Hi Roy, Thanks very much for your comments and suggestion!
If I want to compute the Cholesky decomposition just once and reuse this decomposition for all subsequent solver calls, can I do that via passing a specific solver option when running the program or do I need to cast the libmesh Sparse Matrix to a PETSc matrix? Thanks, Kathrin > Am 08.12.2016 um 11:53 schrieb Roy Stogner <[email protected]>: > > > On Thu, 8 Dec 2016, Kathrin Smetana wrote: > >> 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? > > Sparse Cholesky is probably the right way to go, but for the > implementation I'd suggest MUMPS via PETSc. That will let you > parallelize and experiment more easily. > --- > Roy ------------------------------------------------------------------------------ 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
