Vehicle-cpp/zjw/ceres-solver-master/internal/ceres/dense_linear_solver_benchmark.cc

// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2023 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
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// modification, are permitted provided that the following conditions are met:
//
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// 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 = static_cast<int>(state.range(0));
  const int num_cols = static_cast<int>(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();