Further question about PC with Jaocbi Row Sum

[Matthew Knepley]

On Wed, Apr 9, 2008 at 3:25 PM, Shi Jin <jinzishuai at yahoo.com> 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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