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Magnetic Domain Wall Based Synaptic and Activation Function Generator for Neuromorphic Accelerators.

Saima A Siddiqui1, Sumit Dutta1, Astera Tang2

  • 1Department of Electrical Engineering and Computer Science , Massachusetts Institute of Technology , Cambridge , Massachusetts 02139 , United States.

Nano Letters
|January 1, 2020
PubMed
Summary
This summary is machine-generated.

Magnetic domain walls, used in logic and memory devices, can implement linear and nonlinear functions for neuromorphic computing. These domain-wall devices offer efficient synaptic weight generation and thresholding for deep neural networks.

Keywords:
Analog synapseactivation function generatormagnetic domain wallmagnetic tunnel junctionneural networknonvolatile memory

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Area of Science:

  • Spintronics
  • Neuromorphic Engineering
  • Materials Science

Background:

  • Magnetic domain walls serve as information carriers in advanced computing architectures.
  • Neuromorphic accelerators aim to emulate brain functions by integrating logic and memory.
  • Current synaptic devices face challenges in speed and energy efficiency.

Purpose of the Study:

  • To demonstrate the capability of magnetic domain wall devices for implementing linear and programmable nonlinear functions.
  • To evaluate the potential of these devices for synaptic weight generation and thresholding in deep neural networks.
  • To assess the speed and energy efficiency of magnetic domain wall devices for neuromorphic applications.

Main Methods:

  • Fabrication of micrometer-size devices utilizing electrical manipulation of magnetic domain walls.
  • Characterization of device performance using short current pulses (8 ns).
  • Analysis of energy consumption for synaptic weight modulation.

Main Results:

  • Devices successfully implemented both linear and programmable nonlinear functions.
  • Demonstrated suitability for synaptic weight generators and thresholding elements.
  • Achieved high operational speed (8 ns pulses) and low energy consumption (≤16 pJ for weight modulation).

Conclusions:

  • Magnetic domain wall devices are a promising technology for efficient neuromorphic computing.
  • These devices offer competitive speed and energy performance compared to existing nonvolatile synaptic devices.
  • Scaled 20 nm devices are projected to approach the energy efficiency of biological neurons.