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- // g++ -DNDEBUG -O3 -I.. benchEigenSolver.cpp -o benchEigenSolver && ./benchEigenSolver
- // options:
- // -DBENCH_GMM
- // -DBENCH_GSL -lgsl /usr/lib/libcblas.so.3
- // -DEIGEN_DONT_VECTORIZE
- // -msse2
- // -DREPEAT=100
- // -DTRIES=10
- // -DSCALAR=double
- #include <iostream>
- #include <Eigen/Core>
- #include <Eigen/QR>
- #include <bench/BenchUtil.h>
- using namespace Eigen;
- #ifndef REPEAT
- #define REPEAT 1000
- #endif
- #ifndef TRIES
- #define TRIES 4
- #endif
- #ifndef SCALAR
- #define SCALAR float
- #endif
- typedef SCALAR Scalar;
- template <typename MatrixType>
- __attribute__ ((noinline)) void benchEigenSolver(const MatrixType& m)
- {
- int rows = m.rows();
- int cols = m.cols();
- int stdRepeats = std::max(1,int((REPEAT*1000)/(rows*rows*sqrt(rows))));
- int saRepeats = stdRepeats * 4;
- typedef typename MatrixType::Scalar Scalar;
- typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> SquareMatrixType;
- MatrixType a = MatrixType::Random(rows,cols);
- SquareMatrixType covMat = a * a.adjoint();
- BenchTimer timerSa, timerStd;
- Scalar acc = 0;
- int r = internal::random<int>(0,covMat.rows()-1);
- int c = internal::random<int>(0,covMat.cols()-1);
- {
- SelfAdjointEigenSolver<SquareMatrixType> ei(covMat);
- for (int t=0; t<TRIES; ++t)
- {
- timerSa.start();
- for (int k=0; k<saRepeats; ++k)
- {
- ei.compute(covMat);
- acc += ei.eigenvectors().coeff(r,c);
- }
- timerSa.stop();
- }
- }
- {
- EigenSolver<SquareMatrixType> ei(covMat);
- for (int t=0; t<TRIES; ++t)
- {
- timerStd.start();
- for (int k=0; k<stdRepeats; ++k)
- {
- ei.compute(covMat);
- acc += ei.eigenvectors().coeff(r,c);
- }
- timerStd.stop();
- }
- }
- if (MatrixType::RowsAtCompileTime==Dynamic)
- std::cout << "dyn ";
- else
- std::cout << "fixed ";
- std::cout << covMat.rows() << " \t"
- << timerSa.value() * REPEAT / saRepeats << "s \t"
- << timerStd.value() * REPEAT / stdRepeats << "s";
- #ifdef BENCH_GMM
- if (MatrixType::RowsAtCompileTime==Dynamic)
- {
- timerSa.reset();
- timerStd.reset();
- gmm::dense_matrix<Scalar> gmmCovMat(covMat.rows(),covMat.cols());
- gmm::dense_matrix<Scalar> eigvect(covMat.rows(),covMat.cols());
- std::vector<Scalar> eigval(covMat.rows());
- eiToGmm(covMat, gmmCovMat);
- for (int t=0; t<TRIES; ++t)
- {
- timerSa.start();
- for (int k=0; k<saRepeats; ++k)
- {
- gmm::symmetric_qr_algorithm(gmmCovMat, eigval, eigvect);
- acc += eigvect(r,c);
- }
- timerSa.stop();
- }
- // the non-selfadjoint solver does not compute the eigen vectors
- // for (int t=0; t<TRIES; ++t)
- // {
- // timerStd.start();
- // for (int k=0; k<stdRepeats; ++k)
- // {
- // gmm::implicit_qr_algorithm(gmmCovMat, eigval, eigvect);
- // acc += eigvect(r,c);
