|  | 
 | // g++ -I.. sparse_lu.cpp -O3 -g0 -I /usr/include/superlu/ -lsuperlu -lgfortran -DSIZE=1000 -DDENSITY=.05 && ./a.out | 
 |  | 
 | #define EIGEN_SUPERLU_SUPPORT | 
 | #define EIGEN_UMFPACK_SUPPORT | 
 | #include <Eigen/Sparse> | 
 |  | 
 | #define NOGMM | 
 | #define NOMTL | 
 |  | 
 | #ifndef SIZE | 
 | #define SIZE 10 | 
 | #endif | 
 |  | 
 | #ifndef DENSITY | 
 | #define DENSITY 0.01 | 
 | #endif | 
 |  | 
 | #ifndef REPEAT | 
 | #define REPEAT 1 | 
 | #endif | 
 |  | 
 | #include "BenchSparseUtil.h" | 
 |  | 
 | #ifndef MINDENSITY | 
 | #define MINDENSITY 0.0004 | 
 | #endif | 
 |  | 
 | #ifndef NBTRIES | 
 | #define NBTRIES 10 | 
 | #endif | 
 |  | 
 | #define BENCH(X) \ | 
 |   timer.reset(); \ | 
 |   for (int _j=0; _j<NBTRIES; ++_j) { \ | 
 |     timer.start(); \ | 
 |     for (int _k=0; _k<REPEAT; ++_k) { \ | 
 |         X  \ | 
 |   } timer.stop(); } | 
 |  | 
 | typedef Matrix<Scalar,Dynamic,1> VectorX; | 
 |  | 
 | #include <Eigen/LU> | 
 |  | 
 | template<int Backend> | 
 | void doEigen(const char* name, const EigenSparseMatrix& sm1, const VectorX& b, VectorX& x, int flags = 0) | 
 | { | 
 |   std::cout << name << "..." << std::flush; | 
 |   BenchTimer timer; timer.start(); | 
 |   SparseLU<EigenSparseMatrix,Backend> lu(sm1, flags); | 
 |   timer.stop(); | 
 |   if (lu.succeeded()) | 
 |     std::cout << ":\t" << timer.value() << endl; | 
 |   else | 
 |   { | 
 |     std::cout << ":\t FAILED" << endl; | 
 |     return; | 
 |   } | 
 |  | 
 |   bool ok; | 
 |   timer.reset(); timer.start(); | 
 |   ok = lu.solve(b,&x); | 
 |   timer.stop(); | 
 |   if (ok) | 
 |     std::cout << "  solve:\t" << timer.value() << endl; | 
 |   else | 
 |     std::cout << "  solve:\t" << " FAILED" << endl; | 
 |  | 
 |   //std::cout << x.transpose() << "\n"; | 
 | } | 
 |  | 
 | int main(int argc, char *argv[]) | 
 | { | 
 |   int rows = SIZE; | 
 |   int cols = SIZE; | 
 |   float density = DENSITY; | 
 |   BenchTimer timer; | 
 |  | 
 |   VectorX b = VectorX::Random(cols); | 
 |   VectorX x = VectorX::Random(cols); | 
 |  | 
 |   bool densedone = false; | 
 |  | 
 |   //for (float density = DENSITY; density>=MINDENSITY; density*=0.5) | 
 | //   float density = 0.5; | 
 |   { | 
 |     EigenSparseMatrix sm1(rows, cols); | 
 |     fillMatrix(density, rows, cols, sm1); | 
 |  | 
 |     // dense matrices | 
 |     #ifdef DENSEMATRIX | 
 |     if (!densedone) | 
 |     { | 
 |       densedone = true; | 
 |       std::cout << "Eigen Dense\t" << density*100 << "%\n"; | 
 |       DenseMatrix m1(rows,cols); | 
 |       eiToDense(sm1, m1); | 
 |  | 
 |       BenchTimer timer; | 
 |       timer.start(); | 
 |       FullPivLU<DenseMatrix> lu(m1); | 
 |       timer.stop(); | 
 |       std::cout << "Eigen/dense:\t" << timer.value() << endl; | 
 |  | 
 |       timer.reset(); | 
 |       timer.start(); | 
 |       lu.solve(b,&x); | 
 |       timer.stop(); | 
 |       std::cout << "  solve:\t" << timer.value() << endl; | 
 | //       std::cout << b.transpose() << "\n"; | 
 | //       std::cout << x.transpose() << "\n"; | 
 |     } | 
 |     #endif | 
 |  | 
 |     #ifdef EIGEN_UMFPACK_SUPPORT | 
 |     x.setZero(); | 
 |     doEigen<Eigen::UmfPack>("Eigen/UmfPack (auto)", sm1, b, x, 0); | 
 |     #endif | 
 |  | 
 |     #ifdef EIGEN_SUPERLU_SUPPORT | 
 |     x.setZero(); | 
 |     doEigen<Eigen::SuperLU>("Eigen/SuperLU (nat)", sm1, b, x, Eigen::NaturalOrdering); | 
 | //     doEigen<Eigen::SuperLU>("Eigen/SuperLU (MD AT+A)", sm1, b, x, Eigen::MinimumDegree_AT_PLUS_A); | 
 | //     doEigen<Eigen::SuperLU>("Eigen/SuperLU (MD ATA)", sm1, b, x, Eigen::MinimumDegree_ATA); | 
 |     doEigen<Eigen::SuperLU>("Eigen/SuperLU (COLAMD)", sm1, b, x, Eigen::ColApproxMinimumDegree); | 
 |     #endif | 
 |  | 
 |   } | 
 |  | 
 |   return 0; | 
 | } | 
 |  |