topic Re: Using PARDISO with ARPACK to solver generalized Eigenvalue in Intel® oneAPI Math Kernel Library

Using PARDISO with ARPACK to solver generalized Eigenvalue problem

AndrewC — Sat, 01 Apr 2006 01:36:17 GMT

I want to use PARDISO with ARPACK to solver a genralized eigenvalue problem in shift-invert mode ( in ARPACK lingo , bmat='G', iparam(7)=3).
This requires using PARDISO to factor the matrix (A-sigma*M) where , in my case, A and M are large SPARSE matrices in CSR format, but not of identical sparse structure. I was wondering if in the MKL routines there is an efficient way to form the A-sigma*M matrix as a sparse matrix.

Andrew

Re: Using PARDISO with ARPACK to solver generalized Eigenvalue

wugaxp — Tue, 19 May 2009 04:47:46 GMT

Quoting - vasci_intel

Could you please introduce more details about your method? Now I'm also trying to use Pardiso and ARPACK to solve a generalized eigenvalue problem for sparse matrices.

As for your problem, now I've written some subroutine to convert the sparse matrix in CSR format into coordinates format. This is because two matrices can be combined easily in coordinates format. Although MKL has some auxiliary routines such as mkl_ddnscsr, mkl_dcsrcoo, and mkl_dcsrbsr to make conversation among the different formats, I have to write my own because I have to deal with complex matrices.

Re: Using PARDISO with ARPACK to solver generalized Eigenvalue

Sergey_K_Intel1 — Tue, 19 May 2009 13:34:59 GMT

Quoting - vasci_intel

MKL Sparse BLASprovides such routines for all types of precision.The name of routine for double precision is mkl_dcsradd. Please take a look at page 449 of MKL Reference Manual for more details about these routines. You can also find examples of the usage of these routines in /example/spblas folder.

All the best
Sergey