- // }
- // timerStd.stop();
- // }
- std::cout << " | \t"
- << timerSa.value() * REPEAT / saRepeats << "s"
- << /*timerStd.value() * REPEAT / stdRepeats << "s"*/ " na ";
- }
- #endif
- #ifdef BENCH_GSL
- if (MatrixType::RowsAtCompileTime==Dynamic)
- {
- timerSa.reset();
- timerStd.reset();
- gsl_matrix* gslCovMat = gsl_matrix_alloc(covMat.rows(),covMat.cols());
- gsl_matrix* gslCopy = gsl_matrix_alloc(covMat.rows(),covMat.cols());
- gsl_matrix* eigvect = gsl_matrix_alloc(covMat.rows(),covMat.cols());
- gsl_vector* eigval = gsl_vector_alloc(covMat.rows());
- gsl_eigen_symmv_workspace* eisymm = gsl_eigen_symmv_alloc(covMat.rows());
-
- gsl_matrix_complex* eigvectz = gsl_matrix_complex_alloc(covMat.rows(),covMat.cols());
- gsl_vector_complex* eigvalz = gsl_vector_complex_alloc(covMat.rows());
- gsl_eigen_nonsymmv_workspace* einonsymm = gsl_eigen_nonsymmv_alloc(covMat.rows());
-
- eiToGsl(covMat, &gslCovMat);
- for (int t=0; t<TRIES; ++t)
- {
- timerSa.start();
- for (int k=0; k<saRepeats; ++k)
- {
- gsl_matrix_memcpy(gslCopy,gslCovMat);
- gsl_eigen_symmv(gslCopy, eigval, eigvect, eisymm);
- acc += gsl_matrix_get(eigvect,r,c);
- }
- timerSa.stop();
- }
- for (int t=0; t<TRIES; ++t)
- {
- timerStd.start();
- for (int k=0; k<stdRepeats; ++k)
- {
- gsl_matrix_memcpy(gslCopy,gslCovMat);
- gsl_eigen_nonsymmv(gslCopy, eigvalz, eigvectz, einonsymm);
- acc += GSL_REAL(gsl_matrix_complex_get(eigvectz,r,c));
- }
- timerStd.stop();
- }
- std::cout << " | \t"
- << timerSa.value() * REPEAT / saRepeats << "s \t"
- << timerStd.value() * REPEAT / stdRepeats << "s";
- gsl_matrix_free(gslCovMat);
- gsl_vector_free(gslCopy);
- gsl_matrix_free(eigvect);
- gsl_vector_free(eigval);
- gsl_matrix_complex_free(eigvectz);
- gsl_vector_complex_free(eigvalz);
- gsl_eigen_symmv_free(eisymm);
- gsl_eigen_nonsymmv_free(einonsymm);
- }
- #endif
- std::cout << "\n";
-
- // make sure the compiler does not optimize too much
- if (acc==123)
- std::cout << acc;
- }
- int main(int argc, char* argv[])
- {
- const int dynsizes[] = {4,6,8,12,16,24,32,64,128,256,512,0};
- std::cout << "size selfadjoint generic";
- #ifdef BENCH_GMM
- std::cout << " GMM++ ";
- #endif
- #ifdef BENCH_GSL
- std::cout << " GSL (double + ATLAS) ";
- #endif
- std::cout << "\n";
- for (uint i=0; dynsizes[i]>0; ++i)
- benchEigenSolver(Matrix<Scalar,Dynamic,Dynamic>(dynsizes[i],dynsizes[i]));
- benchEigenSolver(Matrix<Scalar,2,2>());
- benchEigenSolver(Matrix<Scalar,3,3>());
- benchEigenSolver(Matrix<Scalar,4,4>());
- benchEigenSolver(Matrix<Scalar,6,6>());
- benchEigenSolver(Matrix<Scalar,8,8>());
- benchEigenSolver(Matrix<Scalar,12,12>());
- benchEigenSolver(Matrix<Scalar,16,16>());
- return 0;
- }
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