Deterministic approaches to bitstream computing

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Stochastic logic allows complex arithmetic to be performed with very simple logic, but it suffers from high latency and poor precision. Furthermore, the results are always somewhat inaccurate due to random fluctuations. The random or pseudorandom sources required to generate the representation are costly, consuming a majority of the circuit area (and diminishing the overall gains in area). This chapter reexamines the foundations of stochastic computing and comes to some surprising conclusions. It demonstrates that one can compute deterministically using the same structures that are used to compute stochastically. In doing so, the latency is reduced by an exponential factor; also, the area is reduced significantly (and this correlates with a reduction in power); and finally, one obtains completely accurate results, with no errors or uncertainty. This chapter also explores an alternate view of this deterministic approach. Instead of viewing signals as digital bit streams, we can view them as periodic signals, with the value encoded as the fraction of the time that the signal is in the high (on) state compared to the low (off) state in each cycle. Thus we have a time-based encoding. All of the constructs developed for stochastic computing can be used to compute on these periodic signals, so the designs are very efficient in terms of area and power. Given how precisely values can be encoded in the time, the method could produce designs that have much lower latency that conventional ones.

Original languageEnglish (US)
Title of host publicationStochastic Computing
Subtitle of host publicationTechniques and Applications
PublisherSpringer International Publishing
Pages121-136
Number of pages16
ISBN (Electronic)9783030037307
ISBN (Print)9783030037291
DOIs
StatePublished - Feb 18 2019

Keywords

  • Convolution
  • Deterministic computation
  • Pulse-width modulation
  • Time-based computing
  • Unary

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