Experimental Demonstration of Ferroelectric Spiking Neurons for Unsupervised Clustering

Zheng Wang, Brian Crafton, Jorge Gomez, Ruijuan Xu, Aileen Luo, Zoran Krivokapic, Lane Martin, Suman Datta, Arijit Raychowdhury, Asif Islam Khan

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

62 Citas (Scopus)

Resumen

We report the first experimental demonstration of ferroelectric field-effect transistor (FEFET) based spiking neurons. A unique feature of the ferroelectric (FE) neuron demonstrated herein is the availability of both excitatory and inhibitory input connections in the compact 1T-1FEFET structure, which is also reported for the first time for any neuron implementations. Such dual neuron functionality is a key requirement for bio-mimetic neural networks and represents a breakthrough for implementation of the third generation spiking neural networks (SNNs) - also reported herein for unsupervised learning and clustering on real world data for the first time. The key to our demonstration is the careful design of two important device level features: (1) abrupt hysteretic transitions of the FEFET with no stable states therein, and (2) the dynamic tunability of the FEFET hysteresis by bias conditions which allows for the inhibition functionality. Experimentally calibrated, multi-domain Preisach based FEFET models were used to accurately simulate the FE neurons and project their performance at scaled nodes. We also implement an SNN for unsupervised clustering and benchmark the network performance across analog CMOS and emerging technologies and observe (1) unification of excitatory and inhibitory neural connections, (2) STDP based learning, (3) lowest reported power (3.6nW) during classification, and (4) a classification accuracy of 93%.

Idioma originalInglés
Título de la publicación alojada2018 IEEE International Electron Devices Meeting, IEDM 2018
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas13.3.1-13.3.4
ISBN (versión digital)9781728119878
DOI
EstadoPublicada - 2 jul. 2018
Publicado de forma externa
Evento64th Annual IEEE International Electron Devices Meeting, IEDM 2018 - San Francisco, Estados Unidos
Duración: 1 dic. 20185 dic. 2018

Serie de la publicación

NombreTechnical Digest - International Electron Devices Meeting, IEDM
Volumen2018-December
ISSN (versión impresa)0163-1918

Conferencia

Conferencia64th Annual IEEE International Electron Devices Meeting, IEDM 2018
País/TerritorioEstados Unidos
CiudadSan Francisco
Período1/12/185/12/18

Nota bibliográfica

Publisher Copyright:
© 2018 IEEE.

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