Spin Orbit Torque Based Electronic Neuron

Abstract

A device based on current-induced spin-orbit torque (SOT) that functions as an electronic neuron is proposed in this work. The SOT device implements an artificial neuron's thresholding (transfer) function. In the first step of a two-step switching scheme, a charge current places the magnetization of a nano-magnet along the hard-axis i.e. an unstable point for the magnet. In the second step, the SOT device (neuron) receives a current (from the synapses) which moves the magnetization from the unstable point to one of the two stable states. The polarity of the synaptic current encodes the excitatory and inhibitory nature of the neuron input, and determines the final orientation of the magnetization. A resistive crossbar array, functioning as synapses, generates a bipolar current that is a weighted sum of the inputs. The simulation of a two layer feed-forward Artificial Neural Network (ANN) based on the SOT electronic neuron shows that it consumes ~3X lower power than a 45nm digital CMOS implementation, while reaching ~80% accuracy in the classification of one hundred images of handwritten digits from the MNIST dataset.

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Cited by in corpus (8)

• Current-induced spin-orbit torques in ferromagnetic and antiferromagnetic systems
• Intrinsic optimization using stochastic nanomagnets
• Proposal for an All-Spin Artificial Neural Network: Emulating Neural and Synaptic Functionalities Through Domain Wall Motion in Ferromagnets
• Magnetic Skyrmions for Unconventional Computing
• Probabilistic Deep Spiking Neural Systems Enabled by Magnetic Tunnel Junction
• Hybrid Spintronic-CMOS Spiking Neural Network With On-Chip Learning: Devices, Circuits and Systems
• Energy-efficient switching of nanomagnets for computing: Straintronics and other methodologies
• Analog Signal Processing Using Stochastic Magnets