EU H2020 NeurONN: Two-Dimensional Oscillatory Neural Networks for Energy Efficient Neuromorphic Computing - Archive ouverte HAL Access content directly
Poster Communications Year : 2021

EU H2020 NeurONN: Two-Dimensional Oscillatory Neural Networks for Energy Efficient Neuromorphic Computing

Siegfried Karg
Elisabetta Corti
  • Function : Author
  • PersonId : 1067413
Juan Núñez
  • Function : Author
  • PersonId : 988882
Jafar Shamsi
  • Function : Author
  • PersonId : 1082869
Armin Klumpp
  • Function : Author
Jamila Boudaden
  • Function : Author
Théophile Gonos
  • Function : Author
  • PersonId : 1067415
Tanguy Hardelin
  • Function : Author
  • PersonId : 1067417
Marie Durieu
  • Function : Author
  • PersonId : 1082870
Ahmed Nejim
Slobodan Mijalkovic
  • Function : Author
  • PersonId : 1082871

Abstract

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 871501. ARTIFICIAL INTELLIGENCE AT THE EDGE. NEUROMORPHIC COMPUTING ONN Architecture for 5 neurons neurons (oscillators) Synapse Array with 2D MoS 2 memristors MIT VO 2 oscillators 2D MoS 2 memristor Materials Modeling (DFT) Density of States (DOS) Mobility Effective Mass Semiclassical Transport Modeling (TCAD) Compact Modeling (SPICE) Devices Characteristics Compact Models
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Dates and versions

hal-03364335 , version 1 (11-10-2021)

Identifiers

  • HAL Id : hal-03364335 , version 1

Cite

Aida Todri-Sanial, Thierry Gil, Nadine Azemard, Jérémie Salles, Eirini Karachristou, et al.. EU H2020 NeurONN: Two-Dimensional Oscillatory Neural Networks for Energy Efficient Neuromorphic Computing. EuroNanoForum 2021, May 2021, Braga, Portugal. ⟨hal-03364335⟩
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