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();
