This paper demonstrates that statistical error compensation reduces the energy consumption Emin at the minimum energy operating point (MEOP), which is known to occur in the subthreshold regime. In particular, the impact of algorithmic noise-tolerance (ANT) , in conjunction with frequency overscaling (FOS) and voltage overscaling, is studied in the context of an eight-tap finite impulse response (FIR) filter in a 45-nm CMOS process. At the nominal process corner and using low-Vt devices, we show that the ANT-based FIR filter achieves 20%-47% reduction in Emin and a 1.8×-2.25× increase in the frequency of operation over a conventional (error free) filter operating at its MEOP. This result is achieved via the ability of ANT to compensate for a precompensation error rate of 70%-85%. The use of high-Vt devices reduces Emin by 10%. This is due to the reduced effectiveness of FOS and increased sensitivity of delay to voltage variations. In the presence of process variations, the ANT-based FIR filter reduces Emin by 54% over a transistor up-sized design while meeting a fixed throughput constraint, and a parametric yield of 99.7%.
|Original language||English (US)|
|Number of pages||10|
|Journal||IEEE Transactions on Very Large Scale Integration (VLSI) Systems|
|State||Published - Jun 2014|
- Error resiliency
- minimum energy
- ultralow power (ULP)
- voltage overscaling.
ASJC Scopus subject areas
- Hardware and Architecture
- Electrical and Electronic Engineering