[petsc-users] Not getting scalability.

[Matthew Knepley]

On Mon, Mar 7, 2011 at 8:20 AM, Gaurish Telang <gaurish108 at gmail.com> wrote:

> Hi,
>
> I have been testing PETSc's scalability on clusters for matrices of sizes
> 2000, 10,000, uptill 60,000.
>

1) These matrices are incredibly small. We usually recommend 10,000
unknowns/process for weak scaling. You
    might get some benefit from a shared memory implementation on a
multicore.


> All I did was try to solve Ax=b for these matrices. I found that the
> solution time dips if I use upto 16 or 32 processors. However for a larger
> number of processors however the solution time seems to go up rather than
> down. IS there anyway I can make my code strongly scalable ?
>

2) These are small enough that direct factorization should be the fastest
alternative. I would try UMFPack, SuperLU, and MUMPS.

    Matt


> I am measuring the total time (sec) and KSP_SOLVE time in the -log_summary
> output. Both times show the same behaviour described above.
>
> Gaurish
>
-- 
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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