Neat setup, Jim.  I'm planning on rolling out Jupyterhub as a supported service 
sometime soon, with kernels for as many of our software packages / shells / 
languages as possible.  Please let me know how your experimenting goes.  Cheers.

On Mon 07/30/18 06:38PM EDT, Lux, Jim (337K) wrote:
> 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:b...@wharton.upenn.edu] 
> Sent: Monday, July 30, 2018 10:17 AM
> To: Lux, Jim (337K) <james.p....@jpl.nasa.gov>
> Cc: Fred Youhanaie <f...@anydata.co.uk>; beowulf@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-boun...@beowulf.org on behalf of f...@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-boun...@beowulf.org] On Behalf Of Joe 
> > Landman
> >     > Sent: Friday, July 27, 2018 11:54 AM
> >     > To: beowulf@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: 
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Senior Project Leader for Research Computing
The Wharton School
University of Pennsylvania
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