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Spintronic Integrate-Fire-Reset Neuron with Stochasticity for Neuromorphic Computing.

Qu Yang1, Rahul Mishra1,2, Yunuo Cen1

  • 1Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576, Singapore.

Nano Letters
|October 19, 2022
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Summary
This summary is machine-generated.

Researchers developed a novel spintronic neuron device for neuromorphic computing. This device mimics biological neurons with spontaneous resets and probabilistic spiking, achieving high accuracy in pattern recognition tasks.

Keywords:
exchange biasneuromorphic computingspintronic neuronspin−orbit torquespontaneous resetstochasticity

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Area of Science:

  • Neuromorphic Computing
  • Spintronics
  • Biologically Inspired Computing

Background:

  • Spintronics offers energy efficiency and scalability for neuromorphic computing.
  • Existing spintronic devices lack biorealistic neuron functionalities like spontaneous reset and probabilistic spiking.

Purpose of the Study:

  • To propose and demonstrate a biorealistic spintronic neuron device.
  • To achieve spontaneous reset and stochastic firing in a spintronic neuron.

Main Methods:

  • Fabrication of a heavy metal/ferromagnet/antiferromagnet (HM/FM/AFM) spin-orbit torque (SOT) heterostructure.
  • Utilizing AFM exchange bias for autoreset functionality.
  • Leveraging SOT and AFM pinning competition for stochastic firing.

Main Results:

  • Demonstration of a spintronic neuron with spontaneous reset and stochastic firing.
  • Implementation of a restricted Boltzmann machine (RBM) and stochastic integration multilayer perceptron (SI-MLP) using the neuron.
  • Achieved 97.38% accuracy in pattern recognition, surpassing baseline accuracy.

Conclusions:

  • The proposed spintronic neuron device successfully emulates biologically realistic spiking neurons.
  • This work provides a viable spintronic solution for advanced neuromorphic computing applications.