Leveraging dual-mode magnetic crossbar for ultra-low energy in-memory data encryption

Zhezhi He, Shaahin Angizi, Farhana Parveen, Deliang Fan

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

8 Scopus citations

Abstract

The logic-in-memory architecture is highly promising for high-throughput data-driven applications. This paper presents a novel dual-mode magnetic crossbar architecture consisting of perpendicularly cross-coupled magnetic racetrack nanowires, which could morph between non-volatile multi-bit racetrack memory mode and in-memory data encryption mode. The proposed magnetic crossbar is able to automatically perform parallel in-memory bit-wise XOR computations of the data stored in the racetrack memories with the help of magnetic coupling physics without complex peripheral circuits, which could be leveraged to design energy efficient in-memory data encryption engine. We employ Advanced Encryption Standard (AES) algorithm to elucidate the efficiency of the proposed design. The device-to-architecture level simulation results show that the proposed architecture can achieve 70% and 17.5% lower energy consumption compared to CMOSASIC and recent domain wall (DW) AES implementations, respectively. In addition, the AES encryption speed increases by 29.7% compared to the DW-AES implementation.

Original languageEnglish (US)
Title of host publicationGLSVLSI 2017 - Proceedings of the Great Lakes Symposium on VLSI 2017
PublisherAssociation for Computing Machinery
Pages83-88
Number of pages6
ISBN (Electronic)9781450349727
DOIs
StatePublished - May 10 2017
Externally publishedYes
Event27th Great Lakes Symposium on VLSI, GLSVLSI 2017 - Banff, Canada
Duration: May 10 2017May 12 2017

Publication series

NameProceedings of the ACM Great Lakes Symposium on VLSI, GLSVLSI
VolumePart F127756

Other

Other27th Great Lakes Symposium on VLSI, GLSVLSI 2017
CountryCanada
CityBanff
Period5/10/175/12/17

Keywords

  • In-memory encryption
  • Magnetic coupling
  • Magnetic crossbar

ASJC Scopus subject areas

  • Engineering(all)

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