Using Programmable Graphene Channels as Weights in Spin-Diffusive Neuromorphic Computing

Using Programmable Graphene Channels as Weights in Spin-Diffusive Neuromorphic Computing

A graphene-based spin-diffusive neural network is presented in this paper that takes advantage of the locally tunable spin transport of graphene and the non-volatility of nanomagnets. By using electrostatically gated graphene as spintronic synapses, a weighted summation operation can be performed in...

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Bibliographic Details
Main Authors: Jiaxi Hu, Gordon Stecklein, Yoska Anugrah, Paul A. Crowell, Steven J. Koester
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Journal on Exploratory Solid-State Computational Devices and Circuits
Subjects:
Analog weights
graphene
magnetic materials
neural networks
spin valves
spintronics
Online Access:https://ieeexplore.ieee.org/document/8334624/

Internet

https://ieeexplore.ieee.org/document/8334624/

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