Design of accurate stochastic number generators with noisy emerging devices for stochastic computing

Meng Yang, John P. Hayes, Deliang Fan, Weikang Qian

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Stochastic computing (SC) is an unconventional computing paradigm that operates on stochastic bit streams. It has gained attention recently because of the very low area and power needs of its computing core. SC relies on stochastic number generators (SNGs) to map input binary numbers to stochastic bit streams. A conventional SNG comprises a random number source (RNS), typically an LFSR, and a comparator. It needs far more area and power than the SC core, offsetting the latter's main advantages. To mitigate this problem, SNGs employing emerging nanoscale devices such as memristors and spintronic devices have been proposed. However, these devices tend to have large errors in their output probabilities due to unpredictable variations in their fabrication processes and noise in their control signals. We present a novel method of exploiting such devices to design a highly accurate SNG. It is built around an RNS that generates uniformly distributed random numbers under ideal (nominal) conditions. It also has a novel error-cancelling probability conversion circuit (ECPCC) that guarantees very high accuracy in the output probability under realistic conditions when the RNS is subject to errors. An ECPCC can also be used to generate maximally correlated stochastic streams, a useful property for some applications.

Original languageEnglish (US)
Title of host publication2017 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages638-644
Number of pages7
ISBN (Electronic)9781538630938
DOIs
StatePublished - Dec 13 2017
Externally publishedYes
Event36th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2017 - Irvine, United States
Duration: Nov 13 2017Nov 16 2017

Publication series

NameIEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
Volume2017-November
ISSN (Print)1092-3152

Other

Other36th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2017
Country/TerritoryUnited States
CityIrvine
Period11/13/1711/16/17

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

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