Date: Fri, 17 Feb 2012 15:38:55 -0500 From: Jed Brown <[email protected]> Subject: Re: [petsc-users] petsc-users Digest, Vol 38, Issue 41 To: PETSc users list <[email protected]> Message-ID: <CAM9tzSn+CaFbGRdRyc_bVQ8Wa1ACRn8LTRTg1EWxg0az9=YWEQ@mail.gmail.com> Content-Type: text/plain; charset="utf-8"
On Fri, Feb 17, 2012 at 14:09, <[email protected]> wrote:
Indeed I would like to solve the whole linear system by a multigrid approach and not by a lu factorization. Therefore I would like to use -ksp_type richardson -pc_type mg. In this case, the preconditioned problem P^(-1) (f-A x^n) is solved exactly or it performs just a V-cycle iteration? In both cases, since I am using a one-grid multigrid (just for debugging), it should anyway provide the exact solution at the first iteration, but it is not so.
-pc_type mg with one level just applies a normal smoother. I've sometimes thought it should do a coarse-level solve instead, but I haven't messed with it. Barry, why doesn't it do a direct solve?
This explains why the residual decreases so slowly: because it applies the smoother instead of the coarse solver.
In general -pc_type mg does one multigrid cycle (usually a V or W cycle). If you want to use multiple iterations, you can
-pc_type ksp -ksp_pc_type mg
which would use the default KSP (GMRES) as an iteration, preconditioned by multigrid. The "outer" problem will see the result of this converged iterative solve.
I've perfectly understood that. Thank you very much. Armando