Hi John, Thanks very much for your comments and suggestions!
In the Eigen documentation they have a Sparse LU decomposition with Umfpack and Super LU support, but I have not checked the implementation. Unfortunately my matrix has a dimension of 1M \times 1M… Thanks, Kathrin Am 08.12.2016 um 12:01 schrieb John Peterson <[email protected]<mailto:[email protected]>>: On Thu, Dec 8, 2016 at 10:44 AM, Kathrin Smetana <[email protected]<mailto:[email protected]>> wrote: Dear libmesh users/developers, I have to solve a linear system of equations (system size approximately 10^6) very often (about 5000 times). The linear system of equations is the result of a FEM discretization of 3D linear elasticity. I thought about using a sparse Cholesky decomposition as the matrix is symmetric or a sparse LU decomposition, depending on availability. I have had a look at the Eigen package and their direct LU factorization for instance with Umfpack or SuperLU support looks very promising to me. Do you think that is a good option or do you have any other recommendations for me? I don't think the Eigen direct LU implementation is sparse? Is your matrix 1M x 1M or 1000 x 1000? The former is probably prohibitively large for *any* direct solver... I second what Roy said, but will also add that superlu_dist is a good option. You can access the latter by building PETSc with --download-superlu_dist=1 and running with: -pc_type lu -pc_factor_mat_solver_package superlu_dist -- John ------------------------------------------------------------------------------ Developer Access Program for Intel Xeon Phi Processors Access to Intel Xeon Phi processor-based developer platforms. With one year of Intel Parallel Studio XE. Training and support from Colfax. Order your platform today.http://sdm.link/xeonphi _______________________________________________ Libmesh-users mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/libmesh-users
