[petsc-users] GAMG preconditioning

Barry Smith bsmith at petsc.dev
Mon Apr 12 20:07:36 CDT 2021

  Please send -log_view for the ilu and GAMG case.


> On Apr 12, 2021, at 10:34 AM, Milan Pelletier via petsc-users <petsc-users at mcs.anl.gov> wrote:
> Dear all,
> I am currently trying to use PETSc with CG solver and GAMG preconditioner.
> I have started with the following set of parameters:
> -ksp_type cg
> -pc_type gamg
> -pc_gamg_agg_nsmooths 1 
> -pc_gamg_threshold 0.02 
> -mg_levels_ksp_type chebyshev 
> -mg_levels_pc_type sor 
> -mg_levels_ksp_max_it 2
> Unfortunately, the preconditioning seems to run extremely slowly. I tried to play around with the numbers, to check if I could notice some difference, but could not observe significant changes. 
> As a comparison, the KSPSetup call with GAMG PC takes more than 10 times longer than completing the whole computation (preconditioning + ~400 KSP iterations to convergence) of the similar case using the following parameters :
> -ksp_type cg
> -pc_type ilu
> -pc_factor_levels 0
> The matrix size for my case is ~1,850,000*1,850,000 elements, with ~38,000,000 non-zero terms (i.e. ~20 per row). For both ILU and AMG cases I use matseqaij/vecseq storage (as a first step I work with only 1 MPI process).
> Is there something wrong in the parameter set I have been using?
> I understand that the preconditioning overhead with AMG is higher than with ILU, but I would also expect CG/GAMG to be competitive against CG/ILU, especially considering the relatively big problem size.
> For information, I am using the PETSc version built from commit 6840fe907c1a3d26068082d180636158471d79a2 (release branch from April 7, 2021). 
> Any clue or idea would be greatly appreciated!
> Thanks for your help,
> Best regards,
> Milan Pelletier

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.mcs.anl.gov/pipermail/petsc-users/attachments/20210412/d89f21b5/attachment.html>

More information about the petsc-users mailing list