The U.S. Defense Advanced Research Projects Agency has unveiled plans to regain the crown as the fastest supercomputer in the world, barely two weeks after China officially wrestled it away with its 2.5 petaflop Tianhe-1A. The goal is ambitious to say the least; DARPA wants to bypass the petaflop level and hopes to build an exascale computer. As its name suggests, an exascale computer computes in exaflops, which is one million trillion calculations per second. That's a thousand times faster than the Tianhe-1A for you.

The new supercomputer won't be ready until 2018 though, with the lengthy wait attributed to the need to reinvent entire facets of computing. The problem here has to do with fundamental computing limitations; an exaflop-capable supercomputer will need to shift a prodigious amount of data, but the efficiency required to hit these speeds simply does not exist yet.

Allan Snavely, associate director of the Supercomputer Center observed how moving a single exabyte of data using today's "crude and simplistic memory cache and prefetch policies" will require tremendous energy costs. Snavely told Wired.co.uk that doing so would need what he called "a nuclear plant's worth of instantaneous power."

What is certain, however, is that the initiative to build an exascale supercomputer will require more high-quality science and technology Ph.D. students, who are unfortunately in short supply at the moment. So said Peter Beckman when he spoke at length with Computerworld on this topic. Beckman is a top computer scientist at the U.S. Department of Energy's Argonne National Laboratory.

Coincidentally, I wrote a commentary on the comparatively lower ranking of the U.S. in math and science education and its relationship with competing in the supercomputing arena earlier this month. What is your take on this? Will this goal be achievable?

For more on this story:
- check out this article at Wired
- check out this article at Computerworld

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