Further question about PC with Jaocbi Row Sum

[Barry Smith]

   There is no super easy way to do this that I can think of.

   The diagonal cases you can run with -pc_type jacobi and the  
nondiagonal with -pc_type lu (or Cholesky)
I realize this is not exactly what you want.

    Barry

On Apr 11, 2008, at 3:56 PM, Shi Jin wrote:
> Thank you.
> Suppose I have a diagonal matrix, what is the best way to invert it  
> in PETSc?
> Do I have to install the external packages superlu_dist or mumps?
> I realized that LU or Cholesky decomposition does not work with  
> MPIAIJ matrices.
> I also know the best way is probably to directly call Vector  
> operations directly.
> However, I want to keep the same KSPSolve structure so that the same  
> code can be used  for non-diagonal MPIAIJ matrices without changing  
> each call to KSPSolve.
> Thank you very much.
>
> Shi
>> 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
>>
>
>
>
>
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