Self-reset schemes for Magnetic domain wall-based neuron

TL;DR

This paper explores various self-reset schemes for magnetic domain wall-based spintronic neurons, emphasizing how different reset strategies impact energy efficiency in mimicking biological neuron dynamics.

Contribution

It provides a detailed analysis of reset mechanisms in magnetic domain wall neurons, highlighting their energy consumption and importance for efficient neuromorphic computing.

Findings

Reset energy varies from several pJ to a few fJ.

Self-reset strategies significantly influence energy efficiency.

All studied neurons enter a refractory period upon reset.

Abstract

Spintronic artificial spiking neurons are promising due to their ability to closely mimic the leaky integrate-and-fire (LIF) dynamics of the biological LIF spiking neuron. However, the neuron needs to be reset after firing. Few of the spintronic neurons that have been proposed in the literature discuss the reset process in detail. In this article, we discuss the various schemes to achieve this reset in a magnetic domain wall (DW) based spintronic neuron in which the position of the DW represents the membrane potential. In all the spintronic neurons studied, the neuron enters a refractory period and is reset when the DW reaches a particular position. We show that the self-reset operation in the neuron devices consumes energy that can vary from of several pJ to a few fJ, which highlights the importance of the reset strategy in improving the energy efficiency of spintronic artificial spiking neurons.