To the PyCluster!

Enthought is a proud sponsor of the second annual PyGotham conference in New York City (June 8th and 9th). As part of our commitment, we are also offering a High Performance Python track that will illustrate how to build applications and utilize parallel computing techniques with various open source projects. Stayed tuned for more details as they become available.

Here’s the lineup so far:

• Python with Parallelism in Mind. Rarely does code just happen to be “embarrassingly parallel.” We will discuss some simple rules, structural changes, and diagnostic tools that can help optimize the parallel efficiency of your code. This session will also introduce several common parallel communication technologies that can lower the barrier to parallel computing.
• GPU Computing with CLyther. GPU computing has come a long way over the past few years but still requires knowledge of CUDA or OpenCL. Similar to Cython, CLyther is a Python language extension that makes writing OpenCL code as easy as Python itself.
• MapReduce with the Disco Project. MapReduce frameworks provide a powerful abstraction for distributed data storage and processing. Our friend, Chris Mueller, will talk about the Disco Project, a refreshing alternative to the Hadoop hegemony that uses Python for the front-end and Erlang for the back-end. More importantly, he will discuss when a MapReduce framework makes sense and when it doesn’t.
• Interactive Plotting with Chaco. Most “big data” problems don’t stop with distributed computation. You have to render your results in a way that a larger audience can understand. Chaco is an open source library that helps developers generate performant, interactive data visualizations.
• Declarative UIs with Enaml. Enaml is pythonic UI development done right. Enaml shares Python’s goals of simplicity, conciseness and elegance. Enaml implements a constraint based layout system which ensures that UI’s built with Enaml behave and appear identical on Windows, Linux and OSX. This introduction to Enaml will get you started on the path of writing non trivial UI’s in an afternoon.
• Tie It Together: Build An App. In an updated version of his Pycon talk, Jonathan Rocher ties together time series data — from storage to analysis to visualization — in a demo application. We’ll also walk through a more computationally demanding application to illustrate concepts introduced in the previous talks.

Look forward to seeing everyone there!