Thanks a lot, Jed,
I will try the algebric multigrid first.
In order to configure PETSc with --download-ml and --download-hypre,which
shell file in unix should I modify?
Should I add some line in my current code to run with -pc_type ml or
-pc_type hypre, or just use runtime option?
I am solving a 2-D poisson equation with finite difference scheme. Please
find the problem discription as attached if it is necessary. Thanks again.
Date: Wed, 9 Feb 2011 17:54:19 +0100
From: [email protected]
To: petsc-users at mcs.anl.gov
Subject: Re: [petsc-users] questions about the multigrid framework
On Wed, Feb 9, 2011 at 17:44, Peter Wang <pengxwang at hotmail.com> wrote:
Did you mean All the Krylov methods alone will get worse with increasing grid
number?
Yes, the number of Krylov iterations for second order elliptic problems with no
preconditioner scales proportional to the number of grid points in any
direction. You need a spectrally equivalent preconditioner, usually multigrid
of some sort, to prevent this.
Since the finer grid has smaller size and more number of grid.
Since I am a new user of PETSc, the easiest way for me is still keep in KSP
solver. However, if the solver cannot satisfy the speed reqirement. I am
thinking to use MG method. However, I don't have any experience on multigrid.
Could you please give me some suggestion on it?
1, Since I have built the Matrix and the vector for finite difference scheme
in KSP solver, where should I start from to transfer to multigrid? I studied
the example in: src/ksp/ksp/examples/tutorials/ex22f.F. Is it a good prototype
to be based on to create my own code? Is DMMG is the best tool for my problem?
Assuming you currently assemble a matrix, just configure PETSc with
--download-ml and --download-hypre, then try running your code with -pc_type ml
or -pc_type hypre. You can use geometric multigrid later to improve the
constants or handle cases where algebraic multigrid (ML or BoomerAMG from
Hypre) are having trouble.
You need to tell us what equations you are solving if you want useful
suggestions.
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