On 4/19/13 1:31 AM, Lalith Kumar wrote:Since you don't say what you've tried, or what problems you ran into, it's difficult to help you. Modeller doesn't use all the processors by default. To take advantage of multiple cores, you can either split your job manually (as Oscar suggests) or have Modeller do it for you automatically. To do the latter, you need to set up a parallel job object and then call a.use_parallel_job(). How you create the parallel job object depends on how you want to parallelize your job (e.g. whether you want to use a batch scheduling system). To just use 12 cores on the local machine, something like the following should work:
I am running mod9v11 on Intel Xeon with 12 cores processor. I have found
that modeller is utilizing only single processor. Even though there are
few older posts regarding the execution of modeller processors on
multiple processors, I am unable to implement them. Sorry, I am newbie
to python.
a = automodel(...)
j = job(host='localhost')
for i in range(12):
j.append(local_slave())
a.use_parallel_job(j)
Ben Webb, Modeller Caretaker
--
" target="_blank"> http://www.salilab.org/modeller/
Modeller mail list: http://salilab.org/mailman/listinfo/modeller_usage
Attachment:
loop-refine.py
Description: Binary data