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

[Matthew Knepley]

On Thu, Jun 18, 2015 at 1:52 PM, Jason Sarich <jason.sarich at gmail.com>
wrote:

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

Then this sounds like a bug, unless one of the constants is partition
dependent.

  Matt


> 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
>>
>
>


-- 
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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