[petsc-dev] boomerAmg scalability

[Ravi Kannan]

Hi Mark, Matt,

 

We recently downloaded the petsc development version, to test the gamg
package.

 

This works in serial : we tried for small cases. The parallel case (even
with 2 partitions) just hangs. As of now, we have not set any parameters. So
I guess that the default parameters are being used.

 

Do we need to explicitly set the block size to MatSetBlockSize(mat,1) for a
PARALLEL run? Our solver solves U,V,W and P separately. 

 

Any input on this would be great.

 

Thanks,

Ravi. 

 

From: petsc-dev-bounces at mcs.anl.gov [mailto:petsc-dev-bounces at mcs.anl.gov]
On Behalf Of Mark F. Adams
Sent: Thursday, December 15, 2011 1:18 PM
To: For users of the development version of PETSc
Subject: Re: [petsc-dev] boomerAmg scalability

 

 

On Dec 15, 2011, at 1:56 PM, Matthew Knepley wrote:





On Thu, Dec 15, 2011 at 10:23 AM, Ravi Kannan <rxk at cfdrc.com> wrote:

Dear All,

 

This is Ravi Kannan from CFD Research Corporation. Recently, we are
experimenting with the BoomerAMG preconditioner for some "stiff" CFD
problems. In that regard, all the other standard solver-preconditioner
combinations failed for the current CFD problem. The boomer is the only one
which is able to provide with "converged" solutions.

 

We noticed that the scalability of this boomer preconditioner is really
poor. For instance, even with a cell size of 2 million, we cannot scale to
even 16 partitions (in contrast, the other solver-preconditioner
combinations like the BI-CGS/BJacobi gave good enough scalability).

 

Are we missing something? Do we need to use a more latest version of boomer?

 

Have you tried -pc_type gamg in petsc-dev?

 

For gamg you also want to use MPIAIJ matrices and set the block size
MatSetBlockSize(mat,3), for a 3D velocity field, for instance.  You can also
try '-pc_gamg_type pa' or '-pc_gamg_type sa'.  "pa", for plain aggregation
might be better for CFD problems.

 

Mark





 

  Matt

  

Thanks,

Ravi. 

 




 

-- 
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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