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PlasmoniAC

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01.01.2020 — 30.09.2023

PlasmoniAC

Energy- and Size-efficient Ultra-fast Plasmonic Circuits for Neuromorphic Computing Architectures

Förderer Funding Agency: EU

Förderkennzeichen Grant ID: 871391

Following a holistic hardware/software co-design approach, PlasmoniAC targets the following objectives:
i) to elevate plasmonics into a computationally-credible platform with Nx100 Gb/s bandwidth, μm2-scale size and >1014 MAC/s/W computational energy efficiency, using CMOS compatible BTO and SiOC materials for electro-and thermo-optic computational functions,
ii) to blend them via a powerful 3D co-integration platform with SixNy-based photonic interconnects and with non-volatile memristor-based weight control,
iii) to fabricate two different sets of 100 Gb/s 16-and 8-fan-in linear plasmonic neurons,
iv) to deploy a whole new class of plasmo-electronic and nanophotonic activation modules,
v) to demonstrate a full-set of sin2(x), ReLU, sigmoid and tanh plasmonic neurons for Feed-Forward and recurrent neurons,
vi) to embrace them into a properly adapted Deep Learning training model suite, ultimately delivering a neuromorphic plasmonic software design library, and
vii) to apply them on IT security-oriented applications for threat and malware detection.

https://cordis.europa.eu/project/id/871391/reporting

Kontakt

Dr. rer. nat. Stephan Suckow

https://www.linkedin.com/in/stephan-suckow-34b949199/
Group Leader - Nanophotonics


Website

www.plasmoniac.eu

Industrial Partners

  • IBM Research Zürich (CH)
  • Mellanox Technologies Ltd (IL)
  • VPIphotonics GmbH (DE)
  • Lumiphase AG (CH)

Research Centers

  • CNRF (FR)
  • IMEC (BE)

Academic Partners

  • Aristotle University of Thessaloniki (GR)
  • University of Southampton (UK)
  • ETH Zürich (CH)
  • University of Burgundy – Franche-Comté (FR)

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