Filippo Leonardi <[email protected]> writes: > Thank you. > > Actually I had the feeling that it wasn't my problem with Bjacobi and CG. > > So I'll stick to MG. Problem with MG is that there are a lot of parameters to > be tuned, so I leave the defaults (expect I select CG as Krylow method). I > post just results for 64^3 and 128^3. Tell me if I'm missing some useful > detail. (I get similar results with BoomerAMG). > > Time for one KSP iteration (-ksp_type cg -log_summary -pc_mg_galerkin > -pc_type > mg): > 32^3 and 1 proc: 1.01e-1 > 64^3 and 8 proc: 6.56e-01 > 128^3 and 64 proc: 1.05e+00 > Number of PCSetup per KSPSolve: > 15 > 39 > 65
Presumably you mean PCApply. Something is wrong here because this iteration count is way too high. Perhaps your boundary conditions are nonsymmetric or interpolation is not compatible with the discretization. > With BoomerAMG: > stable 8 iterations per KSP but time per iteration greater than PETSc MG and > still increases: > 64^3: 3.17e+00 > 128^3: 9.99e+00 > > > --> For instance with 64^3 (256 iterations): In the first pass with geometric multigrid, don't worry about timing and get the iterations figured out. Are you using a cell-centered or vertex-centered discretization. When you say 128^3, is that counting the number of elements or the number of vertices? Note that if you have a vertex-centered discretization, you will want a 129^3 grid. With PCMG, make sure you are getting the number of levels of refinement that you expect. You should see something like the following (this is 193^3). $ mpiexec -n 4 ./ex45 -da_refine 5 -pc_type mg -ksp_monitor -pc_mg_type full -mg_levels_ksp_type richardson -mg_levels_pc_type sor -ksp_type richardson 0 KSP Residual norm 2.653722249919e+03 1 KSP Residual norm 1.019366121923e+02 2 KSP Residual norm 2.364558296616e-01 3 KSP Residual norm 7.438761746501e-04 Residual norm 1.47939e-06 You can actually do better than this by using higher order FMG interpolation, by going matrix-free, etc. For example, HPGMG (finite-element or finite-volume, see https://hpgmg.org) will solve more than a million equations/second per core. Is your application really solving the constant-coefficient Poisson problem on a Cartesian grid, or is that just a test? > Using Petsc Release Version 3.3.0, Patch 3, Wed Aug 29 11:26:24 CDT 2012 And a reminder to please upgrade to the current version of PETSc.
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