mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-29 16:40:38 +08:00
Add a benchmark for dense linear solvers.
Change-Id: I06c39d62f4e0981be8ef5476b5f13b2b2a1fe794
This commit is contained in:
@@ -552,5 +552,8 @@ if (BUILD_BENCHMARKS)
|
||||
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)
|
||||
|
||||
@@ -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();
|
||||
Reference in New Issue
Block a user