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Top500 shows growing inequality in supercomputing power

The top supercomputers are getting faster while development of midlevel systems is starting to stagnate

By Joab Jackson
November 20, 2013 05:42 PM ET

IDG News Service - Supercomputing power is being concentrated in a smaller number of machines, according to the latest Top500 list of high-performance computers. Keepers of the list are uncertain how to parse that trend.


   Jack Dongarra
Jack Dongarra, creator of the Linpack benchmark, and one of the organizers of the Top500 ranking of supercomputing.

The first 17 entrants in the latest supercomputer ranking produce half of all the supercomputing power on the list, which totaled over 250 petaflop/s (quadrillions of calculations per second), noted Erich Strohmaier, an organizer of the Top500 twice-yearly ranking of the world's most powerful supercomputers, speaking at a Tuesday evening panel at the SC2013 supercomputer conference,

The first place entrant alone, the Chinese Tianhe-2 system, brought in 33.86 petaflop/s (quadrillions of calculations per second).

"The list has become very top heavy in the last couple of years," Strohmaier said. "In the last five years, we have seen a drastic concentration of performance capabilities in large centers."

The organizers of the Top500, however, are unsure if the trend bodes ill for supercomputing in general. Could it signal a decline in supercomputing overall, or a concentration of supercomputing's investigative powers among fewer government agencies and large companies?

"We don't know what it actually means," said Horst Simon of Lawrence Berkeley National Laboratory, one of the organizers of the Top 500. "But it is important to exhibit the trend and have a discussion."

To characterize the depth of this "anomaly" as Strohmaier called this trend, he used a measure of statistical dispersion called a Gini Coefficient, which ranks the distribution of some resource. The Gini Coefficient, which is often used to measure the wealth distribution of nations, can range from 0, where the resource is spread evenly among all the holders, to 1, where one party holds all of the resources.

The list scored a Gini Coefficient of 0.6, which is quite high, Simon noted. By way of comparison, were the Top500 supercomputers a nation, it would have a greater inequality in computation than all but a few of countries have today in terms of wealth distribution. Simon jokingly called it "the rich-getting-richer phenomenon of supercomputing."

Drilling further down into the metrics, Strohmaier found no major differences between the buying habits of governments and industry. Both parties are buying fewer midsized systems and concentrating their efforts on building fewer, larger systems.

The trend could be problematic because fewer larger systems might reduce over time the number of administrators and engineers skilled in running high-performance computers. On the other hand, it might not be problematic in that most of the largest systems are shared across multiple users, such as all the researchers from a nation's universities.

Reprinted with permission from IDG.net. Story copyright 2014 International Data Group. All rights reserved.
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