<html><head><meta http-equiv="content-type" content="text/html; charset=us-ascii"></head><body style="overflow-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;"><div><br></div> The default is some kind of Jacobi plus Chebyshev, for a certain class of problems, it is quite good.<div><br></div><div><br><div><br><blockquote type="cite"><div>On Jan 10, 2023, at 3:31 PM, Mark Lohry <mlohry@gmail.com> wrote:</div><br class="Apple-interchange-newline"><div><div dir="ltr"><div></div><div>So what are people using for GAMG configs on GPU? I was hoping petsc today would be performance competitive with AMGx but it sounds like that's not the case?<br></div></div><br><div class="gmail_quote"><div dir="ltr" class="gmail_attr">On Tue, Jan 10, 2023 at 3:03 PM Jed Brown <<a href="mailto:jed@jedbrown.org">jed@jedbrown.org</a>> wrote:<br></div><blockquote class="gmail_quote" style="margin:0px 0px 0px 0.8ex;border-left:1px solid rgb(204,204,204);padding-left:1ex">Mark Lohry <<a href="mailto:mlohry@gmail.com" target="_blank">mlohry@gmail.com</a>> writes:<br>
<br>
> I definitely need multigrid. I was under the impression that GAMG was<br>
> relatively cuda-complete, is that not the case? What functionality works<br>
> fully on GPU and what doesn't, without any host transfers (aside from<br>
> what's needed for MPI)?<br>
><br>
> If I use -ksp-pc_type gamg -mg_levels_pc_type pbjacobi -mg_levels_ksp_type<br>
> richardson is that fully on device, but -mg_levels_pc_type ilu or<br>
> -mg_levels_pc_type sor require transfers?<br>
<br>
You can do `-mg_levels_pc_type ilu`, but it'll be extremely slow (like 20x slower than an operator apply). One can use Krylov smoothers, though that's more synchronization. Automatic construction of operator-dependent multistage smoothers for linear multigrid (because Chebyshev only works for problems that have eigenvalues near the real axis) is something I've wanted to develop for at least a decade, but time is always short. I might put some effort into p-MG with such smoothers this year as we add DDES to our scale-resolving compressible solver.<br>
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