Further question about PC with Jaocbi Row Sum

Shi Jin jinzishuai at yahoo.com
Thu Apr 10 00:04:03 CDT 2008


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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