Compact oscillation neuron exploiting metal-insulator-transition for neuromorphic computing

Pai Yu Chen, Jae-sun Seo, Yu Cao, Shimeng Yu

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

13 Scopus citations

Abstract

The phenomenon of metal-insulator-transition (MIT) in strongly correlated oxides, such as NbO2, have shown the oscillation behavior in recent experiments. In this work, the MIT based two-terminal device is proposed as a compact oscillation neuron for the parallel read operation from the resistive synaptic array. The weighted sum is represented by the frequency of the oscillation neuron. Compared to the complex CMOS integrate-and-fire neuron with tens of transistors, the oscillation neuron achieves significant area reduction, thereby alleviating the column pitch matching problem of the peripheral circuitry in resistive memories. Firstly, the impact of MIT device characteristics on the weighted sum accuracy is investigated when the oscillation neuron is connected to a single resistive synaptic device. Secondly, the array-level performance is explored when the oscillation neurons are connected to the resistive synaptic array. To address the interference of oscillation between columns in simple cross-point arrays, a 2-transistor-1-resistor (2T1R) array architecture is proposed at negligible increase in array area. Finally, the circuit-level benchmark of the proposed oscillation neuron with the CMOS neuron is performed. At single neuron node level, oscillation neuron shows >12.5X reduction of area. At 128×128 array level, oscillation neuron shows a reduction of ∼4% total area, >30% latency, ∼5X energy and ∼40X leakage power, demonstrating its advantage of being integrated into the resistive synaptic array for neuro-inspired computing.

Original languageEnglish (US)
Title of host publication2016 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781450344661
DOIs
StatePublished - Nov 7 2016
Event35th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2016 - Austin, United States
Duration: Nov 7 2016Nov 10 2016

Publication series

NameIEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
Volume07-10-November-2016
ISSN (Print)1092-3152

Other

Other35th IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2016
CountryUnited States
CityAustin
Period11/7/1611/10/16

Keywords

  • metal-insulator-transition
  • neuromorphic computing
  • neuron
  • oscillation
  • resistive memory
  • synaptic array

ASJC Scopus subject areas

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

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