A Highly Integrated Crosspoint Array Using Self-rectifying FTJ for Dual-mode Operations: CAM and PUF

Sehee Lim, Youngin Goh, Young Kyu Lee, Dong Han Ko, Junghyeon Hwang, Minki Kim, Yeongseok Jeong, Hunbeom Shin, Sanghun Jeon, Seong Ook Jung

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

8 Citations (Scopus)

Abstract

This study proposes a self-rectifying ferroelectric tunnel junction (SR-FTJ) crosspoint array which affords dual-mode operation as content-addressable memory (CAM) and physically unclonable function (PUF). The PUF mode operation of the proposed SR-FTJ crosspoint array does not require any temporary transfer of stored CAM data to buffer, which prevents additional area overhead or potential data security threats. Experimental measurements verify the feasibility of the dual-mode operation. Further simulations using the SR-FTJ model reflecting measured characteristics show that the proposed SR-FTJ crosspoint array reduces area by at least 88.1 % up to 97.4 % compared to the previous structures that implement individual CAM and PUF. In addition, the proposed SR-FTJ crosspoint array achieves the lowest search energy (2.05 fJ/search/bit) and the highest randomness (Hamming weight of 0.5000) among the structures.

Original languageEnglish
Title of host publicationESSCIRC 2022 - IEEE 48th European Solid State Circuits Conference, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages113-116
Number of pages4
ISBN (Electronic)9781665484947
DOIs
Publication statusPublished - 2022
Event48th IEEE European Solid State Circuits Conference, ESSCIRC 2022 - Milan, Italy
Duration: 2022 Sept 192022 Sept 22

Publication series

NameESSCIRC 2022 - IEEE 48th European Solid State Circuits Conference, Proceedings

Conference

Conference48th IEEE European Solid State Circuits Conference, ESSCIRC 2022
Country/TerritoryItaly
CityMilan
Period22/9/1922/9/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Instrumentation
  • Artificial Intelligence

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