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Migrate Eigen benchmarks to the Google benchmark framework

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libeigen/eigen!2132

Closes #3025

Co-authored-by: Rasmus Munk Larsen <rmlarsen@gmail.com>
This commit is contained in:
Rasmus Munk Larsen
2026-02-17 20:51:36 -08:00
parent 740cac97b4
commit 3108f6360e
23 changed files with 1632 additions and 0 deletions
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42
benchmarks/benchEigenSolver.cpp Normal file
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#include <benchmark/benchmark.h>
#include <Eigen/Core>
#include <Eigen/QR>
#include <Eigen/Eigenvalues>
using namespace Eigen;
typedef float Scalar;
static void BM_SelfAdjointEigenSolver(benchmark::State& state) {
int n = state.range(0);
typedef Matrix<Scalar, Dynamic, Dynamic> MatrixType;
MatrixType a = MatrixType::Random(n, n);
MatrixType covMat = a * a.adjoint();
int r = internal::random<int>(0, n - 1);
int c = internal::random<int>(0, n - 1);
Scalar acc = 0;
SelfAdjointEigenSolver<MatrixType> ei(covMat);
for (auto _ : state) {
ei.compute(covMat);
acc += ei.eigenvectors().coeff(r, c);
benchmark::DoNotOptimize(acc);
}
}
BENCHMARK(BM_SelfAdjointEigenSolver)->RangeMultiplier(2)->Range(4, 512);
static void BM_EigenSolver(benchmark::State& state) {
int n = state.range(0);
typedef Matrix<Scalar, Dynamic, Dynamic> MatrixType;
MatrixType a = MatrixType::Random(n, n);
MatrixType covMat = a * a.adjoint();
int r = internal::random<int>(0, n - 1);
int c = internal::random<int>(0, n - 1);
Scalar acc = 0;
EigenSolver<MatrixType> ei(covMat);
for (auto _ : state) {
ei.compute(covMat);
acc += std::norm(ei.eigenvectors().coeff(r, c));
benchmark::DoNotOptimize(acc);
}
}
BENCHMARK(BM_EigenSolver)->RangeMultiplier(2)->Range(4, 512);