I have a pretty well-conditioned problem, eigenvalues in (0.2, 1.55) with bjacobi/ilu. It converges in 20-25 iterations with GMRES or with Chebyshev targeting this range (eigenvalues are almost uniformly distributed). I'd like to make an attempt to do better using GAMG, but the mass term is big enough that I don't want a real coarse grid. Instead, I want to coarsen only once or twice "in-place" and not have any real coarse grid. But it looks like GAMG is hardwired to put the coarsest grid on one process. How should we add this flexibility?
signature.asc
Description: PGP signature
