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Spin Orbit Torque Domain Wall-Magnetic Tunnel Junction Devices and Circuits for In-Memory and Neuromorphic Computing

ORAL

Abstract

Domain wall-magnetic tunnel junction (DW-MTJ) in-memory computing devices can address major data processing bottlenecks with traditional computing, especially for accomplishing data-intensive and real-time tasks. We propose three-terminal DW-MTJ in-memory computing devices that resolve challenges with traditional DW-MTJs by using perpendicular magnetic anisotropy (PMA) with more robustness to thermal fluctuations than in-plane magnetic anisotropy, spin-orbit torque switching that requires less switching current than spin transfer torque, and an optimized lithography process to produce average device tunnel magnetoresistance TMR = 164%, close to the expected highest TMR seen in PMA MTJs, and resistance-area product RA = 31 Ω.μm2 , close to the RA of the unpatterned film. A two-device circuit shows bit propagation between devices. Switching voltage cycle-to-cycle variation is measured as a tunable probabilistic function and is shown to be curtailed to 7% by controlling the DW initial position, which we show corresponds to 96% accuracy in a DW-MTJ full adder simulation. These results make major strides in using DW-MTJs for in-memory and neuromorphic computing applications.

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Presenters

  • Mahshid Alamdar

    Electrical and Computer Engineering Dept., University of Texas at Austin, Austin TX USA

Authors

  • Mahshid Alamdar

    Electrical and Computer Engineering Dept., University of Texas at Austin, Austin TX USA

  • Thomas Leonard

    Electrical and Computer Engineering Dept., University of Texas at Austin, Austin TX USA

  • Can Cui

    Electrical and Computer Engineering, University of Texas at Austin, ECE, The University of Texas at Austin, Electrical and Computer Engineering Dept., University of Texas at Austin, Austin TX USA

  • Bishweshwor P. Rimal

    Electrical and Computer Engineering Dept., University of Texas at Austin, Austin TX USA

  • Lin Xue

    Applied Materials, Santa Clara CA USA

  • Otitoaleke G. Akinola

    Electrical and Computer Engineering, University of Texas at Austin, Electrical and Computer Engineering Dept., University of Texas at Austin, Austin TX USA

  • Tianyao Patrick Xiao

    Sandia National Laboratories, Albuquerque NM USA

  • Joseph S. Friedman

    Electrical and Computer Engineering, University of Texas at Dallas, University of Texas at Dallas, Electrical and Computer Engineering Dept., University of Texas at Dallas, Richardson TX USA, Electrical & Computer Engineering, University of Texas at Dallas, Department of Electrical and Computer Engineering, University of Texas at Dallas

  • Christopher H. Bennet

    Sandia National Laboratories, Sandia National Laboratories, Albuquerque NM USA

  • Matthew J. Marinella

    Sandia National Laboratories, Sandia National Laboratories, Albuquerque NM USA

  • Jean Anne C. Incorvia

    Electrical and Computer Engineering, University of Texas at Austin, University of Texas at Austin, ECE, The University of Texas at Austin, Electrical and Computer Engineering Dept., University of Texas at Austin, Austin TX USA