Wednesday, July 7, 2010

aero nebula cluster

For those who do not know, i'm currently in my last year of the DD program in Aerospace engineering, and my project is implementation of solid mechanics code using SPH (smoothed particle hydrodynamics) integrated into the pysph project.
It pysph is basically a SPH implementation framework written in python/cython. (Now you know my reason for all those optimization posts :) ).
Now for most CFD codes, you need to run them in parallel on clusters so as to reduce the time required. So i just saw the specs of the nebula cluster (on which i have login) in aero department. Its really wonderful. The specs are:
20 nodes (15 working) each node with 12 six-core AMD opteron 2427 processors with 2.2 GHz xloxk speed and 12 GB RAM, in all 180 6-core processors.
This is sure gonna make parallelizing much more fun and interesting.
PS: I just rad and saw quite a few videos from google about their patented map-reduce technique. It would be interesting to implement SPH in map-reduce and let it run in the "cloud", the buzzword of today.


  1. I have just begun looking into SPH/Map-reduce myself. I have focused on the Apache/hadoop framework for map-reduce. It looks promising.

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