Skip to main content
Video s3
    Details
    Presenter(s)
    Wesley Brigner Headshot
    Display Name
    Wesley Brigner
    Affiliation
    Affiliation
    University of Texas at Dallas
    Country
    Author(s)
    Display Name
    Wesley Brigner
    Affiliation
    Affiliation
    University of Texas at Dallas
    Display Name
    Naimul Hassan
    Affiliation
    Affiliation
    University of Texas at Dallas
    Display Name
    Xuan Hu
    Affiliation
    Affiliation
    University of Texas at Dallas
    Affiliation
    Affiliation
    Sandia National Laboratories
    Affiliation
    Affiliation
    Universidad de Salamanca
    Display Name
    Matthew Marinella
    Affiliation
    Affiliation
    Sandia National Laboratories
    Affiliation
    Affiliation
    University of Texas at Austin
    Display Name
    Joseph Friedman
    Affiliation
    Affiliation
    University of Texas at Dallas
    Abstract

    Neuromorphic computing promises revolutionary improvements over conventional systems for applications that process unstructured information. To fully realize this potential, neuromorphic systems should exploit the biomimetic behavior of emerging nanodevices. In particular, exceptional opportunities are provided by the non-volatility and analog capabilities of spintronic devices. While spintronic devices that emulate neurons have been previously proposed, they require complementary metal-oxide semiconductor (CMOS) technology to function. In turn, this significantly increases the power consumption, fabrication complexity, and device area of a single neuron. This work reviews three previously proposed CMOS-free spintronic neurons designed to resolve this issue.

    Slides
    • Purely Spintronic Leaky Integrate-and-Fire Neurons (application/pdf)