A Survey of Computation-Driven Data Encoding

Weikang Qian, Runsheng Wang, Yuan Wang, Marc Riedel, Ru Huang

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

Abstract

Although the metal-oxide-semiconductor field-effect transistor (MOSFET) has been the dominant device for modern very-large scale integration (VLSI) circuits for more than six decades, with the dawning of a post-Moore era, researchers are trying to find replacements. A foundation of modern digital computing is the encoding of digital values through a binary radix representation. However, as we enter into the post-Moore era, the challenges of increasing power density, signal noise, and device unreliability raise the question of whether this basic way of encoding data is still the best choice, particularly with novel electronic devices. Prior work has shown that binary radix encoding has some disadvantages. We argue that it is crucial to rethink the necessity of using this representation in the post-Moore era. In this paper, we review some recent development on computation-driven data encoding. We begin with stochastic encoding, a representation proposed a long time ago, discussing both its advantages and disadvantages. Then, we review several recent breakthroughs with variations of stochastic encoding that mitigate many of its disadvantages. Finally, we conclude the paper by extrapolating future directions for effective computation-driven data encoding.

Original languageEnglish (US)
Title of host publication2019 IEEE International Workshop on Signal Processing Systems, SiPS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7-12
Number of pages6
ISBN (Electronic)9781728119274
DOIs
StatePublished - Oct 2019
Event33rd IEEE International Workshop on Signal Processing Systems, SiPS 2019 - Nanjing, China
Duration: Oct 20 2019Oct 23 2019

Publication series

NameIEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation
Volume2019-October
ISSN (Print)1520-6130

Conference

Conference33rd IEEE International Workshop on Signal Processing Systems, SiPS 2019
CountryChina
CityNanjing
Period10/20/1910/23/19

Bibliographical note

Funding Information:
This work is supported by National Natural Science Foundation of China (NSFC) under grant no. 61472243 and 61204042.

Keywords

  • deterministic unary encoding
  • low discrepancy stochastic encoding
  • stochastic computing
  • stochastic encoding

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