SAN JOSE, Calif. — Nervana Systems is on the cusp of rolling out a microprocessor designed for big data analytics. The startup’s work is one of a handful of efforts aiming to accelerate deep neural networks in hardware for a variety of recognition tasks.
Engineers are racing to develop and accelerate algorithms that find patterns in today’s flood of digital data. Nervana believes it has an edge with a novel processor it hopes to have up and running in its own cloud service late next year.
Nervana competes with giants such as Intel and Nvidia whose processors run most of today’s algorithms for training neural nets. Web giants are also in the hunt, snapping up the best researchers in machine learning. Among the leaders, Google is said to be working on an accelerator chip of its own.
“This revolution in deep neural networks is akin to the invention of microprocessor, it is the solution to our big data problem which is the fundamental industry problem of the next 10-20 years,” said Naveen Rao, chief executive of Nervana.
Rao designed processors for ten years at Sun Microsystems and a string of startups before returning to academia to get a PhD in neuroscience. He did a brief stint in finance working on algorithmic trading, then researched chips that could mimic the brain at Qualcomm before co-founding Nervana.
The Nervana chip “is a culmination of all the things I’ve studied…we want to build inference machines to find structure in large data sets -- that’s the biggest problem of our time,” said Rao.
“We own this business, and we are going to do everything we can to keep it,” Bill Dally, chief scientist of Nvidia told me at a reception last week, a day after he returned from a neural networking conference in Montreal.
It’s early days for inventing new chip architectures for deep learning, said Dally, a veteran microprocessor researcher. He pointed to the recent ImageNet competition as an example of how fast the algorithms are still changing.
More than 50 academic and commercial research teams from around the world competed in the event including groups from Google, NEC, Mitsubishi, Tencent and Qualcomm – and even a research team from China’s Ministry of Public Security. A group from Microsoft Research won the competition showing once again the potential for machines to recognize images faster and more accurately than humans, simply using neural nets running on racks of Intel x86 processors.
Next page: A glimpse of Nervana’s new architecture