An international team of computing experts from the United States, Switzerland,
and Singapore
has created a breakthrough technique for doubling the efficiency of computer
chips by trimming away the portions that are rarely used.
“I believe this is the first time someone has taken an integrated
circuit and said, ‘Let’s get rid of the part that we don’t need,'” said
principal investigator Krishna Palem, the Ken and Audrey Kennedy Professor of
Computing at Rice Univ. in Houston, who holds a joint appointment at Nanyang
Technological Univ. (NTU) in Singapore. “What we’ve shown is that we can
boost performance and cut energy use simultaneously if we prune the unnecessary
portions of the digital application-specific integrated circuits that are
typically used in hearing aids, cameras, and other multimedia devices.”
Pruning is the latest example of inexact hardware, the key approach that the
Rice-NTU Institute for Sustainable and Applied Infodynamics (ISAID) is exploring
with Switzerland’s
Center for Electronics and Microtechnology (CSEM) to produce the next generation
of energy-stingy microchips.
The probabilistic concept is simple: Slash power demands on microprocessors
by allowing them to make mistakes. By managing theprobability of errors and by
limiting which calculations produce errors, the designers have found they can
simultaneously cut energy demands and boost performance.
At DATE11, Rice graduate student Avinash Lingamneni will describe
“probabilistic pruning,” the novel technique the team created for
trimming away the least-used portions of integrated circuits. Lingamneni used
the method to create prototype chips at CSEM. The test prototypes contain both
traditional circuits and pruned circuits that were produced side by side on the
same silicon chip.
“Our initial tests indicate that the pruned circuits will be at least
two times faster, consume about half the energy and take up about half the
space of the traditional circuits,” Lingamneni said. He said he hopes that
the system performs even better in the final tests, which are still under way.
Christian Enz, who leads the CSEM arm of the collaboration and is a co-author
of the DATE study, said, “The cost for these gains is an 8% error
magnitude; and, to put that into context, we know that many perceptive types of
tasks found in vision or hearing applications can easily tolerate error
magnitudes of up to 10%.”
Palem said the next hurdle for pruning will be to use the technique to
create a complete prototype chip for a specific application. Lingamneni said he
hopes to start designing just such a chip for a hearing aid this summer.
“Based on what we already know, we believe probabilistic computing can
produce application-specific integrated circuits for hearing aids that can run
four to five times longer on a set of batteries than current hearing
aids,” Palem said. “The collaboration between ISAID and CSEM was key
to achieving these results.”
