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Tech Times | MIT Technology Review: The chip that's bad at math

Published:Monday | September 5, 2016 | 9:00 AM

DARPA funded the development of a new computer chip that's hardwired to get simple problems wrong but can help computers understand the world.

Your math teacher lied to you. Sometimes getting your sums wrong is a good thing.

So says Joseph Bates, cofounder and CEO of Singular Computing, a company whose computer chips are hardwired to be incapable of performing mathematical calculations correctly. Ask it to add 1 and 1 and you will get answers like 2.01 or 1.98.

The Pentagon research agency DARPA funded the creation of Singular's chip because that fuzziness can be an asset when it comes to some of the hardest problems for computers, such as making sense of video or other messy real-world data. A chip that can't guarantee that every calculation is perfect can still get good results on many problems but needs fewer circuits and burns less energy, Bates says. He has worked with Sandia National Lab, Carnegie Mellon University, the Office of Naval Research, and MIT on tests that used simulations to show how the chip's inexact operations might make certain tricky computing tasks more efficient. Problems with data reflecting built-in noise from the real world, or where some approximation is needed, are the best fits. Bates reports promising results for applications such as high-resolution radar imaging, extracting 3-D information from stereo photos, and deep learning, a technique that has delivered a recent burst of progress in artificial intelligence.




In a simulated test using software that tracks objects such as cars in video, Singular's approach was capable of processing frames almost 100 times faster than a conventional processor restricted to doing correct mathwhile using less than 2 per cent as much power.

Bates is not the first to pursue the idea of using hand-wavy hardware to crunch data more efficiently, a notion known as approximate computing. But DARPA's investment in his chip could give the fuzzy-math dream its biggest tryout yet. Singular is building a batch of error-prone computers that each combine 16 of its chips with a single conventional processor. DARPA will get five such machines sometime this summer and plans to provide access to them for government and academic researchers. The hope is that they can prove the technology's potential and lure interest from the chip industry.

DARPA funded Singular's chip as part of a program called Upside, which is aimed at inventing new, more efficient ways to process video footage. Military drones can collect vast quantities of video, but it can't always be downloaded during flight, and the computer power needed to process it in the air would be too bulky.

Software will have to be designed differently for imprecise hardware to take off. But Deb Roy, a professor at the MIT Media Lab and Twitter's chief media scientist, says that approximate computing may find a readier audience than ever. "There's a natural resonance if you are processing any kind of data that is noisy by nature," he says. That's become more and more common as programmers look to extract information from photos and video or have machines make sense of the world, he adds.