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arXiv · 2304.06343

A spintronic Huxley-Hodgkin-analogue neuron implemented with a single magnetic tunnel junction

Davi R. Rodrigues·Rayan Moukhader·Yanxiang Luo·Bin Fang·Adrien Pontlevy·Abbas Hamadeh·Zhongming Zeng·Mario Carpentieri·Giovanni Finocchio
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Abstract

Spiking neural networks aim to emulate the brain's properties to achieve similar parallelism and high-processing power. A caveat of these neural networks is the high computational cost to emulate, while current proposals for analogue implementations are energy inefficient and not scalable. We propose a device based on a single magnetic tunnel junction to perform neuron firing for spiking neural networks without the need of any resetting procedure. We leverage two physics, magnetism and thermal effects, to obtain a bio-realistic spiking behavior analogous to the Huxley-Hodgkin model of the neuron. The device is also able to emulate the simpler Leaky-Integrate and Fire model. Numerical simulations using experimental-based parameters demonstrate firing frequency in the MHz to GHz range under constant input at room temperature. The compactness, scalability, low cost, CMOS-compatibility, and power efficiency of magnetic tunnel junctions advocate for their broad use in hardware implementations of spiking neural networks.

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Davi R. Rodrigues, Rayan Moukhader, Yanxiang Luo, Bin Fang, Adrien Pontlevy, Abbas Hamadeh, Zhongming Zeng, Mario Carpentieri, Giovanni Finocchio. 2023-04-13. A spintronic Huxley-Hodgkin-analogue neuron implemented with a single magnetic tunnel junction. https://arxiv.org/abs/2304.06343

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