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// g++ -I.. sparse_lu.cpp -O3 -g0 -I /usr/include/superlu/ -lsuperlu -lgfortran -DSIZE=1000 -DDENSITY=.05 && ./a.out
// #define EIGEN_TAUCS_SUPPORT
// #define EIGEN_CHOLMOD_SUPPORT
#define EIGEN_SUPERLU_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>
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();
LU<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
// eigen sparse matrices
{
x.setZero();
BenchTimer timer;
timer.start();
SparseLU<EigenSparseMatrix,SuperLU> lu(sm1);
timer.stop();
std::cout << "Eigen/SuperLU:\t" << timer.value() << endl;
timer.reset();
timer.start();
lu.solve(b,&x);
timer.stop();
std::cout << " solve:\t" << timer.value() << endl;
std::cout << x.transpose() << "\n";
}
}
return 0;
}
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