Further question about PC with Jaocbi Row Sum

[Hong Zhang]

Then you may try direct sparse linear solver,
sequential run:
-ksp_type preonly -pc_type cholesky
parallel run (install external packages superlu_dist or mumps):
-ksp_type preonly -pc_type lu -mat_type superlu_dist
or
-ksp_type preonly -pc_type cholesky -mat_type sbaijmumps

Hong

On Wed, 9 Apr 2008, Shi Jin wrote:

>
> Thank you. I have used the -ksp_converged_reason option.
> The result says:
> Linear solve did not converge due to DIVERGED_INDEFINITE_PC iterations 2
> I then further checked the row sum matrix, it has negative eigenvalues.
> So I guess it does not work at all.
> Thank you all for your help.
>
> --
> Shi Jin, PhD
>
> ----- Original Message ----
> > From: Matthew Knepley <knepley at gmail.com>
> > To: petsc-users at mcs.anl.gov
> > Sent: Wednesday, April 9, 2008 2:50:29 PM
> > Subject: Re: Further question about PC with Jaocbi Row Sum
> >
> > On Wed, Apr 9, 2008 at 3:25 PM, Shi Jin  wrote:
> > > Thank you very much.
> > >
> > >
> > >
> > >  > > Is there something particular about this rowsum method?
> > >  >
> > >  >     No. If you use a -ksp_rtol of 1.e-12 and still get different
> > >  > answers, this needs to be investigated.
> > >  >
> > >  >
> > >
> > >  I have tried even with -ksp_rtol   1.e-20 but still got different results.
> > >
> > >  Here is what I got when solving the mass matrix with
> > >
> > > -pc_type  jacobi
> > >  -pc_jacobi_rowsum 1
> > >  -ksp_type cg
> > >  -sub_pc_type icc
> > >  -ksp_rtol 1.e-20
> > >  -ksp_monitor
> > >  -ksp_view
> > >
> > >   0 KSP Residual norm 2.975203858623e+00
> > >   1 KSP Residual norm 2.674371671721e-01
> > >   2 KSP Residual norm 1.841074927355e-01
> > >  KSP Object:
> > >   type: cg
> > >   maximum iterations=10000, initial guess is zero
> > >   tolerances:  relative=1e-20, absolute=1e-50, divergence=10000
> > >   left preconditioning
> > >  PC Object:
> > >   type: jacobi
> > >   linear system matrix = precond matrix:
> > >   Matrix Object:
> > >     type=seqaij, rows=8775, cols=8775
> > >     total: nonzeros=214591, allocated nonzeros=214591
> > >       not using I-node routines
> > >
> > >  I realize that the iteration ended when the residual norm is quite large.
> > >  Do you think this indicates something wrong here?
> >
> > Can you run with
> >
> >   -ksp_converged_reason
> >
> > It appears that the solve fails rather than terminates with an answer. Is it
> > possible that your matrix is not SPD?
> >
> >   Matt
> >
> > >  Thank you again.
> > >
> > >  Shi
> > >
> > >
> > >
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> >
> > --
> > 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
> >
> >
>
>
>
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