[petsc-users] Varying TAO optimization solve iterations using BLMVM

[Jason Sarich]

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 <jychang48 at gmail.com> 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
>
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