Files
eigen/benchmarks/QR/bench_qr.cpp
Rasmus Munk Larsen 1f49bf96cf Add new benchmarks for Core, LU, and QR operations
libeigen/eigen!2177

Closes #3035

Co-authored-by: Rasmus Munk Larsen <rmlarsen@gmail.com>
2026-02-22 12:19:37 -08:00

124 lines
3.9 KiB
C++

// Benchmarks for QR decompositions.
//
// Tests HouseholderQR, ColPivHouseholderQR, FullPivHouseholderQR, and COD.
// Both square and tall-thin matrix shapes are tested.
#include <benchmark/benchmark.h>
#include <Eigen/QR>
using namespace Eigen;
template <typename QR>
EIGEN_DONT_INLINE void do_compute(QR& qr, const typename QR::MatrixType& A) {
qr.compute(A);
}
// --- HouseholderQR ---
template <typename Scalar>
static void BM_HouseholderQR(benchmark::State& state) {
const Index rows = state.range(0);
const Index cols = state.range(1);
using Mat = Matrix<Scalar, Dynamic, Dynamic>;
Mat A = Mat::Random(rows, cols);
HouseholderQR<Mat> qr(rows, cols);
for (auto _ : state) {
do_compute(qr, A);
benchmark::DoNotOptimize(qr.matrixQR().data());
}
state.SetItemsProcessed(state.iterations());
}
// --- ColPivHouseholderQR ---
template <typename Scalar>
static void BM_ColPivHouseholderQR(benchmark::State& state) {
const Index rows = state.range(0);
const Index cols = state.range(1);
using Mat = Matrix<Scalar, Dynamic, Dynamic>;
Mat A = Mat::Random(rows, cols);
ColPivHouseholderQR<Mat> qr(rows, cols);
for (auto _ : state) {
do_compute(qr, A);
benchmark::DoNotOptimize(qr.matrixQR().data());
}
state.SetItemsProcessed(state.iterations());
}
// --- FullPivHouseholderQR ---
template <typename Scalar>
static void BM_FullPivHouseholderQR(benchmark::State& state) {
const Index rows = state.range(0);
const Index cols = state.range(1);
using Mat = Matrix<Scalar, Dynamic, Dynamic>;
Mat A = Mat::Random(rows, cols);
FullPivHouseholderQR<Mat> qr(rows, cols);
for (auto _ : state) {
do_compute(qr, A);
benchmark::DoNotOptimize(qr.matrixQR().data());
}
state.SetItemsProcessed(state.iterations());
}
// --- CompleteOrthogonalDecomposition (COD) ---
template <typename Scalar>
static void BM_COD(benchmark::State& state) {
const Index rows = state.range(0);
const Index cols = state.range(1);
using Mat = Matrix<Scalar, Dynamic, Dynamic>;
Mat A = Mat::Random(rows, cols);
CompleteOrthogonalDecomposition<Mat> cod(rows, cols);
for (auto _ : state) {
do_compute(cod, A);
benchmark::DoNotOptimize(cod.matrixQTZ().data());
}
state.SetItemsProcessed(state.iterations());
}
// --- QR solve ---
template <typename Scalar>
static void BM_HouseholderQR_Solve(benchmark::State& state) {
const Index rows = state.range(0);
const Index cols = state.range(1);
using Mat = Matrix<Scalar, Dynamic, Dynamic>;
using Vec = Matrix<Scalar, Dynamic, 1>;
Mat A = Mat::Random(rows, cols);
Vec b = Vec::Random(rows);
HouseholderQR<Mat> qr(A);
Vec x(cols);
for (auto _ : state) {
x = qr.solve(b);
benchmark::DoNotOptimize(x.data());
}
state.SetItemsProcessed(state.iterations());
}
// --- Size configurations ---
static void QrSizes(::benchmark::Benchmark* b) {
// Square
for (int n : {32, 64, 128, 256, 512, 1024}) b->Args({n, n});
// Tall-thin
b->Args({1000, 32});
b->Args({1000, 100});
b->Args({10000, 32});
b->Args({10000, 100});
}
// Register: float
BENCHMARK(BM_HouseholderQR<float>)->Apply(QrSizes)->Name("HouseholderQR_float");
BENCHMARK(BM_ColPivHouseholderQR<float>)->Apply(QrSizes)->Name("ColPivHouseholderQR_float");
BENCHMARK(BM_FullPivHouseholderQR<float>)->Apply(QrSizes)->Name("FullPivHouseholderQR_float");
BENCHMARK(BM_COD<float>)->Apply(QrSizes)->Name("COD_float");
BENCHMARK(BM_HouseholderQR_Solve<float>)->Apply(QrSizes)->Name("HouseholderQR_Solve_float");
// Register: double
BENCHMARK(BM_HouseholderQR<double>)->Apply(QrSizes)->Name("HouseholderQR_double");
BENCHMARK(BM_ColPivHouseholderQR<double>)->Apply(QrSizes)->Name("ColPivHouseholderQR_double");
BENCHMARK(BM_FullPivHouseholderQR<double>)->Apply(QrSizes)->Name("FullPivHouseholderQR_double");
BENCHMARK(BM_COD<double>)->Apply(QrSizes)->Name("COD_double");
BENCHMARK(BM_HouseholderQR_Solve<double>)->Apply(QrSizes)->Name("HouseholderQR_Solve_double");