Justin, Since the PETSc logging cannot "see" into the hypre run it doesn't have any information about the times for constructing the AMG levels, so yes is less informative than with GAMG.
You can get some information about the decisions hypre BoomerAMG made with the option -pc_hypre_boomeramg_print_statistics Barry > On Sep 24, 2015, at 8:21 PM, Justin Chang <[email protected]> wrote: > > Hi all, > > I ran both BoomerAMG and GAMG. It seems to me there is a lot more "info" in > GAMG's log_summary than the one for Hypre's BoomerAMG. Is the latter > completely documented within PETSc's log_summary? Because I am not sure these > performance metrics make sense to me. > > Attached are the -log_summary and -info outputs for the respective solvers. > > Thanks, > Justin > > On Mon, Sep 21, 2015 at 1:25 PM, Justin Chang <[email protected]> wrote: > Okay I will just experiment around with these then. Thanks for the input > everyone > > On Mon, Sep 21, 2015 at 6:21 AM, Mark Adams <[email protected]> wrote: > And I will just add that performance is sensitive to parameters. The defaults > try to be conservative and hypre's seem to be geared for 2D low order > discretizations. GAMG is probably a bit more geared for 3D. If you are > interested in looking this carefully you can run GAMG with '-info', and grep > on GAMG, and send us the results and we can verify that it running OK. Also > run with -log_summary and send that separately. The two solvers should be > about the same speed on your problem. > > > On Fri, Sep 18, 2015 at 7:36 AM, Jed Brown <[email protected]> wrote: > Justin Chang <[email protected]> writes: > > I see that there's GAMG and there's Hypre's BoomerAMG (and perhaps others > > too?) > > ML > > > What exactly is the difference between these two? Do they have very > > different implementations under the hood? Does one have better > > scalability over another? Or more importantly, when would I choose one > > over the other? > > BoomerAMG is classical AMG, which is a different coarsening strategy > From GAMG and ML which use smoothed aggregation. The math is different > and the implementation is different. ML and GAMG have similar math and > there exist configurations that are equivalent. > > > > <GAMG_info.txt><GAMG_logsummary.txt><HYPRE_info.txt><HYPRE_logsummary.txt>
