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sparse module: add support for umfpack, the sparse direct LU

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solver from suitesparse (as cholmod). It seems to be even faster
than SuperLU and it was much simpler to interface ! Well,
the factorization is faster, but for the solve part, SuperLU is
quite faster. On the other hand the solve part represents only a
fraction of the whole procedure. Moreover, I bench random matrices
that does not represents real cases, and I'm not sure at all
I use both libraries with their best settings !
This commit is contained in:
Gael Guennebaud
2008-10-19 22:44:21 +00:00
parent 64f7fbe3f2
commit 3a231c2349
4 changed files with 187 additions and 22 deletions
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60
bench/sparse_lu.cpp
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@@ -1,9 +1,8 @@
// 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
#define EIGEN_UMFPACK_SUPPORT
#include <Eigen/Sparse>
#define NOGMM
@@ -43,6 +42,33 @@ 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;
@@ -82,28 +108,22 @@ int main(int argc, char *argv[])
timer.stop();
std::cout << " solve:\t" << timer.value() << endl;
// std::cout << b.transpose() << "\n";
std::cout << x.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;
#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
timer.reset();
timer.start();
lu.solve(b,&x);
timer.stop();
std::cout << " solve:\t" << timer.value() << endl;
std::cout << x.transpose() << "\n";
}
#ifdef EIGEN_UMFPACK_SUPPORT
x.setZero();
doEigen<Eigen::UmfPack>("Eigen/UmfPack (auto)", sm1, b, x, 0);
#endif
}