Graded-Anisotropy-Induced Magnetic Domain Wall Drift for an Artificial Spintronic Leaky Integrate-and-Fire Neuron

Autor: Wesley H. Brigner, Xuan Hu, Naimul Hassan, Christopher H. Bennett, Jean Anne C. Incorvia, Felipe Garcia-Sanchez, Joseph S. Friedman
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, Vol 5, Iss 1, Pp 19-24 (2019)
Druh dokumentu: article
ISSN: 2329-9231
DOI: 10.1109/JXCDC.2019.2904191
Popis: Spintronic three-terminal magnetic-tunnel-junction (3T-MTJ) devices have gained considerable interest in the field of neuromorphic computing. Previously, these devices required external circuitry to implement the leaking functionality that leaky integrate-and-fire (LIF) neurons should display. However, the use of external circuitry results in decreased device efficiency. We previously demonstrated lateral inhibition with a 3T-MTJ neuron that intrinsically performs the leaking, integrating, and firing functions; however, it required the fabrication of a complex multilayer structure. In this paper, we introduce an anisotropy gradient to implement a single-layer intrinsically leaking 3T-MTJ LIF neuron without the use of any external circuitry. This provides the leaking functionality with no hardware cost and reduced fabrication complexity, which increases the device, circuit, system, and cost efficiency.
Databáze: Directory of Open Access Journals