AW: [NMusers] IMP and parallelisation

From: Dirk Garmann <dirk.garmann_at_bayer.com>
Date: Tue, 20 Sep 2016 13:47:09 +0000

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 th=
e 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=1=
000
> CTYPE=3 NOABORT GRD=SN(1,2) NOTHETABOUNDTEST PRINT=1
>
> $EST METHOD=IMP INTERACTION NOABORT GRD=SN(1,2) EONLY=1 ISAMPLE=3=
000
> 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
>
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>
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>
> E-mail: _dirk.garmann_at_bayer.com_
>
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>
>
>
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>
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>
Received on Tue Sep 20 2016 - 09:47:09 EDT

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