Highly energy and performance efficient embedded computing through approximately correct arithmetic

Abstract

We develop a theoretical foundation to characterize a novel methodology for low energy and high performance dsp for embedded computing. Computing elements are operated at a frequency higher than that permitted by a conventionally correct circuit design, enabling a trade-off between error that is deliberately introduced, and the energy consumed. Similar techniques considered previously were relevant to deeply scaled future technology generations. Our work extends this idea to be applicable to current-day designs through: (i) a mathematically rigorous foundation characterizing a tradeoff between energy consumed and the quality of solution, and (ii) a means of achieving this trade off through very aggressive voltage scaling beyond that of a conventionally designed circuit. Through our "cmos inspired" mathematical model, we show that our approach is better (by an exponential factor) than the conventional uniform voltage scaling approach for comparable computational speed or performance. We further establish through experimental study that a similar improvement by a factor of 3.4x to the snr over conventional voltage-scaled approaches can be achieved in the context of the ubiquitous discrete Fourier transform.