If you want few selected eigen solutions of sparse matrix, you should use sparse eigen solver. Take a look at' slepc (http://www.grycap.upv.es/slepc/) or use slepc interface with arpack.
Hong On Mon, 14 Jan 2008, Yujie wrote: > Thank you for your advice. > I have used -ksp_compute_eigenvalues_explicitly to get the eigen values. > However, it is very very > slow because the dimension of the matrix is about ten thousand. > > Yujie > > On 1/14/08, Matthew Knepley <knepley at gmail.com> wrote: >> >> You can use >> >> >> http://www-unix.mcs.anl.gov/petsc/petsc-as/snapshots/petsc-current/docs/manualpages/KSP/KSPComputeEigenvaluesExplicitly.html >> >> with and without a preconditioner. We have not coded the SVD >> counterpart, but you can use >> >> >> http://www-unix.mcs.anl.gov/petsc/petsc-as/snapshots/petsc-current/docs/manualpages/KSP/KSPComputeExplicitOperator.html >> >> and then call the LAPACK yourself. >> >> Matt >> >> On Jan 13, 2008 11:23 PM, Yujie <recrusader at gmail.com> wrote: >>> Hi, everyone >>> >>> I want to select iterative methods by observing the singular values >>> decompostion of the matrix. However, I don't know how to get all the >>> singular values of the matrix in PETSc. I know the command >>> "-ksp_monitor_singular_value" may get the max and min singular values at >>> each iteration. How to get the singular values of the matrix I want to >>> solve? In addition, when I use the preconditioned iterative method, how >> to >>> get the singular values of the preconditioned iterative operator? >>> >>> thanks a lot. >>> >>> Regards, >>> Yujie >>> >> >> >> >> -- >> What most experimenters take for granted before they begin their >> experiments is infinitely more interesting than any results to which >> their experiments lead. >> -- Norbert Wiener >> >> >
