blob: ef9ecb7dfdd6371df6d0486d3086e0b53aa0a75a [file] [log] [blame]
#include <iostream>
#include "BenchTimer.h"
#include <Eigen/Dense>
#include <map>
#include <vector>
#include <string>
#include <sstream>
using namespace Eigen;
std::map<std::string, Array<float, 1, 8, DontAlign | RowMajor> > results;
std::vector<std::string> labels;
std::vector<Array2i> sizes;
template <typename Solver, typename MatrixType>
EIGEN_DONT_INLINE void compute_norm_equation(Solver &solver, const MatrixType &A) {
if (A.rows() != A.cols())
solver.compute(A.transpose() * A);
else
solver.compute(A);
}
template <typename Solver, typename MatrixType>
EIGEN_DONT_INLINE void compute(Solver &solver, const MatrixType &A) {
solver.compute(A);
}
template <typename Scalar, int Size>
void bench(int id, int rows, int size = Size) {
typedef Matrix<Scalar, Dynamic, Size> Mat;
typedef Matrix<Scalar, Dynamic, Dynamic> MatDyn;
typedef Matrix<Scalar, Size, Size> MatSquare;
Mat A(rows, size);
A.setRandom();
if (rows == size) A = A * A.adjoint();
BenchTimer t_llt, t_ldlt, t_lu, t_fplu, t_qr, t_cpqr, t_cod, t_fpqr, t_jsvd, t_bdcsvd;
int tries = 5;
int rep = 1000 / size;
if (rep == 0) rep = 1;
// rep = rep*rep;
LLT<MatSquare> llt(size);
LDLT<MatSquare> ldlt(size);
PartialPivLU<MatSquare> lu(size);
FullPivLU<MatSquare> fplu(size, size);
HouseholderQR<Mat> qr(A.rows(), A.cols());
ColPivHouseholderQR<Mat> cpqr(A.rows(), A.cols());
CompleteOrthogonalDecomposition<Mat> cod(A.rows(), A.cols());
FullPivHouseholderQR<Mat> fpqr(A.rows(), A.cols());
JacobiSVD<MatDyn, ComputeThinU | ComputeThinV> jsvd(A.rows(), A.cols());
BDCSVD<MatDyn, ComputeThinU | ComputeThinV> bdcsvd(A.rows(), A.cols());
BENCH(t_llt, tries, rep, compute_norm_equation(llt, A));
BENCH(t_ldlt, tries, rep, compute_norm_equation(ldlt, A));
BENCH(t_lu, tries, rep, compute_norm_equation(lu, A));
if (size <= 1000) BENCH(t_fplu, tries, rep, compute_norm_equation(fplu, A));
BENCH(t_qr, tries, rep, compute(qr, A));
BENCH(t_cpqr, tries, rep, compute(cpqr, A));
BENCH(t_cod, tries, rep, compute(cod, A));
if (size * rows <= 10000000) BENCH(t_fpqr, tries, rep, compute(fpqr, A));
if (size < 500) // JacobiSVD is really too slow for too large matrices
BENCH(t_jsvd, tries, rep, jsvd.compute(A));
// if(size*rows<=20000000)
BENCH(t_bdcsvd, tries, rep, bdcsvd.compute(A));
results["LLT"][id] = t_llt.best();
results["LDLT"][id] = t_ldlt.best();
results["PartialPivLU"][id] = t_lu.best();
results["FullPivLU"][id] = t_fplu.best();
results["HouseholderQR"][id] = t_qr.best();
results["ColPivHouseholderQR"][id] = t_cpqr.best();
results["CompleteOrthogonalDecomposition"][id] = t_cod.best();
results["FullPivHouseholderQR"][id] = t_fpqr.best();
results["JacobiSVD"][id] = t_jsvd.best();
results["BDCSVD"][id] = t_bdcsvd.best();
}
int main() {
labels.push_back("LLT");
labels.push_back("LDLT");
labels.push_back("PartialPivLU");
labels.push_back("FullPivLU");
labels.push_back("HouseholderQR");
labels.push_back("ColPivHouseholderQR");
