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

[Justin Chang]

My code sort of requires HDF5 so installing quad precision might be a
little difficult. I could try to work around this but that might take some
effort.

In the mean time, is there any other potential explanation or alternative
to figuring this out?

Thanks,
Justin

On Thursday, June 18, 2015, Matthew Knepley <knepley at gmail.com> wrote:

> On Thu, Jun 18, 2015 at 1:52 PM, Jason Sarich <jason.sarich at gmail.com
> <javascript:_e(%7B%7D,'cvml','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
>> <javascript:_e(%7B%7D,'cvml','knepley at gmail.com');>> wrote:
>>
>>>   On Thu, Jun 18, 2015 at 12:15 PM, Jason Sarich <jason.sarich at gmail.com
>>> <javascript:_e(%7B%7D,'cvml','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
>>>> <javascript:_e(%7B%7D,'cvml','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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