On Fri, Dec 16, 2011 at 9:37 AM, Dave Nystrom <dnystrom1 at comcast.net> wrote:

> I'm trying to figure out whether I can do a couple of things with petsc.
>
> 1.  It looks like the preconditioning matrix can actually be different from
> the full problem matrix.  So I'm wondering if I could provide a different
> preconditioning matrix for my problem and then do an LU solve of the
> preconditioning matrix using the -pc_type lu as my preconditioner.
>

Yes, that is what it is for.


> 2.  When I build petsc, I use the --download-f-blas-lapack=yes option.  I'm
> wondering if petsc uses lapack under the hood or has the capability to use
> lapack under the hood when one uses the -pc_type lu option.  In particular,
> since my matrices are band matrices from doing a discretization on a 2d
> regular mesh, I'm wondering if the petsc lu solve has the ability to use
> the
> lapack band solver dgbsv or dgbsvx.  Or is it possible to use the lapack
> band
> solver through one of the external packages that petsc can interface with.
> I'm interested in this capability for smaller problem sizes that fit on a
> single node and that make sense.
>

We do not have any banded matrix stuff. Its either dense or sparse right
now.


> 3.  I'm also wondering how I might be able to learn more about the petsc
> ilu
> capability.  My impression is that it does ilu(k) and I have tried it with
> k>0 but am wondering if one of the options might allow it to do ilut and
> whether as k gets big whether ilu(k) approximates lu.  I currently do not
> understand the petsc ilu well enough to know how much extra fill I get as I
> increase k and where that extra fill might be located for the case of a
> band
> matrix that one gets from discretization on a regular 2d mesh.
>

We do not do ilu(dt). Its complicated, and we determined that it was not
worth
the effort. You can get that from Hypre is you want. Certainly, for big
enough
k, ilu(k) is lu but its a slow way to do it.

   Matt


> Thanks,
>
> Dave
>



-- 
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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