| // Ceres Solver - A fast non-linear least squares minimizer |
| // Copyright 2022 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 |
| // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE |
| // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR |
| // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF |
| // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS |
| // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN |
| // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) |
| // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE |
| // POSSIBILITY OF SUCH DAMAGE. |
| // |
| // Authors: sameeragarwal@google.com (Sameer Agarwal) |
| |
| #include "Eigen/Dense" |
| #include "benchmark/benchmark.h" |
| #include "ceres/context_impl.h" |
| #include "ceres/dense_sparse_matrix.h" |
| #include "ceres/internal/config.h" |
| #include "ceres/linear_solver.h" |
| |
| namespace ceres::internal { |
| |
| template <ceres::DenseLinearAlgebraLibraryType kLibraryType, |
| ceres::LinearSolverType kSolverType> |
| static void BM_DenseSolver(benchmark::State& state) { |
| const int num_rows = state.range(0); |
| const int num_cols = state.range(1); |
| DenseSparseMatrix jacobian(num_rows, num_cols); |
| *jacobian.mutable_matrix() = Eigen::MatrixXd::Random(num_rows, num_cols); |
| Eigen::VectorXd rhs = Eigen::VectorXd::Random(num_rows, 1); |
| |
| Eigen::VectorXd solution(num_cols); |
| |
| LinearSolver::Options options; |
| options.type = kSolverType; |
| options.dense_linear_algebra_library_type = kLibraryType; |
| ContextImpl context; |
| options.context = &context; |
| auto solver = LinearSolver::Create(options); |
| |
| LinearSolver::PerSolveOptions per_solve_options; |
| Eigen::VectorXd diagonal = Eigen::VectorXd::Ones(num_cols) * 100; |
| per_solve_options.D = diagonal.data(); |
| for (auto _ : state) { |
| solver->Solve(&jacobian, rhs.data(), per_solve_options, solution.data()); |
| } |
| } |
| |
| // Some reasonable matrix sizes. I picked them out of thin air. |
| static void MatrixSizes(benchmark::internal::Benchmark* b) { |
| // {num_rows, num_cols} |
| b->Args({1, 1}); |
| b->Args({2, 1}); |
| b->Args({3, 1}); |
| b->Args({6, 2}); |
| b->Args({10, 3}); |
| b->Args({12, 4}); |
| b->Args({20, 5}); |
| b->Args({40, 5}); |
| b->Args({100, 10}); |
| b->Args({150, 15}); |
| b->Args({200, 16}); |
| b->Args({225, 18}); |
| b->Args({300, 20}); |
| b->Args({400, 20}); |
| b->Args({600, 22}); |
| b->Args({800, 25}); |
| } |
| |
| BENCHMARK_TEMPLATE2(BM_DenseSolver, ceres::EIGEN, ceres::DENSE_QR) |
| ->Apply(MatrixSizes); |
| BENCHMARK_TEMPLATE2(BM_DenseSolver, ceres::EIGEN, ceres::DENSE_NORMAL_CHOLESKY) |
| ->Apply(MatrixSizes); |
| |
| #ifndef CERES_NO_LAPACK |
| BENCHMARK_TEMPLATE2(BM_DenseSolver, ceres::LAPACK, ceres::DENSE_QR) |
| ->Apply(MatrixSizes); |
| BENCHMARK_TEMPLATE2(BM_DenseSolver, ceres::LAPACK, ceres::DENSE_NORMAL_CHOLESKY) |
| ->Apply(MatrixSizes); |
| #endif // CERES_NO_LAPACK |
| |
| #ifndef CERES_NO_CUDA |
| BENCHMARK_TEMPLATE2(BM_DenseSolver, ceres::CUDA, ceres::DENSE_NORMAL_CHOLESKY) |
| ->Apply(MatrixSizes); |
| BENCHMARK_TEMPLATE2(BM_DenseSolver, ceres::CUDA, ceres::DENSE_QR) |
| ->Apply(MatrixSizes); |
| #endif // CERES_NO_CUDA |
| |
| } // namespace ceres::internal |
| |
| BENCHMARK_MAIN(); |