[petsc-users] Expected weak scaling behaviour for AMG libraries?

[Khurana, Parv]

Hello PETSc Community,
I am trying to understand the scaling behaviour of AMG methods in PETSc (Hypre for now) and how many DOFs/Rank are needed for a performant AMG solve.
I’m currently conducting weak scaling tests using src/snes/tutorials/ex12.c in 3D, applying Dirichlet BCs with FEM at P=1. The tests keep DOFs per processor constant while increasing the mesh size and processor count, specifically:

  *   20000 and 80000 DOF/RANK configurations.
  *   Running SNES twice, using GMRES with a tolerance of 1e-5 and preconditioning with Hypre-BoomerAMG.

Unfortunately, parallel efficiency degrades noticeably with increased processor counts. Are there any insights or rules of thumb for using AMG more effectively? I have been looking at this issue for a while now and would love to engage in a further discussion. Please find below the weak scaling results and the options I use to run the tests.
[cid:b3265a6e-baed-4fc1-a58d-0eebbb7de5a4]
#Run type
-run_type full
-petscpartitioner_type simple

#Mesh settings
-dm_plex_dim 3
-dm_plex_simplex 1
-dm_refine 5 #Varied this
-dm_plex_box_faces 6,6,6

#BCs and FEM space
-bc_type dirichlet
-petscspace_degree 1

#Solver settings
-snes_max_it 2
-ksp_type gmres
-ksp_rtol 1.0e-5
#Same settings as what we use for LOR
-pc_type hypre
-pc_hypre_type boomeramg
-pc_hypre_boomeramg_coarsen_type hmis
-pc_hypre_boomeramg_relax_type_all symmetric-sor/jacobi
-pc_hypre_boomeramg_strong_threshold 0.7
-pc_hypre_boomeramg_interp_type ext+i
-pc_hypre_boomeramg_P_max 2
-pc_hypre_boomeramg_truncfactor 0.3

Best,
Parv
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