TITLE: Busy Days, Computational Science
AUTHOR: Eugene Wallingford
DATE: January 22, 2008  4:37 PM
DESC: 
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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
<A HREF="http://www.springerlink.com/content/t73q6574726k4777/">
   this paper</A>
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
<A HREF="http://www.amrita-ebook.org/">
   web site</A>,
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
<A HREF="http://www.literateprogramming.com/">
   literate programming</A>
using the concept of a <EM>program fold</EM>, 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
<A HREF="http://www.cs.uni.edu/~wallingf/blog/archives/monthly/2007-12.html#e2007-12-18T16_40_07.htm">
   SECANT workshop</A>.
The paragraph that made me sit up, though, was this lead-in
to his argument:

<BLOCKQUOTE><EM>
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.
</EM></BLOCKQUOTE>

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.
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