A central component of modern computing is the idea that computation requires
determinism. Contrary to this belief, the primary contribution of this work shows that
useful computation can be accomplished in an error-prone fashion. Focusing on low-power
computing and the increasing push toward energy conservation, the work seeks to sacrifice
accuracy in exchange for energy savings.
Probabilistic computing forms the basis for this error-prone computation by diverging from the requirement of determinism and allowing for randomness within computing.
Implemented as probabilistic CMOS (PCMOS), the approach realizes enormous energy sav-
ings in applications that require probability at an algorithmic level. Extending probabilistic
computing to applications that are inherently deterministic, the biased voltage overscaling
(BIVOS) technique presented here constrains the randomness introduced through PCMOS.
Doing so, BIVOS is able to limit the magnitude of any resulting deviations and realizes
energy savings with minimal impact to application quality.
Implemented for a ripple-carry adder, array multiplier, and finite-impulse-response (FIR)
filter; a BIVOS solution substantially reduces energy consumption and does so with im-
proved error rates compared to an energy equivalent reduced-precision solution. When
applied to H.264 video decoding, a BIVOS solution is able to achieve a 33.9% reduction in
energy consumption while maintaining a peak-signal-to-noise ratio of 35.0dB (compared to
14.3dB for a comparable reduced-precision solution).
While the work presented here focuses on a specific technology, the technique realized
through BIVOS has far broader implications. It is the departure from the conventional
mindset that useful computation requires determinism that represents the primary innovation of this work. With applicability to emerging and yet to be discovered technologies,
BIVOS has the potential to contribute to computing in a variety of fashions.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/42812 |
| Date | 26 October 2011 |
| Creators | George, Jason |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
Page generated in 0.0019 seconds