|  | #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"; | 
|  | } |