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Re: AW: [NMusers] IMP and parallelisation

From: Leonid Gibiansky <lgibiansky_at_quantpharm.com>
Date: Tue, 20 Sep 2016 09:54:21 -0400

Hi Dirk,
What do you mean "does not solve the issue"? Were the results identical
with different number of nodes or not?
Thanks
Leonid

On 9/20/2016 9:47 AM, Dirk Garmann wrote:
> Thank you Leonid,
> We have tried RANMETHOD=P, which is an interesting possibility.
> Unfortunately this does not solve the issue. We will further evaluate if the information from all nodes is used for the population update.
> Any further hints are highly welcome
>
>
> Best
> Dirk
>
> -----Ursprüngliche Nachricht-----
> Von: Leonid Gibiansky [mailto:lgibiansky_at_quantpharm.com]
> Gesendet: Montag, 19. September 2016 22:26
> An: Dirk Garmann; nmusers_at_globomaxnm.com
> Betreff: Re: [NMusers] IMP and parallelisation
>
> It is a good idea to use RANMETHOD=P at estimation step; then the
> results should be identical independently of the number of nodes and
> computer load.
>
> Concerning specific behavior .. looks strange. I would try to start from
> the initial values of the model with the lowest OF and see what happens.
>
> Thanks
> Leonid
>
>
> On 9/19/2016 1:29 PM, Dirk Garmann wrote:
>> Dear nmusers.
>>
>> During a popPK analysis using the M3 method and IMP we observed an
>> unexpected behavior and would be interested if anyone else observed the
>> same and can provide guidance/explanations.
>>
>>
>>
>> The IMP produces "strange" results in cases requiring a parallelization.
>>
>> We observed a general (and strong) trend that with increasing number
>> of nodes the OBF increases (!) which in my opinion is unexpected if the
>> number of samples in MC is sufficiently large.
>>
>>
>>
>> The initial settings have been as follows:
>>
>> Parse Type 1
>>
>>
>>
>> $EST METHOD=IMP INTERACTION LAPLACIAN EONLY=0 ISAMPLE=300 NITER=1000
>> CTYPE=3 NOABORT GRD=SN(1,2) NOTHETABOUNDTEST PRINT=1
>>
>> $EST METHOD=IMP INTERACTION NOABORT GRD=SN(1,2) EONLY=1 ISAMPLE=3000
>> NITER=30 PRINT=1
>>
>>
>>
>> With 1 node the OBF decreased to ~- 1400
>>
>> Using 16 nodes the OBF stabilized at ~ 1000
>>
>> In both cases the OBF does not fluctuate much after 100 interations
>> (monitoring of EM step) and seems to be stable (no clear hint for a
>> local minima).
>>
>> Interestingly the estimated residual error is higher using 1 node. With
>> 16 nodes the variability seems to be shifted to the ETAS.
>>
>>
>>
>> This behavior might be a concern for a covariate analysis using IMP
>>
>> Our first assumption was that we need to increase iSAMPLE in the EM
>> step, since a different seed might be used for each node. However even
>> increasing ISAMPLE to 3000 in the first step did not change the results
>> much.
>>
>> My guess is that it points in the direction of how population values are
>> updated, but I am not an expert in the implementation of IMP in NONMEM
>>
>>
>>
>> We would be highly interested in any guidance and explanation.
>>
>>
>>
>> Many thanks in advance
>>
>>
>>
>> Dirk
>>
>>
>>
>> Freundliche Grüße / Best regards,
>>
>>
>>
>> Dirk Garmann
>>
>> Head Quantitative Pharmacology
>>
>>
>>
>>
>>
>> Bayer Pharma Aktiengesellschaft
>>
>> BPH-DD-CS-CP-QP, Quantitative Pharmacology
>>
>> Building 0431, 322
>>
>> 51368 Leverkusen, Germany
>>
>>
>>
>> Tel: +49 202 365577
>>
>> Fax:
>>
>> Mobile: +49 175 3109407
>>
>> E-mail: _dirk.garmann_at_bayer.com_
>>
>> Web: _http://www.bayer.com_
>>
>>
>>
>> Vorstand: Dieter Weinand, Vorsitzender | Christoph Bertram
>>
>> Vorsitzender des Aufsichtsrats: Hartmut Klusik
>>
>> Sitz der Gesellschaft: Berlin | Amtsgericht Charlottenburg, HRB 283 B
>>
>>
>>
>>
>>
>>
>>
>
Received on Tue Sep 20 2016 - 09:54:21 EDT

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