The Promise of Personal Supercomputers

What will it take to put thousands of microprocessors in cell phones and laptops?

Last week, Intel announced a research project that made geeks jump with glee: the first programmable "terascale" supercomputer on a chip. The company demonstrated a single chip with 80 cores, or processors, and showed that these cores could be programmed to crunch numbers at the rate of a trillion operations per second, a measure known as a teraflop. The chip is about the size of a large postage stamp, but it has the same calculation speed as a supercomputer that, in 1996, took up about 2,000 square feet and drew about 1,000 times more power.

Not so super: A supercomputer in 1996 (top left) capable of calculating one trillion operations per second took up about 2,000 square feet and consumed 500,000 watts. Recently, Intel unveiled an 80-core research chip (bottom right) that achieves the same calculation rate but is the size of a large postage stamp and uses about 65 watts. Credit: Intel

This research chip is one of Intel's first steps toward massively multicore technology, says Nitin Borkar, engineering manager and lab project head at Intel. The goal, he says, is to use this chip to test techniques that could make massively multicore technology faster, more energy efficient, and, most daunting, easy to program. These techniques will be "funneled into future products" that could appear, if all goes well, within five to ten years.

But nearly all engineers in the computing industry agree that making consumer computers with hundreds of cores won't be easy. In fact, many aren't even sure that it can be done. The most glaring challenge will be to find a way to completely overhaul software so that applications can take advantage of numerous cores. This includes teaching software developers how to write code for multicore machines--a task known as parallel programming--and developing new tools that allow them to code accurately and efficiently.

Researchers and visionaries are already thinking about how these supercomputer chips can best be used. Intel thinks that recognition, mining, and synthesis (RMS) applications will be key. Put together, these technologies could allow real-time language translation via cell phones, real-time video search by spoken phrase or image, and better recommendation systems for shopping, meal planning, and even health care.

To make these applications a reality, the computing industry will experience some growing pains, says David Patterson, professor of computer science at the University of California, Berkeley. (He and his colleagues have a website that hosts discussions and provides a white paper and videos on the topic.) "We're at the early stages of this gigantic change," Patterson says. He describes the direction in which the industry has decided to go--abandoning performance-constrained, single-core processors for multicore technology--as like a "Hail Mary pass" thrown in a football game. Chip makers are putting more and more cores on a chip, but the software engineers aren't sure if they can keep up. "It's an exciting time for researchers," Patterson says, "if we can figure out how to catch the pass."

Because clock frequency--the measure of processor speed--of single-core chips kept rising steadily for decades, programmers could dodge the challenge of programming in parallel, says John Shalf, computer scientist at Lawrence Berkeley Laboratory, in Berkeley, CA. Their programs would run faster if they just waited 18 months for the next generation of chip to arrive, he says. But by about 2002, it became evident that these single-core chips were consuming too much power and weren't going to be able to maintain the speed increases. So, the industry decided to change tack: instead of trying to eke out more speed from a single processor, chip makers simply added another processor. "Now that we can't crank up the clock frequency, we have to face parallelism head-on," Shalf says, "and the best way to characterize the industry's response is widespread panic."