A team of researchers from Rice University and Singapore’s Nanyang Technological University (NTU) are developing a new PCMOS silicon technology that they say uses 30 times less electricity while running seven times faster than today’s technology. The announcement was made at this week’s International Solid-State Circuits Conference (ISSCC) in San Francisco.
Although PCMOS runs on standard silicon, it breaks with computing’s past by abandoning the set of mathematical rules — called Boolean logic — that have thus far been used in all digital computers. PCMOS instead uses probabilistic logic, a new form of logic developed by Rice University Professor Krishna Palem and his doctoral student, Lakshmi Chakrapani. Palem’s PCMOS research was funded by the Defense Advanced Research Projects Agency and Intel.
Silicon transistors become increasingly ‘noisy’ as they get smaller, but engineers have historically dealt with this by boosting the operating voltage to overpower the noise and ensure accurate calculations. Chips with more and smaller transistors are consequently more power-hungry.
“PCMOS is fundamentally different,” Palem said. “We lower the voltage dramatically and deal with the resulting computational errors by embracing the errors and uncertainties through probabilistic logic.”
PCMOS was jointly validated by Rice and Nanyang Technological University (NTU) in Singapore via a joint institute that Palem founded in 2007, the Institute for Sustainable Nanoelectronics (ISNE). Directed by Palem, ISNE is based at NTU, where the first prototype PCMOS chips were manufactured last year in collaboration with Professor Yeo Kiat Seng and his team. The first prototype is an ASIC designed for encryption. The Rice-NTU team plans to follow up with proof-of-concept tests on microchips for cell phones, graphics cards and medical implants.
Palem said PCMOS is ideally suited for encryption, a process that relies on generating random numbers. It’s equally well-suited for graphics, but for different reasons. In a streaming video application on a cell phone, for example, it is unnecessary to conduct precise calculations. The small screen, combined with the human brain’s ability to process less-than-perfect pictures, results in a case where the picture looks just as good with a calculation that’s only approximately correct. For consumers, it could mean the difference between charging a cell phone every few weeks instead of every few days.
http://www.rice.edu/nationalmedia/news2009-02-08-pcmos.shtml
