Performance of MatMatSolve

[Hong Zhang]

David,

You may run with option '-log_summary <log_file>' and
check which function dominates the time.
I suspect the symbolic factorization, because it is
implemented sequentially in mumps.

If this is the case, you may swich to superlu_dist
which supports parallel symbolic factorization
in the latest release.

Let us know what you get,

Hong

On Fri, 13 Mar 2009, David Fuentes wrote:

>
> The majority of time in my code is spent in the MatMatSolve. I'm running 
> MatMatSolve in parallel using Mumps as the factored matrix.
> Using top, I've noticed that during the MatMatSolve
> the majority of the load seems to be on the root process.
> Is this expected? Or do I most likely have a problem with the matrices that 
> I'm passing in?
>
>
>
> thank you,
> David Fuentes
>
>