Next-Generation Supercomputers – IEEE Spectrum

Amora R Jelo

Supercomputers are the crowning achievement of the digital age. Yes, it’s true that yesterday’s supercomputer is today’s game console, as far as performance goes. But there is no doubt that during the past half-century these machines have driven some fascinating if esoteric pursuits: breaking codes, predicting the weather, modeling automobile crashes, simulating nuclear explosions, and designing new drugs—to name just a few. And in recent years, supercomputers have shaped our daily lives more directly. We now rely on them every time we do a Google search or try to find an old high school chum on Facebook, for example. And you can scarcely watch a big-budget movie without seeing supercomputer-generated special effects.

So with these machines more ingrained than ever into our institutions and even our social fabric, it’s an excellent time to wonder about the future. Will the next decade see the same kind of spectacular progress as the last two did?

Alas, no.

Modern supercomputers are based on groups of tightly interconnected microprocessors. For decades, successive generations of those microprocessors have gotten ever faster as their individual transistors got smaller—the familiar Moore’s Law paradigm. About five years ago, however, the top speed for most microprocessors peaked when their clocks hit about 3 gigahertz. The problem is not that the individual transistors themselves can’t be pushed to run faster; they can. But doing so for the many millions of them found on a typical microprocessor would require that chip to dissipate impractical amounts of heat. Computer engineers call this the power wall. Given that obstacle, it’s clear that all kinds of computers, including supercomputers, are not going to advance at nearly the rates they have in the past.

So just what can we expect? That’s a question with no easy answer. Even so, in 2007 the U.S. Defense Advanced Research Projects Agency (DARPA) decided to ask an even harder one: What sort of technologies would engineers need by 2015 to build a supercomputer capable of executing a quintillion (1018) mathematical operations per second? (The technical term is floating-point operations per second, or flops. A quintillion of them per second is an exaflops.)

DARPA didn’t just casually pose the question. The agency asked me to form a study group to find out whether exaflops-scale computing would be feasible within this interval—half the time it took to make the last thousandfold advance, from teraflops to petaflops—and to determine in detail what the key challenges would likely be. So I assembled a panel of world-renowned experts who met about a dozen times over the following year. Many of us had worked on today’s petaflops supercomputers, so we had a pretty good idea how hard it was going to be to build something with 1000 times as much computing clout.

We consulted with scores of other engineers on particular new technologies, we made dozens of presentations to our DARPA sponsors, and in the end we hammered out a 278-page report [PDF], which had lots of surprises, even for us. The bottom line, though, was rather glum. The practical exaflops-class supercomputer DARPA was hoping for just wasn’t going to be attainable by 2015. In fact, it might not be possible anytime in the foreseeable future. Think of it this way: The party isn’t exactly over, but the police have arrived, and the music has been turned way down.

This was a sobering conclusion for anyone working at the leading edge of high-performance computing. But it was worrisome for many others, too, because the same issues come up whether you’re aiming to construct an exaflops-class supercomputer that occupies a large building or a petaflops-class one that fits in a couple of refrigerator-size racks—something lots of engineers and scientists would dearly like to have at their disposal. Our panel’s conclusion was that to put together such “exascale” computers—ones with DARPA’s requested density of computational might, be they building-size supercomputers or blazingly fast rack-size units—would require engineers to rethink entirely how they construct number crunchers in the future.

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