Parallel programming of resistive cross-point array for synaptic plasticity

Zihan Xu, Abinash Mohanty, Pai Yu Chen, Deepak Kadetotad, Binbin Lin, Jieping Ye, Sarma Vrudhula, Shimeng Yu, Jae-sun Seo, Yu Cao

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

12 Scopus citations

Abstract

This paper proposes a parallel programming scheme for the cross-point array with resistive random access memory (RRAM). Synaptic plasticity in unsupervised learning is realized by tuning the conductance of each RRAM cell. Inspired by the spike-timing-dependent-plasticity (STDP), the programming strength is encoded into the spike firing rate (i.e., pulse frequency) and the overlap time (i.e., duty cycle) of the pre-synaptic node and post-synaptic node, and simultaneously applied to all RRAM cells in the cross-point array. Such an approach achieves parallel programming of the entire RRAM array, only requiring local information from pre-synaptic and post-synaptic nodes to each RRAM cell. As demonstrated by digital peripheral circuits implemented in 65nm CMOS, the programming time of a 40kb RRAM array is 84 ns, indicating 900X speedup as compared to state-ofthe-art software approach of sparse coding in image feature extraction.

Original languageEnglish (US)
Title of host publicationProcedia Computer Science
PublisherElsevier
Pages126-133
Number of pages8
Volume41
DOIs
StatePublished - 2014
Event5th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2014 - Cambridge, United States
Duration: Nov 7 2014Nov 9 2014

Other

Other5th Annual International Conference on Biologically Inspired Cognitive Architectures, BICA 2014
Country/TerritoryUnited States
CityCambridge
Period11/7/1411/9/14

Keywords

  • Dictionary learning
  • Parallel programming
  • Resistive cross-point array
  • Synaptic plasticity

ASJC Scopus subject areas

  • General Computer Science

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