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Conference Papers Year : 2021

Energy Efficient Neuromorphic Computing with beyond-CMOS Oscillatory Neural Networks

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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Dates and versions

lirmm-03229262 , version 1 (22-09-2021)

Identifiers

  • HAL Id : lirmm-03229262 , version 1

Cite

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