On Fri, Jan 22, 2016 at 9:27 AM, Mark Adams <[email protected]> wrote: > >> >> I said the Hypre setup cost is not scalable, >> > > I'd be a little careful here. Scaling for the matrix triple product is > hard and hypre does put effort into scaling. I don't have any data > however. Do you? >
I used it for PyLith and saw this. I did not think any AMG had scalable setup time. Matt > but it can be amortized over the iterations. You can quantify this >> just by looking at the PCSetUp time as your increase the number of >> processes. I don't think they have a good >> model for the memory usage, and if they do, I do not know what it is. >> However, generally Hypre takes more >> memory than the agglomeration MG like ML or GAMG. >> >> > agglomerations methods tend to have lower "grid complexity", that is > smaller coarse grids, than classic AMG like in hypre. THis is more of a > constant complexity and not a scaling issue though. You can address this > with parameters to some extent. But for elasticity, you want to at least > try, if not start with, GAMG or ML. > > >> Thanks, >> >> Matt >> >> >>> >>> Giang >>> >>> On Mon, Jan 18, 2016 at 5:25 PM, Jed Brown <[email protected]> wrote: >>> >>>> Hoang Giang Bui <[email protected]> writes: >>>> >>>> > Why P2/P2 is not for co-located discretization? >>>> >>>> Matt typed "P2/P2" when me meant "P2/P1". >>>> >>> >>> >> >> >> -- >> What most experimenters take for granted before they begin their >> experiments is infinitely more interesting than any results to which their >> experiments lead. >> -- Norbert Wiener >> > > -- What most experimenters take for granted before they begin their experiments is infinitely more interesting than any results to which their experiments lead. -- Norbert Wiener
