| |
| // 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; |
| } |