[yt-users] HaloFinder- parallel is slower?

[Cameron Hummels]

Maybe it's running low on memory in the parallel case where you use all 
8 processors on a node.  Why don't you try doing it with 7 or 6 ppn and 
see if that changes things.  Britton suggested experimenting with the 
parameters in his previous email, so why not try?  You can always ssh to 
the node where your job is running and look at the memory consumption to 
see if it's running low.  Above all, experiment on your own to try to 
figure these things out.

Cameron

Agarwal, Shankar wrote:
> Hi,
>
> I ran yt's HaloFinder routine on 1 processor, and then on 8 processors. Both give identical output : 40,000 halos starting from 512^3 particles.
>
> 1 processor   :   took 1 hour 45 minutes.
> 8 processors :   took 2 hours.
>
>
> My script is  hop_yt.py....
>
> from yt.mods import *
> fn = "RedshiftOutput0002"
> pf = load(fn)
> halos = HaloFinder(pf,40,padding=0.02)
> halos.write_out("HopAnalysis.out")
>
>
> commands I used....
>
> mpirun -np 1 python hop_yt.py --parallel
> mpirun -np 8 python hop_yt.py --parallel
>
>
> Any idea why 8 cpus would take longer ?
>
>
> shankar
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>
>   

-- 
Cameron Hummels
PhD Candidate, Astronomy Department of Columbia University
Public Outreach Director, Astronomy Department of Columbia University
NASA IYA New York State Student Ambassador
http://outreach.astro.columbia.edu