Statistical Analysis of Temperature Variability on the Write Efficiency of Spin-Orbit Torque MRAM using Polynomial Chaos Metamodels

Sonal Shreya, Surila Guglani, Brajesh Kumar Kaushik, Sourajeet Roy

Research output: Contribution to conferenceConference abstract for conferenceResearchpeer-review

Abstract

Analyzing the effects of temperature variability on the operation of spintronic devices is of great importance for memory applications. This is because temperature variations often induce variations in the switching metrics such as the critical current density and write energy. Traditionally, predictive analysis of the effect of temperature variations was done using a Monte Carlo framework. In this paper, a far more numerically efficient surrogate modeling approach based on the Polynomial Chaos (PC) technique is presented for thermal analysis of spin-orbit torque (SOT) based magnetic random access memory (MRAM). Importantly, for a wide range of temperature variation from-50°C to 120°C, it has been demonstrated that the PC technique is able to predict the statistical variations of current density (J SOT) and write energy (E write) with more than 99.9% accuracy while offering between one to three orders of magnitude in speedup over the conventional Monte Carlo framework.

Original languageEnglish
Publication date9 Jul 2020
Number of pages6
DOIs
Publication statusPublished - 9 Jul 2020
Event21st International Symposium on Quality Electronic Design - Santa Clara, California, United States
Duration: 25 Mar 202026 Mar 2020

Conference

Conference21st International Symposium on Quality Electronic Design
LocationSanta Clara
Country/TerritoryUnited States
CityCalifornia
Period25/03/202026/03/2020

Keywords

  • MRAM
  • Polynomial Chaos
  • Spin-orbit torque
  • Statistical Analysis
  • Temperature Effects

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