TITLE: Busy Days, Computational Science AUTHOR: Eugene Wallingford DATE: January 22, 2008 4:37 PM DESC: ----- BODY: Some days, I want to write but don't have anything to say. The start of the semester often finds me too busy doing things to do anything else. Plowing through the arcane details of Unix basic regular expressions that I tend not to use very often is perhaps the most interesting thing I've been doing. Over the weekend, I did have a chance to read this paper by James Quirk, a computational scientist who has built a sophisticated simulation-and-documentation system called AMRITA. (You can download the paper as a PDF from his web site, by following About AMRITA and clinking on the link "Computational Science: Same Old Silence, Same Old Mistakes".) Quirk's system supports a writing style that interleaves code and commentary in the spirit of literate programming using the concept of a program fold, which at one level is a way to specify a different processor for each item in a tree of structured text items. The AMRITA project is an ambitious mixture of (1) demonstrating a new way to communicate computational science results and (2) arguing for software standards that make it possible for computational scientists to examine one another's work effectively. The latter point is essential if computational science is to behave like science, yet the complexity of most simulation programs almost precludes examination, replication, and experimentation with the ideas they implement. Much of what Quirk says about scientists as programmers meshes with what I wrote in my reports on November's SECANT workshop. The paragraph that made me sit up, though, was this lead-in to his argument:
The AMR simulation shown in Figure 1 was computed July 1990.... It took just over 12 hours to run on a Sun SPARCstation 1. In 2003 it can be run on an IBM T30 laptop in a shade over two minutes.
It is sobering occasionally to see the advances in processors and other hardware presented in such concrete terms. I remember programming on a Sun SPARCstation 1 back in the early '90s, and how fast it seemed! By 2003 a laptop could perform more than 300 times faster on a data-intensive numeric simulation. How much faster still by 2008? Quirk is interested in what this means for the conduct of computational science. "What should the computational science community be doing over and above scaling up the sizes of the problems it computes?" That is the heart of his paper, and much of the motivation behind AMRITA. -----