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							132 lines
						
					
					
						
							2.9 KiB
						
					
					
				| 
 | |
| // 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; | |
| } | |
| 
 |