[petsc-users] MatPtAP

[David Knezevic]

On Wed, Feb 24, 2016 at 1:06 AM, Barry Smith <bsmith at mcs.anl.gov> wrote:

>
>   Yes, could definitely be faster with a custom code but a bit of a pain
> to write.
>


OK, thanks for your input!

David





>
> > On Feb 23, 2016, at 10:08 PM, David Knezevic <david.knezevic at akselos.com>
> wrote:
> >
> > On Tue, Feb 23, 2016 at 10:40 PM, Barry Smith <bsmith at mcs.anl.gov>
> wrote:
> >
> >   A custom MatPtAP would almost surely pay off, but it is only an
> optimization so you need to ask if this computation is your main "blocker"
> to getting more "science" done.  Can you send a picture of the exact
> structure of P?
> >
> > I've attached a picture of the sparsity pattern of P. There are 0s and
> 1s on the diagonal, and some dense columns in the first few columns.
> >
> > David
> >
> >
> >
> >
> >
> >
> >
> >
> > > On Feb 23, 2016, at 9:35 PM, David Knezevic <
> david.knezevic at akselos.com> wrote:
> > >
> > > I'm using MatPtAP, which works well for me, but in some examples I've
> tested the PtAP calculation dominates the overall solve time (e.g. see
> attached -log_summary output).
> > >
> > > In my case, A is a stiffness matrix, and P is the identity matrix
> except for a small number of columns (e.g. about 10 or so) which are dense.
> > >
> > > In this situation, I was wondering if there is a more efficient way to
> proceed than using MatPtAP? For example, would it be noticeably faster to
> calculate P^T A P directly using MatMults for the dense columns, rather
> than using MatPtAP?
> > >
> > > Thanks!
> > > David
> > >
> > >
> > > <PtAP_log_summary.txt>
> >
> >
> > <P_sparsity.png>
>
>
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