MG question
Matthew Knepley
knepley at gmail.com
Wed Feb 27 14:29:44 CST 2008
On Wed, Feb 27, 2008 at 2:22 PM, <jens.madsen at risoe.dk> wrote:
> Ok
>
> Thanks Matthew and Barry
>
> First I solve 2d boundary value problems of size 512^2 - 2048^2.
>
> Typically either kind of problem(solve for phi)
>
> I) poisson type equation:
>
> \nabla^2 \phi(x,y) = f(x,y)
>
> II)
>
> \nabla \cdot (g(x,y) \nabla\phi(x,y)) = f(x,y)
>
> Successively with new f and g functions
>
>
> Do you know where to read about the smoothing properties of GMRES and
> CG? All refs that I find are only describing smoothing with GS-RB etc.
>
> My vague idea on how a fast solver is to use a (preconditioned ILU?)
> krylov (CG for spd ie. problem I, GMRES for II)) method with additional
> MG preconditioning(GS-RB smoother, Krylov solver on coarsest level)?
>
> As my problems are not that big I fear that I will get no MG speedup if
> I use krylov methods as smoothers?
Well, you might need to prove things, but I would not worry about that first.
It is so easy to code up, just run everything and see what actually works.
Then sit down and try to show it.
Matt
> Kind Regards Jens
>
>
> -----Original Message-----
> From: owner-petsc-users at mcs.anl.gov
> [mailto:owner-petsc-users at mcs.anl.gov] On Behalf Of Barry Smith
> Sent: Wednesday, February 27, 2008 8:49 PM
> To: petsc-users at mcs.anl.gov
> Subject: Re: MG question
>
>
> The reason we default to these "very strong" (gmres + ILU(0))
> smoothers is robustness, we'd rather have
> the solver "just work" for our users and be a little bit slower than
> have it often fail but be optimal
> for special cases.
>
> Most of the MG community has a mental block about using Krylov
> methods, this is
> why you find few papers that discuss their use with multigrid. Note
> also that using several iterations
> of GMRES (with or without ILU(0)) is still order n work so you still
> get the optimal convergence of
> mutligrid methods (when they work, of course).
>
> Barry
>
>
> On Feb 27, 2008, at 1:40 PM, Matthew Knepley wrote:
>
> > On Wed, Feb 27, 2008 at 1:31 PM, <jens.madsen at risoe.dk> wrote:
> >> Hi
> >>
> >> I hope that this question is not outside the scope of this
> >> mailinglist.
> >>
> >> As far as I understand PETSc uses preconditioned GMRES(or another KSP
> >> method) as pre- and postsmoother on all multigrid levels? I was just
> >
> > This is the default. However, you can use any combination of KSP/PC
> > on any
> > given level with options. For instance,
> >
> > -mg_level_ksp_type richardson -mg_level_pc_type sor
> >
> > gives "regulation" MG. We default to GMRES because it is more robust.
> >
> >> wondering why and where in the literature I can read about that
> >> method? I
> >> thought that a fast method would be to use MG (with Gauss-Seidel RB/
> >> zebra
> >> smothers) as a preconditioner for GMRES? I have looked at papers
> >> written by
> >> Oosterlee etc.
> >
> > In order to prove something about GMRES/MG, you would need to prove
> > something
> > about the convergence of GMRES on the operators at each level. Good
> > luck. GMRES
> > is the enemy of all convergence proofs. See paper by Greenbaum,
> > Strakos, & Ptak.
> > If SOR works, great and it is much faster. However, GMRES/ILU(0) tends
> > to be more
> > robust.
> >
> > Matt
> >
> >> Kind Regards
> > --
> > 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
> >
>
>
>
--
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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