Python for Scientific Computing at SIAM CSE 2009: Slides

At the 2009 SIAM CSE meeting held in Miami on March 2-6, Randy LeVeque from U. Washington, Hans-Petter Langtangen from the Simula Research Laboratory in Norway and I co-organized a 3-part minisymposium entitled Python for Scientific Computing. This was done partly as a followup to the successful one we had last year, and we had again good attendance and lively discussions. See a short blog post of mine for some more thoughts on the event, this page is just for hosting the slides.


SIAM News published a full writeup of this event. Here are both a PDF suitable for printing and the version SIAM put on their site:

The minisymposium was divided in three parts, and I am posting here links to the original program pages as well as all the slides I have so far from the speakers, along with any links they may have provided to their personal or project pages.

Part I

9:30-9:55 Experience with Python in a Major Computational Science Teaching Reform. Hans Petter Langtangen, Simula Research Laboratory, Norway.

10:00-10:25 PyCuda and PyUblas. Andreas Klöckner, Brown University.

10:30-10:55 Use of High-Level User Interfaces for Software Sustainability. Leroy A. Drummond, Lawrence Berkeley National Laboratory.

11:00-11:25 FiPy: A PDE Solver for Materials Science (Project site). Jon Guyer, Daniel Wheeler, and James Warren, National Institute of Standards and Technology.

Part II

2:00-2:25 Exploring Network Structure, Dynamics, and Function using NetworkX. Aric Hagberg, Los Alamos National Laboratory.

2:30-2:55 Matplotlib: Data Visualization in Python. John Hunter, Tradelink, Inc.

3:00-3:25 VisIt’s Python Interface for Visualization and Analysis. Hank Childs, Brad Whitlock, and Cyrus Harrison, Lawrence Livermore National Laboratory.

3:30-3:55 An Efficient Computer Algebra System for Python. Pearu Peterson, Tallinn Technical University, Estonia.

Part III

4:30-4:55 IPython: Components for Interactive Scientific Computing. Fernando Perez, University of California, Berkeley; Brian Granger, California Polytechnic State University, San Luis Obispo.

5:00-5:25 Distributed Data Structures, Parallel Computing and IPython. Brian Granger, California Polytechnic State University, San Luis Obispo; Fernando Perez, University of California, Berkeley.

5:30-5:55 Teaching Astronomical Data Analysis in Python (or in OpenOffice format, if you prefer it to PowerPoint). Joseph Harrington, University of Central Florida.

6:00-6:25 MPI for Python (mpi4py). Lisandro Dalcin, Centro Int. de Métodos Computacionales en Ingeniería, Argentina (presentation delivered by Brian Granger, as Lisandro could not attend the meeting) . Note: The previous link points to a locally hosted copy of the slides; this is a static tarball.