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Related Experiment Video

Updated: Oct 2, 2025

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High On/Off Ratio Spintronic Multi-Level Memory Unit for Deep Neural Network.

Kun Zhang1,2, Xiaotao Jia1,3, Kaihua Cao1,2

  • 1Fert Beijing Research Institute, MIIT Key Laboratory of Spintronics, School of Integrated Circuit Science and Engineering, Beihang University, Beijing, 100191, P. R. China.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)
|March 1, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel spintronic multi-level memory unit that overcomes limitations in non-volatile memory devices. The proposed design achieves a high on/off ratio, enabling advanced computing applications like deep neural network accelerators.

Keywords:
deep neural networkdiodehigh on/off ratiomagnetic tunnel junctionmulti-level memory unit

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Area of Science:

  • Spintronics
  • Materials Science
  • Computer Engineering

Background:

  • Spintronic devices offer promise for non-volatile memory and computing.
  • Current limitations include lack of intrinsic multi-level operation and low on/off ratio, hindering applications like deep neural network (DNN) accelerators.

Purpose of the Study:

  • To propose a spintronic multi-level memory unit with a high on/off ratio.
  • To address the limitations hindering advanced spintronic computing applications.

Main Methods:

  • Integration of series-connected magnetic tunnel junctions (MTJs) with perpendicular magnetic anisotropy (PMA) and a Schottky diode in parallel.
  • Utilizing the rectification effect of PMA MTJs with a specific AC/DC current proportion.
  • Employing spin transfer torque for reconfiguring multiple resistance states.

Main Results:

  • Achieved an on/off ratio exceeding 100, significantly higher than intrinsic values.
  • Demonstrated stable multi-level resistance states.
  • Evaluated a computing-in-memory architecture based DNN accelerator for image classification.

Conclusions:

  • The proposed spintronic memory unit meets rigorous DNN requirements.
  • This advancement promotes the development of high-accuracy and robust artificial intelligence applications.