[Beowulf] Jupyter and EP HPC

Lux, Jim (337K) james.p.lux at jpl.nasa.gov
Mon Jul 30 15:38:58 PDT 2018


Job Queue?   At home, my experimental cluster is a pack of 4 beaglebones running a pretty vanilla debian - not exactly a mindbender in performance, but easy to fool with to experiment. 

At work, yeah, all the usual stuff.

Jim Lux
(818)354-2075 (office)
(818)395-2714 (cell)


-----Original Message-----
From: Gavin W. Burris [mailto:bug at wharton.upenn.edu] 
Sent: Monday, July 30, 2018 10:17 AM
To: Lux, Jim (337K) <james.p.lux at jpl.nasa.gov>
Cc: Fred Youhanaie <fly at anydata.co.uk>; beowulf at beowulf.org
Subject: Re: [Beowulf] Jupyter and EP HPC

Since this is Beowulf, I assume you have a job queue.  Check out the batch spawner, too.
https://github.com/jupyterhub/batchspawner

Cheers.


On Sat 07/28/18 10:21AM EDT, Lux, Jim (337K) wrote:
> That might be exactly it..
> thanks.
> 
> On 7/27/18, 2:17 PM, "Beowulf on behalf of Fred Youhanaie" <beowulf-bounces at beowulf.org on behalf of fly at anydata.co.uk> wrote:
> 
>     Jim
>     
>     I'm not a jupyter user, yet, however, out of curiosity I just googled for what I think you're looking for. Is this any good?
>     
>     https://ipyparallel.readthedocs.io/en/stable/
>     
>     I have now bookmarked it for my own future use!
>     
>     Cheers,
>     Fred
>     
>     On 27/07/18 21:56, Lux, Jim (337K) wrote:
>     > 
>     > -----Original Message-----
>     > From: Beowulf [mailto:beowulf-bounces at beowulf.org] On Behalf Of Joe Landman
>     > Sent: Friday, July 27, 2018 11:54 AM
>     > To: beowulf at beowulf.org
>     > Subject: Re: [Beowulf] Jupyter and EP HPC
>     > 
>     > 
>     > 
>     > On 07/27/2018 02:47 PM, Lux, Jim (337K) wrote:
>     >>
>     >> I’ve just started using Jupyter to organize my Pythonic ramblings..
>     >>
>     >> What would be kind of cool is to have a high level way to do some
>     >> embarrassingly parallel python stuff, and I’m sure it’s been done, but
>     >> my google skills appear to be lacking (for all I know there’s someone
>     >> at JPL who is doing this, among the 6000 people doing stuff here).
>     >>
>     >> What I’m thinking is this:
>     >>
>     >> I have a high level python script that iterates through a set of data
>     >> values for some model parameter, and farms out running the model to
>     >> nodes on a cluster, but then gathers the results back.
>     >>
>     >> So, I’d have N copies of the python model script on the nodes.
>     >>
>     >> Almost like a pythonic version of pdsh.
>     >>
>     >> Yeah, I’m sure I could use lots of subprocess() and execute() stuff
>     >> (heck, I could shell pdsh), but like with all things python, someone
>     >> has probably already done it before and has all the nice hooks into
>     >> the Ipython kernel.
>     >>
>     > 
>     > I didn't do this with ipython or python ... but this was effectively the way I parallelized NCBI BLAST in 1998-1999 or so.  Wrote a perl script to parse args, construct jobs, move data, submit/manage jobs, recover results, reassemble output.  SGI turned that into a product.
>     > 
>     > 
>     > -- yes.. but I was hoping someone had done that for Jupyter..
>     > 
>     >>>> for parametervalue in parametervaluelist:
>     > ....          result = simulation(parametervalue)
>     >                 Results.append(result)
>     > 
>     > 
>     > 
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--
Gavin W. Burris
Senior Project Leader for Research Computing The Wharton School University of Pennsylvania Search our documentation: http://research-it.wharton.upenn.edu/about/
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