TY - JOUR
T1 - A Vision for All-Spin Neural Networks
T2 - A Device to System Perspective
AU - Sengupta, Abhronil
AU - Roy, Kaushik
N1 - Publisher Copyright:
© 2004-2012 IEEE.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2016/12
Y1 - 2016/12
N2 - Spin-transfer torque (STT) mechanisms in vertical and lateral spin valves and magnetization reversal/domain wall motion with spin-orbit torque (SOT) have opened up new possibilities of efficiently mimicking 'neural' and 'synaptic' functionalities with much lower area and energy consumption compared to CMOS implementations. In this paper, we review various STT/SOT devices that can provide a compact and area-efficient implementation of artificial neurons and synapses. We provide a device-circuit-system perspective and envision design of an All-Spin neuromorphic processor (with different degrees of bio-fidelity) that can be potentially appealing for ultra-low power cognitive applications.
AB - Spin-transfer torque (STT) mechanisms in vertical and lateral spin valves and magnetization reversal/domain wall motion with spin-orbit torque (SOT) have opened up new possibilities of efficiently mimicking 'neural' and 'synaptic' functionalities with much lower area and energy consumption compared to CMOS implementations. In this paper, we review various STT/SOT devices that can provide a compact and area-efficient implementation of artificial neurons and synapses. We provide a device-circuit-system perspective and envision design of an All-Spin neuromorphic processor (with different degrees of bio-fidelity) that can be potentially appealing for ultra-low power cognitive applications.
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U2 - 10.1109/TCSI.2016.2615312
DO - 10.1109/TCSI.2016.2615312
M3 - Article
AN - SCOPUS:85002902556
VL - 63
SP - 2267
EP - 2277
JO - IEEE Transactions on Circuits and Systems I: Regular Papers
JF - IEEE Transactions on Circuits and Systems I: Regular Papers
SN - 1549-8328
IS - 12
M1 - 7755884
ER -