Ganesh Swami

Fifteen Mac-vs-PC commercials back to back:

Do you really have to stoop to such low levels?

Chistophe Bisciglia, an engineer from Google, is teaching a course at the University of Washington. The course focuses on problem solving on large-scale clusters. The complete course material is available on the homepage.

I think there’s a huge potential for programs to analyze voluminous amounts of data. Most data analysis is done either using Excel, or using command line tools such as awk and sed. A smart way to distribute the post-processing or analysis would be cool.

I was surprised to learn today that there was a difference between statistical and stochastic simulation. I quote from the latest issue of Computing in Science & Engineering:

We can divide existing approaches to uncertainty quantification into two classes: statistical and stochastic. Statistical approaches include brute-force Monte Carlo simulations (MCS), accelerated MCS (such as quasi-Monte Carlo and Markov chain Monte Carlo methods), importance-sampling techniques, variance-reduction schemes, and response surface methods. Stochastic approaches consist of direct methods (such as interval analysis, operator-based approaches, and polynomial chaos expansions) and indirect methods (such as Fokker-Plank and moment equations). This special issue of Computing & Engineering magazine is devoted to recent advances in stochastic methods.