Performance Estimate of Inverse Rashba-Edelstein Magnetoelectric Devices for Neuromorphic Computing

Performance Estimate of Inverse Rashba-Edelstein Magnetoelectric Devices for Neuromorphic Computing

We propose a new design for a cellular neural network with spintronic neurons and CMOS-based synapses. Harnessing the magnetoelectric and inverse Rashba-Edelstein effects allows natural emulation of the behavior of an ideal cellular network. This combination of effects offers an increase in speed an...

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Veröffentlicht in:IEEE journal on exploratory solid-state computational devices and circuits 2019-06, Vol.5 (1), p.25-33
Hauptverfasser: Stephan, Andrew W., Hu, Jiaxi, Koester, Steven J.
Format: Artikel
Sprache:eng
Schlagworte:
Cellular communication
Cellular neural network (CNN)
CMOS
Computer simulation
energy efficiency
Frequency modulation
magnetoelectric (ME)
Mathematical model
Neural networks
Neurons
Rashba–Edelstein
Saturation magnetization
Spintronics
Synapses
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Zusammenfassung:We propose a new design for a cellular neural network with spintronic neurons and CMOS-based synapses. Harnessing the magnetoelectric and inverse Rashba-Edelstein effects allows natural emulation of the behavior of an ideal cellular network. This combination of effects offers an increase in speed and efficiency over other spintronic neural networks. A rigorous performance analysis via simulation is provided.
ISSN:2329-9231
2329-9231
DOI:10.1109/JXCDC.2019.2903286