Algorithms for Parallel Universes (potentially)

This last week, I attended a seminar called "Proven Algorithmic Techniques for Manycore Processors", presented by the Virtual School of Computational Science and Engineering (VSCSE), which is sponsored by the NCSA at the University of Illinois Urbana-Champaign (the same people who head up the Blue Waters supercomputer initiative). The topic was developing algorithms suitable for the architecture of many-core processors. This seminar opened by eyes to the challenges imposed by large, non-uniform datasets, not only in the context of parallel computing, but also as a broader research topic for statisticians and applied mathematics.

The focus of this seminar was on applications for the Graphical Processing Unit (GPU) technology developed by nVIDIA. The level and extent of instruction, especially from Dr. Hwu, was excellent. This is part of the NCSA summer school initiative, which is very useful for covering niche topics. I attended the "Big Data for Science" seminar last year, which was also very good). Here are my written notes from the session (I always find that written notes helps along the learning process).