Skip to main content

Python goes to Reno: SIAM CSE 2011

In what's becoming a bit of a tradition, Simula's Hans-Petter Langtangen, U. Washington's Randy LeVeque and I co-organized yet another minisymposium on Python for Scientific computing at a SIAM conference.

At the Computational Science and Engineering 2011 meeting, held in Reno February 28-March 4, we had 2 sessions with 4 talks each (part I and II).  I have put together a page with all the slides I got from the various speakers, that also includes slides from python-related talks in other minisymposia.  I have also posted some pictures from our sessions and from the minisymposium on reproducible research that my friend and colleague Jarrod Millman organized during the same conference.

We had great attendance, with a standing-room-only crowd for the first session, something rather unusual during the parallel sessions of a SIAM conference.  But more importantly, this year there were three other sessions entirely devoted to Python in scientific computing at the conference, organized completely independently from ours.  One focused on PDEs and the other on optimization.  Furthermore, there were scattered talks at several other sessions where Python was explicitly discussed in the title or abstract.  For all of these, I have collected the slides I was able to get; if you have slides for one such talk I failed to include, please contact me and I'll be happy to post them there. 

Unfortunately for our audience, we had last-minute logistical complications that prevented Robert Bradshaw and John Hunter from attending, so I had to deliver the Cython and matplotlib talks (in addition to my IPython one).  Having a speaker give three back-to-back talks isn't ideal, but both of them kindly prepared all the materials and "delivered" them to me over skype the day before, so hopefully the audience got a reasonable simile of their original intent. It's a shame, since I know first-hand how good both of them are as speakers, but canceling talks on these two key tools would really have been a disservice to everyone; my thanks go to the SIAM organizers who were flexible enough to allow for this to happen.  Given how packed the room was, I'm sure we made the right choice.

It's now abundantly clear from this level of interest that Python is being very successful in solving real problems in scientific computing.  We've come a long way from the days when some of us (I have painful memories of this) had to justify to our colleagues/advisors why we wanted to 'play' with this newfangled 'toy' instead of just getting on with our job using the existing tools (in my case it was IDL, a hodgepodge of homegrown shell/awk/sed/perl scripting, custom C and some Gnuplot thrown in the mix for good measure).  Things are by no means perfect, and there's plenty of problems to solve, but we have a great foundation, a number of good quality tools that continue to improve as well as our most important asset: a rapidly growing community that is solving new problems, creating new libraries and coming up with innovative approaches to computational and mathematical questions, often facilitated by Python's tremendous flexibility. It's been a fun ride so far, but I suspect the next decade is going to be even more interesting.  If you missed this, try to make it to SciPy 2011 or EuroSciPy 2011!

Link summary


Comments

Unknown said…
Well, from the photos I can see that you were impressed by Reno's countryside, just like I am always! Reno is a great place to live. :)

Popular posts from this blog

Blogging with the IPython notebook

Update (May 2014): Please note that these instructions are outdated. while it is still possible (and in fact easier) to blog with the Notebook, the exact process has changed now that IPython has an official conversion framework. However, Blogger isn't the ideal platform for that (though it can be made to work). If you are interested in using the Notebook as a tool for technical blogging, I recommend looking at Jake van der Plas' Pelican support or Damián Avila's support in Nikola . Update: made full github repo for blog-as-notebooks, and updated instructions on how to more easily configure everything and use the newest nbconvert for a more streamlined workflow. Since the notebook was introduced with IPython 0.12 , it has proved to be very popular, and we are seeing great adoption of the tool and the underlying file format in research and education. One persistent question we've had since the beginning (even prior to its official release) was whether it would...

Help save open space in the Bay Area by protecting Knowland Park from development

Vote NO on new Tax Measure A1 Update:  there is now evidence that Zoo officials have actually violated election laws  in their zeal to promote measure A1. I normally only blog about technical topics, but the destruction of a beautiful piece of open space in the Bay Area is imminent, and I want to at least do a little bit to help prevent this disaster. In short: there's a tax measure on the November ballot, Measure A1 , that would impose a parcel tax on all residences and businesses in Alameda County to fund the Oakland Zoo for the next 25 years .  The way the short text on the ballot is worded makes it appear as something geared towards animal care for a cash-strapped Zoo.  The sad reality is that the full text of the measure allows the Zoo to use these funds for a very controversial expansion plan that includes a 34,000 sq. ft. visitor center, gift shop and restaurant serviced by a ski gondola atop one of the last pristine remaining ridges in Knowland Park, ...

An ambitious experiment in Data Science takes off: a biased, Open Source view from Berkeley

Today, during a White House OSTP event combining government, academia and industry, the Gordon and Betty Moore Foundation and the Alfred P. Sloan Foundation announced a $37.8M funding commitment to build new data science environments. This caps a year's worth of hard work for us at Berkeley, and even more for the Moore and Sloan teams, led by Vicki Chandler , Chris Mentzel and Josh Greenberg : they ran a very thorough selection process to choose three universities to participate in this effort. The Berkeley team was led by Saul Perlmutter , and we are now thrilled to join forces with teams at the University of Washington and NYU, respectively led by Ed Lazowska and Yann LeCun . We have worked very hard on this in private, so it's great to finally be able to publicly discuss what this ambitious effort is all about. Most of the UC Berkeley BIDS team, from left to right: Josh Bloom, Cathryn Carson, Jas Sekhon, Saul Perlmutter, Erik Mitchell, Kimmen Sjölander, Jim Sethia...