Integrated neuromorphic computing networks by artificial spin synapses and spin neurons

Title
Integrated neuromorphic computing networks by artificial spin synapses and spin neurons
Authors
김재욱정연주김태윤양승모신정훈문경웅장가브리엘현다슬양정엽황찬용홍진표
Issue Date
2021-01
Publisher
NPG Asia Materials
Citation
VOL 13, 11
Abstract
One long-standing goal in the emerging neuromorphic field is to create a reliable neural network hardware implementation that has low energy consumption, while providing massively parallel computation. Although diverse oxide-based devices have made significant progress as artificial synaptic and neuronal components, these devices still need further optimization regarding linearity, symmetry, and stability. Here, we present a proof-of-concept experiment for integrated neuromorphic computing networks by utilizing spintronics-based synapse (spin-S) and neuron (spin-N) devices, along with linear and symmetric weight responses for spin-S using a stripe domain and activation functions for spin-N. An integrated neural network of electrically connected spin-S and spin-N successfully proves the integration function for a simple pattern classification task. We simulate a spin-N network using the extracted device characteristics and demonstrate a high classification accuracy (over 93%) for the spin-S and spin-N optimization without the assistance of additional software or circuits required in previous reports. These experimental studies provide a new path toward establishing more compact and efficient neural network systems with optimized multifunctional spintronic devices.
URI
http://pubs.kist.re.kr/handle/201004/72872
ISSN
1884-4049
Appears in Collections:
KIST Publication > Article
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