Steven Louis;Hannah Bradley;Cody Trevillian;Andrei Slavin;Vasyl Tyberkevych
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引用次数: 0
Abstract
This letter presents a novel spiking artificial neuron design based on a combined spin valve/magnetic tunnel junction (SV/MTJ). Traditional hardware used in artificial intelligence and machine learning faces significant challenges related to high power consumption and scalability. To address these challenges, spintronic neurons, which can mimic biologically inspired neural behaviors, offer a promising solution. We present a model of an SV/MTJ-based neuron that uses technologies that have been successfully integrated with CMOS in commercially available applications. The operational dynamics of the neuron are derived analytically through the Landau–Lifshitz-Gilbert–Slonczewski equation, demonstrating its ability to replicate key spiking characteristics of biological neurons such as response latency and refractive behavior. Simulation results indicate that the proposed neuron design can operate on a timescale of about 1 ns, without any bias current and with power consumption as low as 50
${\mu }$
W.
期刊介绍:
IEEE Magnetics Letters is a peer-reviewed, archival journal covering the physics and engineering of magnetism, magnetic materials, applied magnetics, design and application of magnetic devices, bio-magnetics, magneto-electronics, and spin electronics. IEEE Magnetics Letters publishes short, scholarly articles of substantial current interest.
IEEE Magnetics Letters is a hybrid Open Access (OA) journal. For a fee, authors have the option making their articles freely available to all, including non-subscribers. OA articles are identified as Open Access.