(int i) { return &c_[i * cols_]; } |
| |
| private: |
| const int num_elements_; |
| const int rows_; |
| const int cols_; |
| std::vector<double> a_; |
| std::vector<double> b_; |
| std::vector<double> c_; |
| }; |
| |
| // Helper function to generate the various matrix sizes for which we |
| // run the benchmark. |
| static void MatrixSizeArguments(benchmark::internal::Benchmark* benchmark) { |
| std::vector<int> rows = {1, 2, 3, 4, 6, 8}; |
| std::vector<int> cols = {1, 2, 3, 4, 8, 12, 15}; |
| for (int r : rows) { |
| for (int c : cols) { |
| benchmark->Args({r, c}); |
| } |
| } |
| } |
| |
| void BM_MatrixVectorMultiply(benchmark::State& state) { |
| const int rows = state.range(0); |
| const int cols = state.range(1); |
| MatrixVectorMultiplyData data(rows, cols); |
| const int num_elements = data.num_elements(); |
| int iter = 0; |
| for (auto _ : state) { |
| // A += B * C; |
| internal::MatrixVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>( |
| data.GetB(iter), rows, cols, data.GetC(iter), data.GetA(iter)); |
| iter = (iter + 1) % num_elements; |
| } |
| } |
| |
| BENCHMARK(BM_MatrixVectorMultiply)->Apply(MatrixSizeArguments); |
| |
| void BM_MatrixTransposeVectorMultiply(benchmark::State& state) { |
| const int rows = state.range(0); |
| const int cols = state.range(1); |
| MatrixVectorMultiplyData data(cols, rows); |
| const int num_elements = data.num_elements(); |
| int iter = 0; |
| for (auto _ : state) { |
| internal::MatrixTransposeVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>( |
| data.GetB(iter), rows, cols, data.GetC(iter), data.GetA(iter)); |
| iter = (iter + 1) % num_elements; |
| } |
| } |
| |
| BENCHMARK(BM_MatrixTransposeVectorMultiply)->Apply(MatrixSizeArguments); |
| |
| } // namespace ceres |
| |
| BENCHMARK_MAIN(); |