Hi folks,

I'm trying to solve a 3D problem in parallel using an AMG preconditioner, 
but the performance is bad. I'm wondering if I can get some advice from 
someone who has experience choosing and tuning multigrid preconditioners, 
particularly for problems in 3D.

For context:

   - The problem is vector-valued (5 components) and elliptic(ish)
   - I use GMRES w/BoomerAMG preconditioner for asymmetric matrices, 
   everything is default
   - In 2D, scaling is good even down to 5,000 DoFs per processor, and 
   number of iterations is independent of problem size
   - In 3D the scaling is bad. Adding more processors after about 50,000 
   DoFs/processor actually slows the program down and sometimes gives memory 
   errors.
   - Taking away the preconditioner in 3D gives a ~20x speedup at 16 
   processors, and strong scaling is linear. However, the number of iterations 
   increases with problem size.
   
Given all that, I have some questions:

   1. Why might it be that the memory and wall-time scaling is so bad in 3D?
   2. Are there any examples lying around deal.II of folks using multigrid 
   for 3D problems in parallel? All the tutorials that I looked at were in 2D, 
   including the 2 examples used in the distributed computing paper.
   3. Might there be an easy way to fix it while still using BoomerAMG? I 
   know the Hypre documentation 
   <https://hypre.readthedocs.io/en/latest/solvers-boomeramg.html> gives 
   some parameter recommendations, but I'm not so sure (1) how to set those 
   options via deal.II (I think they are not available via the AdditionalData 
   interface), or (2) whether those will work. Does anyone have experience 
   with this?
   4. Might the Trilinos AMG preconditioner work any better for this 
   problem by default? And if not, is there a systematic way to tune it 
   (particularly using a deal.II interface) to work better for a 3D problem?
   5. Might the in-house GMG methods work better? And if so, do the 
   matrix-free methods stand a chance of performing better even if I have to 
   use some complicated functions in the matrix assembly (for my weak form I 
   have a 5-component nonlinear function of my solution vector which has to be 
   inverted via Newton's method across my domain).

If more context on the particular problem would be helpful I can certainly 
give details. Mostly I'm looking for intuition, general suggestions, or 
pointers to good references. Any help is much appreciated.

Kind regards,
Lucas

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