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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2022 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 <memory>
#include <random>
#include "Eigen/Dense"
#include "benchmark/benchmark.h"
#include "ceres/block_jacobi_preconditioner.h"
#include "ceres/block_sparse_matrix.h"
#include "ceres/fake_bundle_adjustment_jacobian.h"
#include "ceres/internal/config.h"
#include "ceres/internal/eigen.h"
namespace ceres::internal {
constexpr int kNumCameras = 1000;
constexpr int kNumPoints = 10000;
constexpr int kCameraSize = 6;
constexpr int kPointSize = 3;
constexpr double kVisibility = 0.1;
constexpr int kNumRowBlocks = 100000;
constexpr int kNumColBlocks = 10000;
constexpr int kMinRowBlockSize = 1;
constexpr int kMaxRowBlockSize = 5;
constexpr int kMinColBlockSize = 1;
constexpr int kMaxColBlockSize = 15;
constexpr double kBlockDensity = 5.0 / kNumColBlocks;
static void BM_BlockSparseJacobiPreconditionerBA(benchmark::State& state) {
std::mt19937 prng;
auto jacobian = CreateFakeBundleAdjustmentJacobian(
kNumCameras, kNumPoints, kCameraSize, kPointSize, kVisibility, prng);
Preconditioner::Options preconditioner_options;
ContextImpl context;
preconditioner_options.context = &context;
preconditioner_options.num_threads = static_cast<int>(state.range(0));
context.EnsureMinimumThreads(preconditioner_options.num_threads);
BlockSparseJacobiPreconditioner p(preconditioner_options, *jacobian);
Vector d = Vector::Ones(jacobian->num_cols());
for (auto _ : state) {
p.Update(*jacobian, d.data());
}
}
BENCHMARK(BM_BlockSparseJacobiPreconditionerBA)
->Arg(1)
->Arg(2)
->Arg(4)
->Arg(8)
->Arg(16);
static void BM_BlockCRSJacobiPreconditionerBA(benchmark::State& state) {
std::mt19937 prng;
auto jacobian = CreateFakeBundleAdjustmentJacobian(
kNumCameras, kNumPoints, kCameraSize, kPointSize, kVisibility, prng);
CompressedRowSparseMatrix jacobian_crs(
jacobian->num_rows(), jacobian->num_cols(), jacobian->num_nonzeros());
jacobian->ToCompressedRowSparseMatrix(&jacobian_crs);
Preconditioner::Options preconditioner_options;
ContextImpl context;
preconditioner_options.context = &context;
preconditioner_options.num_threads = static_cast<int>(state.range(0));
context.EnsureMinimumThreads(preconditioner_options.num_threads);
BlockCRSJacobiPreconditioner p(preconditioner_options, jacobian_crs);
Vector d = Vector::Ones(jacobian_crs.num_cols());
for (auto _ : state) {
p.Update(jacobian_crs, d.data());
}
}
BENCHMARK(BM_BlockCRSJacobiPreconditionerBA)
->Arg(1)
->Arg(2)
->Arg(4)
->Arg(8)
->Arg(16);
static void BM_BlockSparseJacobiPreconditionerUnstructured(
benchmark::State& state) {
BlockSparseMatrix::RandomMatrixOptions options;
options.num_row_blocks = kNumRowBlocks;
options.num_col_blocks = kNumColBlocks;
options.min_row_block_size = kMinRowBlockSize;
options.min_col_block_size = kMinColBlockSize;
options.max_row_block_size = kMaxRowBlockSize;
options.max_col_block_size = kMaxColBlockSize;
options.block_density = kBlockDensity;
std::mt19937 prng;
auto jacobian = BlockSparseMatrix::CreateRandomMatrix(options, prng);
Preconditioner::Options preconditioner_options;
ContextImpl context;
preconditioner_options.context = &context;
preconditioner_options.num_threads = static_cast<int>(state.range(0));
context.EnsureMinimumThreads(preconditioner_options.num_threads);
BlockSparseJacobiPreconditioner p(preconditioner_options, *jacobian);
Vector d = Vector::Ones(jacobian->num_cols());
for (auto _ : state) {
p.Update(*jacobian, d.data());
}
}
BENCHMARK(BM_BlockSparseJacobiPreconditionerUnstructured)
->Arg(1)
->Arg(2)
->Arg(4)
->Arg(8)
->Arg(16);
static void BM_BlockCRSJacobiPreconditionerUnstructured(
benchmark::State& state) {
BlockSparseMatrix::RandomMatrixOptions options;
options.num_row_blocks = kNumRowBlocks;
options.num_col_blocks = kNumColBlocks;
options.min_row_block_size = kMinRowBlockSize;
options.min_col_block_size = kMinColBlockSize;
options.max_row_block_size = kMaxRowBlockSize;
options.max_col_block_size = kMaxColBlockSize;
options.block_density = kBlockDensity;
std::mt19937 prng;
auto jacobian = BlockSparseMatrix::CreateRandomMatrix(options, prng);
CompressedRowSparseMatrix jacobian_crs(
jacobian->num_rows(), jacobian->num_cols(), jacobian->num_nonzeros());
jacobian->ToCompressedRowSparseMatrix(&jacobian_crs);
Preconditioner::Options preconditioner_options;
ContextImpl context;
preconditioner_options.context = &context;
preconditioner_options.num_threads = static_cast<int>(state.range(0));
context.EnsureMinimumThreads(preconditioner_options.num_threads);
BlockCRSJacobiPreconditioner p(preconditioner_options, jacobian_crs);
Vector d = Vector::Ones(jacobian_crs.num_cols());
for (auto _ : state) {
p.Update(jacobian_crs, d.data());
}
}
BENCHMARK(BM_BlockCRSJacobiPreconditionerUnstructured)
->Arg(1)
->Arg(2)
->Arg(4)
->Arg(8)
->Arg(16);
} // namespace ceres::internal
BENCHMARK_MAIN();