Investigation of statistical retention of filamentary analog RRAM for neuromophic computing

Meiran Zhao, Huaqiang Wu, Bin Gao, Qingtian Zhang, Wei Wu, Shan Wang, Yue Xi, Dong Wu, Ning Deng, Shimeng Yu, Hong Yu Chen, He Qian

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

21 Scopus citations

Abstract

The retention requirements of analog RRAM for neuromorphic computing applications are quite different from conventional RRAM for memory applications. Meanwhile, filamentary analog RRAM exhibits different retention behavior in comparison to strong-filament RRAM. For the first time, the statistical behaviors of read current noise and retention in a 1Kb filamentary analog RRAM array are investigated in this work. The conductance distribution of different levels is found to change with time, and the physical mechanism of the retention degradation is elucidated. From the experimental data, a compact model is developed in order to predict the statistical conductance evolution, which can effectively evaluate the impact of read noise and retention degradation in neuromorphic computing systems.

Original languageEnglish (US)
Title of host publication2017 IEEE International Electron Devices Meeting, IEDM 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages39.4.1-39.4.4
ISBN (Electronic)9781538635599
DOIs
StatePublished - Jan 23 2018
Event63rd IEEE International Electron Devices Meeting, IEDM 2017 - San Francisco, United States
Duration: Dec 2 2017Dec 6 2017

Publication series

NameTechnical Digest - International Electron Devices Meeting, IEDM
ISSN (Print)0163-1918

Other

Other63rd IEEE International Electron Devices Meeting, IEDM 2017
CountryUnited States
CitySan Francisco
Period12/2/1712/6/17

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Electrical and Electronic Engineering
  • Materials Chemistry

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