Forget Moore's Law?
Roland Piquepaille writes "On a day where CNET News.com releases a story named "Moore's Law to roll on for another decade," it's refreshing to look at another view. Michael S. Malone says we should forget Moore's law, not because it isn't true, but mainly because it has become dangerous. "An extraordinary announcement was made a couple of months ago, one that may mark a turning point in the high-tech story. It was a statement by Eric Schmidt, CEO of Google. His words were both simple and devastating: when asked how the 64-bit Itanium, the new megaprocessor from Intel and Hewlett-Packard, would affect Google, Mr. Schmidt replied that it wouldn't. Google had no intention of buying the superchip. Rather, he said, the company intends to build its future servers with smaller, cheaper processors." Check this column for other statements by Marc Andreessen or Gordon Moore himself. If you have time, read the long Red Herring article for other interesting thoughts."
BBC Article on the same story here.
Google supports thousands of user request sessions, not one huge straight-line serial command sequence. This means that a huge bunch of smaller servers will do the jobb quicker than a big super-server. Not only because of the raw computing power, but due to the parallellalism that is extracted by doing so and the loss of overhead introduced by running too many tasks on one server.
It's worth noting that the Earth Simulator is actually a cluster of vector mainframes (NEC SX-6s) using a custom interconnect. You could do something similar with the Cray X-1 if you had US$400M or so to spend.
If you're referring to the article I think you are, it was specifically talking in the context of weather simulation -- an application area where vector systems are known to excel (hence why the Earth Simulator does so well at it). The problem is that vector systems aren't always as cost-effective as clusters for a highly heterogeneous workload. With vector systems, a good deal of the cost is in the memory subsystem (often capable of several 10s of GB/s in memory bandwidth), but not every application needs heavy-duty memory bandwidth. Where I work, we've got benchmarks that show a cluster of Itanium-2 systems wiping the walls with a vector machine for some applications (specifically structural dynamics and some types of quantum chemistry calcuations), and others where a bunch of cheap AMDs beat everything in sight (on some bioinformatics stuff). It all depends on what your workload is.
"My life's work has been to prompt others... and be forgotten." --Cyrano de Bergerac
Computing the MD5 sum of 1TB of data. :-) MD5 depends on (among other things) being non-parallelizable for its security.