Design and evaluation of a spintronic in-memory processing platform for nonvolatile data encryption

Shaahin Angizi, Zhezhi He, Nader Bagherzadeh, Deliang Fan

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

In this paper, we propose an energy-efficient reconfigurable platform for in-memory processing based on novel four-terminal spin Hall effect-driven domain wall motion devices that could be employed as both nonvolatile memory cell and in-memory logic unit. The proposed designs lead to unity of memory and logic. The device to system level simulation results show that, with 28% area increase in memory structure, the proposed in-memory processing platform achieves a write energy 15.6 fJ/bit with 79% reduction compared to that of SOT-MRAM counterpart while keeping the identical 1 ns writing speed. In addition, the proposed in-memory logic scheme improves the operating energy by 61.3%, as compared with the recent nonvolatile in-memory logic designs. An extensive reliability analysis is also performed over the proposed circuits. We employ advanced encryption standard (AES) algorithm as a case study to elucidate the efficiency of the proposed platform at application level. Simulation results exhibit that the proposed platform can show up to 75.7% and 30.4% lower energy consumption compared to CMOS-ASIC and recent pipelined domain wall (DW) AES implementations, respectively. In addition, the AES energy-delay product can show 15.1% and 6.1% improvements compared to the DW-AES and CMOS-ASIC implementations, respectively.

Original languageEnglish (US)
Article number8113549
Pages (from-to)1788-1801
Number of pages14
JournalIEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Volume37
Issue number9
DOIs
StatePublished - Sep 2018
Externally publishedYes

Keywords

  • Advanced encryption standard (AES)
  • domain wall motion (DWM)
  • in-memory processing platform
  • spin Hall effect (SHE)

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering

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