Hi Justin, I can't tell for sure why this is happening, have you tried using quad precision to make sure that numerical cutoffs isn't the problem?
1 The Hessian being approximate and the resulting implicit computation is the source of the cutoff, but would not be causing different convergence rates in infinite precision. 2 the local size may affect load balancing but not the resulting norms/convergence rate. Jason On Thu, Jun 18, 2015 at 10:44 AM, Justin Chang <[email protected]> wrote: > I solved a transient diffusion across multiple cores using TAO BLMVM. > When I simulate the same problem but on different numbers of processing > cores, the number of solve iterations change quite drastically. The > numerical solution is the same, but these changes are quite vast. I > attached a PDF showing a comparison between KSP and TAO. KSP remains > largely invariant with number of processors but TAO (with bounded > constraints) fluctuates. > > My question is, why is this happening? I understand that accumulation of > numerical round-offs may attribute to this, but the differences seem quite > vast to me. My initial thought was that > > 1) the Hessian is only projected and not explicitly computed, which may > have something to do with the rate of convergence > > 2) local problem size. Certain regions of my domain have different number > of "violations" which need to be corrected by the bounded constraints so > the rate of convergence depends on how these regions are partitioned? > > Any thoughts? > > Thanks, > Justin >
