Hi Mark/Jed, The problem I'm solving is scalar helmholtz in 2D, (u_t = A*u_xx + A*u_yy + F_t*u, with the familiar 5 point central difference as the derivative approximation, I'm also attaching the result of -info | grep GAMG if that helps). My goal is to get weak and strong scaling results for the FD solver (leading me to double check all my parameters). I ran the sweep again as Mark suggested and it looks like my base params were close to optimal ( negative threshold and 10 levels of squaring with gmres/jacobi smoothers (chebyshev/sor is slower)).
[image: image.png] While I think that the base parameters should work well for strong scaling, do I have to modify any of my parameters for a weak scaling run ? Does GAMG automatically increase the number of mg-levels as grid size increases or is it upon the user to do that ? @Mark : Is there a GAMG implementation paper I should cite ? I've already added a citation for the Comput. Mech. (2007) 39: 497–507 as a reference for the general idea of applying agglomeration type multigrid preconditioning to helmholtz operators. Thank You, Sajid Ali | PhD Candidate Applied Physics Northwestern University s-sajid-ali.github.io
