Researchers
at Yale University and New York University have developed a
new supercomputer that is capable of navigating a car more
quickly and efficiently through the use of a human-based visual
system.
The
supercomputer is called NeuFlow, and it was created by Eugenio
Culurciello of Yale's School of Engineering & Applied Science
along with Yann LeCun from New York University. Culurciello developed
the human-inspired system while LeCun supplied the complex vision
algorithms, which runs the neural networks for synthetic
vision applications. NeuFlow's actions are based on the
human visual system, acting as quickly and efficiently as a human
when obeying traffic laws, distinguishing different objects from one
another such as trees and buildings, and reacting to other drivers on
the road.
Culurciello
and LeCun are looking to use this supercomputer as a way for cars to
drive themselves. To do this, NeuFlow runs more than 100 billion
operations per second only using a few watts of power, which is less
than what's required to power a cell phone. NeuFlow exists on a
single chip, making it no larger than a wallet, but it is more
efficient and powerful than full-scale computers. Also, this system
"processes tens of megapixel images in real time."
"One
of our first prototypes of this system is already capable of
outperforming graphic
processors on vision tasks," said Culurciello.
The
development of fully-autonomous vehicle's will be a significant
advancement in the world of human convenience and safety, and that's
why NeuFlow isn't the only computer-driven system out there right
now.
In
2008, DailyTech went
for a spin in the Chevrolet Tahoe DARPA Challenge vehicle,
which is a fully-autonomous vehicle that won the DARPA 2007 Urban
Challenge and is equipped with GPS, radar, video, laser and LIDAR
sensors and inputs to recognize objects on the road. Its key sensor,
velodyne, has 64 sensors in a wide array and is able to collect one
million bits of data per second at 10 Hz. It's logic consists of over
350,000 lines of code, and is able to obtain a 3-D view of the
surrounding terrain just like NeuFlow.
But
unlike the Chevrolet
Tahoe DARPA Challenge vehicle, NeuFlow is not quite ready
for vehicle use yet. Culurciello and LeCun are looking to use NeuFlow
in other applications as well, such as a tool for 360-degree
synthetic vision for soldiers in combat and to help improve robot
navigation in dangerous locations.
NeuFlow
was presented by Culurciello at the High
Performance Embedded Computing (HPEC) workshop in Boston,
Mass. on September 15.
