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Energy Efficient Neuromorphic Computing with beyond-CMOS Oscillatory Neural Networks

Corentin Delacour 1 Stefania Carapezzi 1 Gabriele Boschetto 1 Aida Todri-Sanial 1
1 SmartIES - Smart Integrated Electronic Systems
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : Oscillatory Neural Networks (ONNs) are non-von Neumann architectures where information is encoded in phase relations between coupled oscillators. In this work, we present the concept of ONN based on beyond-CMOS devices to reduce the energy footprint of neuromorphic circuits. We investigate oscillating neurons made of vanadium dioxide material (VO2) and synapses based on molybdenum disulfide (MoS2) memristors to emulate synaptic plasticity.
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https://hal-lirmm.ccsd.cnrs.fr/lirmm-03229262
Contributor : Corentin Delacour <>
Submitted on : Tuesday, May 18, 2021 - 7:01:14 PM
Last modification on : Thursday, May 20, 2021 - 3:22:59 AM

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  • HAL Id : lirmm-03229262, version 1

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Corentin Delacour, Stefania Carapezzi, Gabriele Boschetto, Aida Todri-Sanial. Energy Efficient Neuromorphic Computing with beyond-CMOS Oscillatory Neural Networks. International Conference on Neuromorphic Systems (ICONS 2021), Jul 2021, Oak Ridge, United States. ⟨lirmm-03229262⟩

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