The New York Times The New York Times Science June 25, 2002  

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At Los Alamos, Two Visions of Supercomputing

(Page 2 of 2)

"All of us who are in this game are busy learning how to run these big machines," said Dr. Mike Levine, a scientific director at the Pittsburgh Supercomputing Center and a physics professor at Carnegie Mellon University. A project like Green Destiny is "a good way to get people's attention," he said, "but it is only the first step in solving the problem."


Green Destiny belongs to a class of makeshift supercomputers called Beowulf clusters. Named for the monster-slaying hero in the eighth-century Old English epic, the machines are made by stringing together off-the-shelf PC's into networks, generally communicating via Ethernet the same technology used in home and office networking. What results is supercomputing for the masses or, in any case, for those whose operating budgets are in the range of tens or hundreds of thousands of dollars rather than the hundreds of millions required for Q.

Dr. Feng's team, which also includes Dr. Michael S. Warren and Eric H. Weigle, began with a similar approach. But while traditional Beowulfs are built from Pentium chips and other ordinary processors, Green Destiny uses a special low-power variety intended for laptop computers.

A chip's computing power is ordinarily derived from complex circuits packed with millions of invisibly tiny transistors. The simpler Transmeta chips eliminate much of this energy-demanding hardware by performing important functions using software instead instructions coded in the chip's memory. Each chip is mounted along with other components on a small chassis, called a blade. Stack the blades into a tower and you have a Bladed Beowulf, in which the focus is on efficiency rather than raw unadulterated power.

The method has its limitations. A computer's power depends not just on the speed of its processors but on how fast they can cooperate with one another. Linked by high-speed fiber-optical cable, Q's many subsections, or nodes, exchange data at a rate as high as 6.3 gigabits a second. Green Destiny's nodes are limited to 100-megabit Ethernet.

The tightly knit communication used by Q is crucial for the intense computations involved in modeling nuclear tests. A weapons simulation recently run on the Accelerated Strategic Computing Initiative's ASCI White supercomputer at Lawrence Livermore National Laboratory in California took four months of continuous calculating time the equivalent of operating a high-end personal computer 24 hours a day for more than 750 years.

Dr. Feng has looked into upgrading Green Destiny to gigabit Ethernet, which seems destined to become the marketplace standard. But with current technology that would require more energy consumption, erasing the machine's primary advantage.

For now, a more direct competitor may be the traditional Beowulfs with their clusters of higher-powered chips. Though they are cheaper and faster, they consume more energy, take up more space, and are more prone to failure. In the long run, Dr. Feng suggests, an efficient machine like Green Destiny might actually perform longer chains of sustained calculations.

At some point, in any case, the current style of supercomputing is bound to falter, succumbing to its own heat. Then, Dr. Feng hopes, something like the Bladed Beowulfs may serve as "the foundation for the supercomputer of 2010."

Meanwhile, the computational arms race shows no signs of slowing down. Half of the computing floor at the Metropolis Center has been left empty for expansion. And ground was broken this spring at Lawrence Livermore for a new Terascale Simulation Facility. It is designed to hold two 100-teraops machines.

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Los Alamos National Laboratory
"Bigger and faster machines simply aren't good enough," said Dr. Wu-Chung Feng, a builder of a fast, efficient computer, Green Destiny.


Two Approaches to Massive Computation

Interactive Feature: Two Approaches to Massive Computation


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A faster, less efficient computer, Q, shows how density varies as a shock wave passes from one material to the next.

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