venkatesh: > > Is it possible to do a non-symmetric complex eigenvalue problem with this > approach ? > Unfortunately, no. Hong
> > > > On Thu, Jul 3, 2014 at 8:11 AM, murat keçeli <[email protected]> wrote: > >> Hi Jifeng, >> >> I think your application is suitable for the SIPs method, see attached >> paper. We have improved it recently, so that it can handle very >> large (500k by 500k with more than 3.e7 nonzeros) sparse matrices.Current >> version of SIPs is basically adding a second layer of parallelism on top of >> SLEPc's shift and invert method. Let me or Hong Zhang (cc, the developer of >> SIPs) know, if you would like to give it a try. >> >> Murat Keceli >> >> >> On Wed, Jul 2, 2014 at 4:46 PM, jifeng zhao < >> [email protected]> wrote: >> >>> Hello all, >>> >>> I am working on solving a generalized eigenvalue problem with SLEPC >>> and PETSC. >>> >>> *K* x = lamda *M* x >>> >>> I attached the sparsity pattern of matrix *M* (*K* is the same). It is >>> a FEM model. It is so sparse is because of constraints. >>> >>> I have tried two things: >>> >>> 1. Krylov-Schur and exact shift-and-invert (I will try MUMPS in >>> future). It works. But I am worrying that it is less parrallelable, when >>> the problem contains millions of degree of freedom. >>> >>> 2. JD with Jacobi preconditioner. It could work, but a lot of tuning >>> needs to be done in terms of RTOL, max_iteration_number. And sometimes I >>> suffer from a stagnated solution, and can't obtain accurate result. >>> >>> Does anybody know that for my specific case of matrix sparsity, is >>> there any thing I can do to speed up my direct solver (Krylov-Schur)? >>> >>> Is there any recommended preconditioners I could try on, for the case >>> of JD? There are a lot of preconditioners in HYPRE library. >>> >>> Thank you in advance! >>> [image: Inline image 1] >>> -- >>> Jifeng Zhao >>> PhD candidate at Northwestern University, US >>> Theoretical and Applied Mechanics Program >>> >> >> >
