Polynomial arithmetic using sequential stochastic logic

Naman Saraf, Kia Bazargan

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

6 Scopus citations

Abstract

We present the design of stochastic computing systems based on sequential logic to implement arbitrary polynomial functions. Stochastic computing is an emerging alternative computing paradigm that performs arithmetic operations on real-valued data represented as random bitstreams using digital logic gates. Stochastic computing systems are capable of realizing complex mathematical operations using a small number of hardware resources by expressing the computation in terms of probabilities. Moreover, the stochastic representation of data using random bitstreams is extremely robust against bit errors. We present a systematic approach to implement arbitrary polynomial functions in stochastic computing using sequential logic, and compare our approach against prior conventional and stochastic implementations.

Original languageEnglish (US)
Title of host publicationGLSVLSI 2016 - Proceedings of the 2016 ACM Great Lakes Symposium on VLSI
PublisherAssociation for Computing Machinery
Pages245-250
Number of pages6
ISBN (Electronic)9781450342742
DOIs
StatePublished - May 18 2016
Event26th ACM Great Lakes Symposium on VLSI, GLSVLSI 2016 - Boston, United States
Duration: May 18 2016May 20 2016

Publication series

NameProceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI
Volume18-20-May-2016

Other

Other26th ACM Great Lakes Symposium on VLSI, GLSVLSI 2016
CountryUnited States
CityBoston
Period5/18/165/20/16

Bibliographical note

Funding Information:
This material is based on work supported by the National Science Foundation under grant CCF-1408123.

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