labels.push_back("CompleteOrthogonalDecomposition");
labels.push_back("FullPivHouseholderQR");
labels.push_back("JacobiSVD");
labels.push_back("BDCSVD");
for (int i = 0; i < labels.size(); ++i) results[labels[i]].fill(-1);
const int small = 8;
sizes.push_back(Array2i(small, small));
sizes.push_back(Array2i(100, 100));
sizes.push_back(Array2i(1000, 1000));
sizes.push_back(Array2i(4000, 4000));
sizes.push_back(Array2i(10000, small));
sizes.push_back(Array2i(10000, 100));
sizes.push_back(Array2i(10000, 1000));
sizes.push_back(Array2i(10000, 4000));
using namespace std;
for (int k = 0; k < sizes.size(); ++k) {
cout << sizes[k](0) << "x" << sizes[k](1) << "...\n";
bench<float, Dynamic>(k, sizes[k](0), sizes[k](1));
}
cout.width(32);
cout << "solver/size";
cout << " ";
for (int k = 0; k < sizes.size(); ++k) {
std::stringstream ss;
ss << sizes[k](0) << "x" << sizes[k](1);
cout.width(10);
cout << ss.str();
cout << " ";
}
cout << endl;
for (int i = 0; i < labels.size(); ++i) {
cout.width(32);
cout << labels[i];
cout << " ";
ArrayXf r = (results[labels[i]] * 100000.f).floor() / 100.f;
for (int k = 0; k < sizes.size(); ++k) {
cout.width(10);
if (r(k) >= 1e6)
cout << "-";
else
cout << r(k);
cout << " ";
}
cout << endl;
}
// HTML output
cout << "<table class=\"manual\">" << endl;
cout << "<tr><th>solver/size</th>" << endl;
for (int k = 0; k < sizes.size(); ++k) cout << " <th>" << sizes[k](0) << "x" << sizes[k](1) << "</th>";
cout << "</tr>" << endl;
for (int i = 0; i < labels.size(); ++i) {
cout << "<tr";
if (i % 2 == 1) cout << " class=\"alt\"";
cout << "><td>" << labels[i] << "</td>";
ArrayXf r = (results[labels[i]] * 100000.f).floor() / 100.f;
for (int k = 0; k < sizes.size(); ++k) {
if (r(k) >= 1e6)
cout << "<td>-</td>";
else {
cout << "<td>" << r(k);
if (i > 0) cout << " (x" << numext::round(10.f * results[labels[i]](k) / results["LLT"](k)) / 10.f << ")";
if (i < 4 && sizes[k](0) != sizes[k](1)) cout << " <sup><a href=\"#note_ls\">*</a></sup>";
cout << "</td>";
}
}
cout << "</tr>" << endl;
}
cout << "</table>" << endl;
// cout << "LLT (ms) " << (results["LLT"]*1000.).format(fmt) << "\n";
// cout << "LDLT (%) " << (results["LDLT"]/results["LLT"]).format(fmt) << "\n";
// cout << "PartialPivLU (%) " << (results["PartialPivLU"]/results["LLT"]).format(fmt) << "\n";
// cout << "FullPivLU (%) " << (results["FullPivLU"]/results["LLT"]).format(fmt) << "\n";
// cout << "HouseholderQR (%) " << (results["HouseholderQR"]/results["LLT"]).format(fmt) <<
// "\n"; cout << "ColPivHouseholderQR (%) " <<
// (results["ColPivHouseholderQR"]/results["LLT"]).format(fmt) << "\n"; cout << "CompleteOrthogonalDecomposition (%)
// " << (results["CompleteOrthogonalDecomposition"]/results["LLT"]).format(fmt) << "\n"; cout <<
// "FullPivHouseholderQR (%) " << (results["FullPivHouseholderQR"]/results["LLT"]).format(fmt) << "\n";
// cout << "JacobiSVD (%) " << (results["JacobiSVD"]/results["LLT"]).format(fmt) << "\n";
// cout << "BDCSVD (%) " << (results["BDCSVD"]/results["LLT"]).format(fmt) << "\n";
}