Dear Leonid Still in the evaluation phase. I thought it was already finished but still running (long run times). I will keep you informed if the results are identical
Best Dirk -----Ursprüngliche Nachricht----- Von: Leonid Gibiansky [mailto:lgibian...@quantpharm.com] Gesendet: Dienstag, 20. September 2016 15:54 An: Dirk Garmann; nmusers@globomaxnm.com Betreff: Re: AW: [NMusers] IMP and parallelisation 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:lgibian...@quantpharm.com] > Gesendet: Montag, 19. September 2016 22:26 > An: Dirk Garmann; nmusers@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@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 >> >> >> >> >> >> >> >
