Guang,

We will allocate 50K core-hours to your project to parallelize your code with MPI and to get started.  When you can demonstrate good parallel scaling up to hundreds or core with your code, we can discuss increasing your allocation. 

John J. Low

Principal Computational Science Specialist

Computing, Environment and Life Sciences

Building 240, 2143

9700 South Cass Avenue

Argonne National Laboratory

Argonne, IL 60439.

630-252-0045

www.linkedin.com/pub/john-low/15/8b0/5aa/

From: Guang Yang <gyang9@hawk.iit.edu>
Date: Tuesday, March 24, 2015 at 7:21 PM
To: "Low, John J." <jlow@mcs.anl.gov>
Subject: Re: [allocations-admins] FW: [LCRC Accounts] Project Request: NeutrinoSim

Hi John,

I also learned how to use MPI just now from a guy in our division.

I think I got clear with this thing and could run jobs with MPI.

So for the non-sequential jobs with only different random seeds, I can efficiently use the cores.

Please let me know if we could get the core hours.

Thanks,
Guang

On Tue, Mar 24, 2015 at 3:02 PM, Guang Yang <gyang9@hawk.iit.edu> wrote:

Hi John,

Thank you very much.

I read it and I think the task farmer and apron with listing different job scripts methods are quite straightforward to me.

My jobs can run in parallel. For example, generating 100,000 random events takes too long. So I would break it into 100 jobs *1000 events. (1,000 events takes 1 hour and half.)  They are not sequential.

Just make sure that if I can do something like:

1.#PBS -q regular

02.#PBS -l mppwidth=144

03.#PBS -l walltime=12:00:00

04.#PBS -N my_job

05.#PBS -e my_job.$PBS_JOBID.err

06.#PBS -o my_job.$PBS_JOBID.out

07. 

08.cd $PBS_O_WORKDIR

09.aprun -n 32 ./a.out &

10.aprun -n 65 ./b.out &

11.aprun -n 24 ./c.out &

12.wait




Then I can definitely run them in parallel. I may just have 16 exactly same job scripts.




Thanks, 

Guang

On Tue, Mar 24, 2015 at 2:38 PM, Low, John J. <jlow@mcs.anl.gov> wrote:

Guang,

Shashi Aithal suggested this link to more examples of running parallel
jobs in this link.
https://www.nersc.gov/users/computational-systems/hopper/running-jobs/examp
le-batch-scripts/

John J. Low
Principal Computational Science Specialist
Computing, Environment and Life Sciences
Building 240, 2143
9700 South Cass Avenue
Argonne National Laboratory
Argonne, IL 60439.
630-252-0045
www.linkedin.com/pub/john-low/15/8b0/5aa/