[petsc-users] Mat/Vec with empty ranks

Matthew Knepley knepley at gmail.com
Tue Oct 3 03:05:35 CDT 2017


On Mon, Oct 2, 2017 at 10:11 PM, Florian Lindner <mailinglists at xgm.de>
wrote:

>
>
> Am 02.10.2017 um 21:04 schrieb Matthew Knepley:
> > On Mon, Oct 2, 2017 at 6:21 AM, Florian Lindner <mailinglists at xgm.de
> <mailto:mailinglists at xgm.de>> wrote:
> >
> >     Hello,
> >
> >     I have a matrix and vector that live on 4 ranks, but only rank 2 and
> 3 have values:
> >
> >     Doing a simple LSQR solve does not converge. However, when the
> values are distributed equally, it converges within 3
> >     iterations.
> >
> >     What can I do about that?
> >
> >     I have attached a simple program and creates the matrix and vector
> or loads them from a file.
> >
> >
> > There are a few problems with this program. I am attaching a cleaned up
> version. However, convergence still differs starting
> > at iteration 2. It appears that LSQR has a problem with this system, or
> we have a bug that I cannot see.
>
> Thanks for having a look at it!
>
> And good to hear it's not by design. If I can be of any more help tracking
> this down, pleae let me know.
>
> In the meantime, what could be a good way to work around this? This is
> admittedly a very malformed example. Is there a
> way to force solving on a single CPU and then distribute the results resp.
> KSP object to the original parallel layout?
> Of course, we would first try to solve in parallel, but we have little
> influence about the actual parallel layout, since
> we are just a library and other solvers give us the data.
>

I need to be more clear. I do not think convergence has anything to do with
being on 1 process. I think this is an ill-conditioned
example and convergence is an accident in one case. Unless you see this in
a bunch of cases, I would not worry about gathering
to a single process. However, that can be done using PCREDUNDANT if this is
really a problem.

  Thanks,

     Matt


> Best,
> Florian
>



-- 
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

https://www.cse.buffalo.edu/~knepley/ <http://www.caam.rice.edu/~mk51/>
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