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

[Matthew Knepley]

On Thu, Jun 18, 2015 at 12:15 PM, Jason Sarich <jason.sarich at gmail.com>
wrote:

> 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.
>

This sounds to be like the preconditioner is dependent on the partition.
Can you send -tao_view -snes_view

  Matt


> 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
>>
>
>


-- 
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
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