|  | #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 svd_opt = ComputeThinU|ComputeThinV; | 
|  |  | 
|  | 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> jsvd(A.rows(),A.cols()); | 
|  | BDCSVD<MatDyn> 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,svd_opt)); | 
|  | //   if(size*rows<=20000000) | 
|  | BENCH(t_bdcsvd, tries, rep, bdcsvd.compute(A,svd_opt)); | 
|  |  | 
|  | 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"; | 
|  | } |