mirror of
https://gitlab.com/libeigen/eigen.git
synced 2026-04-10 11:34:33 +08:00
104 lines
3.5 KiB
C++
104 lines
3.5 KiB
C++
#include <benchmark/benchmark.h>
|
|
#include <Eigen/Dense>
|
|
|
|
using namespace Eigen;
|
|
|
|
// Benchmark JacobiSVD and BDCSVD for various scalar types, matrix shapes,
|
|
// and computation options.
|
|
|
|
// ---------- helpers ----------
|
|
|
|
template <typename Scalar>
|
|
using Mat = Matrix<Scalar, Dynamic, Dynamic>;
|
|
|
|
template <typename SVD>
|
|
EIGEN_DONT_INLINE void do_compute(SVD& svd, const typename SVD::MatrixType& A) {
|
|
svd.compute(A);
|
|
}
|
|
|
|
// ---------- JacobiSVD ----------
|
|
|
|
template <typename Scalar, int Options>
|
|
static void BM_JacobiSVD(benchmark::State& state) {
|
|
const Index rows = state.range(0);
|
|
const Index cols = state.range(1);
|
|
Mat<Scalar> A = Mat<Scalar>::Random(rows, cols);
|
|
JacobiSVD<Mat<Scalar>, Options> svd(rows, cols);
|
|
for (auto _ : state) {
|
|
do_compute(svd, A);
|
|
benchmark::DoNotOptimize(svd.singularValues().data());
|
|
}
|
|
state.SetItemsProcessed(state.iterations());
|
|
}
|
|
|
|
// ---------- BDCSVD ----------
|
|
|
|
template <typename Scalar, int Options>
|
|
static void BM_BDCSVD(benchmark::State& state) {
|
|
const Index rows = state.range(0);
|
|
const Index cols = state.range(1);
|
|
Mat<Scalar> A = Mat<Scalar>::Random(rows, cols);
|
|
BDCSVD<Mat<Scalar>, Options> svd(rows, cols);
|
|
for (auto _ : state) {
|
|
do_compute(svd, A);
|
|
benchmark::DoNotOptimize(svd.singularValues().data());
|
|
}
|
|
state.SetItemsProcessed(state.iterations());
|
|
}
|
|
|
|
// ---------- Size configurations ----------
|
|
|
|
// Sizes suitable for JacobiSVD (O(n^2 p), expensive for large n).
|
|
static void JacobiSizes(::benchmark::Benchmark* b) {
|
|
// Square
|
|
for (int s : {4, 8, 16, 32, 64, 128, 256, 512}) b->Args({s, s});
|
|
// Tall-skinny
|
|
b->Args({100, 4});
|
|
b->Args({1000, 4});
|
|
b->Args({1000, 10});
|
|
}
|
|
|
|
// Sizes suitable for BDCSVD (divide-and-conquer, faster for large matrices).
|
|
static void BDCSizes(::benchmark::Benchmark* b) {
|
|
// Square
|
|
for (int s : {4, 8, 16, 32, 64, 128, 256, 512, 1024}) b->Args({s, s});
|
|
// Tall-skinny (triggers R-bidiagonalization when aspect ratio > 4)
|
|
b->Args({100, 4});
|
|
b->Args({1000, 4});
|
|
b->Args({1000, 10});
|
|
b->Args({1000, 100});
|
|
b->Args({10000, 10});
|
|
b->Args({10000, 100});
|
|
}
|
|
|
|
// ---------- Register benchmarks ----------
|
|
|
|
// JacobiSVD — float
|
|
BENCHMARK(BM_JacobiSVD<float, ComputeThinU | ComputeThinV>)->Apply(JacobiSizes)->Name("JacobiSVD_float_ThinUV");
|
|
BENCHMARK(BM_JacobiSVD<float, 0>)->Apply(JacobiSizes)->Name("JacobiSVD_float_ValuesOnly");
|
|
|
|
// JacobiSVD — double
|
|
BENCHMARK(BM_JacobiSVD<double, ComputeThinU | ComputeThinV>)->Apply(JacobiSizes)->Name("JacobiSVD_double_ThinUV");
|
|
BENCHMARK(BM_JacobiSVD<double, 0>)->Apply(JacobiSizes)->Name("JacobiSVD_double_ValuesOnly");
|
|
|
|
// BDCSVD — float
|
|
BENCHMARK(BM_BDCSVD<float, ComputeThinU | ComputeThinV>)->Apply(BDCSizes)->Name("BDCSVD_float_ThinUV");
|
|
BENCHMARK(BM_BDCSVD<float, 0>)->Apply(BDCSizes)->Name("BDCSVD_float_ValuesOnly");
|
|
|
|
// BDCSVD — double
|
|
BENCHMARK(BM_BDCSVD<double, ComputeThinU | ComputeThinV>)->Apply(BDCSizes)->Name("BDCSVD_double_ThinUV");
|
|
BENCHMARK(BM_BDCSVD<double, 0>)->Apply(BDCSizes)->Name("BDCSVD_double_ValuesOnly");
|
|
|
|
// JacobiSVD — QR preconditioner comparison (double, 64x64, ThinUV)
|
|
BENCHMARK(BM_JacobiSVD<double, ComputeThinU | ComputeThinV | ColPivHouseholderQRPreconditioner>)
|
|
->Args({64, 64})
|
|
->Args({1000, 10})
|
|
->Name("JacobiSVD_double_ColPivQR");
|
|
BENCHMARK(BM_JacobiSVD<double, ComputeThinU | ComputeThinV | HouseholderQRPreconditioner>)
|
|
->Args({64, 64})
|
|
->Args({1000, 10})
|
|
->Name("JacobiSVD_double_HouseholderQR");
|
|
BENCHMARK(BM_JacobiSVD<double, ComputeFullU | ComputeFullV | FullPivHouseholderQRPreconditioner>)
|
|
->Args({64, 64})
|
|
->Name("JacobiSVD_double_FullPivQR");
|