Add a benchmark for dense linear solvers. Change-Id: I06c39d62f4e0981be8ef5476b5f13b2b2a1fe794
diff --git a/internal/ceres/CMakeLists.txt b/internal/ceres/CMakeLists.txt index 018c5b4..5d9e0ab 100644 --- a/internal/ceres/CMakeLists.txt +++ b/internal/ceres/CMakeLists.txt
@@ -552,5 +552,8 @@ add_executable(jet_operator_benchmark jet_operator_benchmark.cc) add_dependencies_to_benchmark(jet_operator_benchmark) + add_executable(dense_linear_solver_benchmark dense_linear_solver_benchmark.cc) + add_dependencies_to_benchmark(dense_linear_solver_benchmark) + add_subdirectory(autodiff_benchmarks) endif (BUILD_BENCHMARKS)
diff --git a/internal/ceres/dense_linear_solver_benchmark.cc b/internal/ceres/dense_linear_solver_benchmark.cc new file mode 100644 index 0000000..e949eb8 --- /dev/null +++ b/internal/ceres/dense_linear_solver_benchmark.cc
@@ -0,0 +1,103 @@ +// 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/linear_solver.h" +#include "ceres/random.h" + +namespace ceres { +namespace 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); + constexpr bool kReserveDiagonal = true; + + DenseSparseMatrix jacobian(num_rows, num_cols, kReserveDiagonal); + 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(BM_DenseSolver<ceres::EIGEN, ceres::DENSE_QR>)->Apply(MatrixSizes); +BENCHMARK(BM_DenseSolver<ceres::EIGEN, ceres::DENSE_NORMAL_CHOLESKY>) + ->Apply(MatrixSizes); + +#ifndef CERES_NO_LAPACK +BENCHMARK(BM_DenseSolver<ceres::LAPACK, ceres::DENSE_QR>)->Apply(MatrixSizes); +BENCHMARK(BM_DenseSolver<ceres::LAPACK, ceres::DENSE_NORMAL_CHOLESKY>) + ->Apply(MatrixSizes); +#endif + +} // namespace internal +} // namespace ceres + +BENCHMARK_MAIN();