Dear Ben and Oscar,

Thank you for the suggestions. Sorry if my query is not clear. To explain, I am trying to do loop modeling and at some situation I have to do cooperatively for about 12 loops. So, here I need to implement the multiple processing in modeller. I am here attaching the script (for single loop) that I have prepared to do on my 12 core processor. But, unfortunately I could not execute this because of the python script error, which I could not trace. From this point, I would like to get suggestion and help from your side. Please do the needful correction to my scripts and let me know where did I went wrong.

Thank you a Lot

On Fri, Apr 19, 2013 at 9:28 PM, Modeller Caretaker <modeller-care@salilab.org> wrote:

On 4/19/13 1:31 AM, Lalith Kumar wrote:

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.

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:

a = automodel(...)
j = job(host='localhost')
for i in range(12):
    j.append(local_slave())
a.use_parallel_job(j)

        Ben Webb, Modeller Caretaker
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Dr. Reddy's Institute of Life Sciences (Formerly known as Institute of Life Sciences)
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