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

[Jason Sarich]

BLMVM doesn't use a KSP or preconditioner, it updates using the L-BFGS-B
formula

On Thu, Jun 18, 2015 at 1:45 PM, Matthew Knepley <knepley at gmail.com> wrote:

>   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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