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PlasmoniAC SIGNED

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

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EC-Contrib. €

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Partnership

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 PlasmoniAC project word cloud

Explore the words cloud of the PlasmoniAC project. It provides you a very rough idea of what is the project "PlasmoniAC" about.

volatile    mac    linear    platforms    power    energy    recurrent    function    fabricate    plasmonics    invests    gt    magnitude    materials    ideal    detection    1014    modules    model    fan    oriented    introducing    envelopes    co    bandwidth    vi    threat    material    scaling    size    holistic    interconnects    sustaining    neurons    software    properly    3d    efficiencies    optic    neuromorphic    employs    electro    proven    powerful    integration    library    sin2    bridging    elevate    optimizing    credible    blend    compatible    memristor    nx100gb    sigmoid    delivering    bandwidths    respectively    feed    training    embrace    security    deploy    sioc    consumption    100gb    learning    plasmoniac    computing    sixny    deep    plasmo    machines    electronic    hardware    activation    platform    computations    nanoelectronics    orders    plasmonic    full    adopting    release    um2    weight    constituent    functions    tanh    class    computationally    photonic    computational    artificial    credentials    ultra    malware    succeeding    thermo    cmos    footprint    suite    efficiency    nm    16    relu    neuron    nanophotonic    bto    memory    ultimately   

Project "PlasmoniAC" data sheet

The following table provides information about the project.

Coordinator
ARISTOTELIO PANEPISTIMIO THESSALONIKIS 

Organization address
address: KEDEA BUILDING, TRITIS SEPTEMVRIOU, ARISTOTLE UNIV CAMPUS
city: THESSALONIKI
postcode: 54636
website: www.auth.gr

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Greece [EL]
 Total cost 4˙114˙926 €
 EC max contribution 3˙999˙458 € (97%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
 Code Call H2020-ICT-2019-2
 Funding Scheme RIA
 Starting year 2020
 Duration (year-month-day) from 2020-01-01   to  2022-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    ARISTOTELIO PANEPISTIMIO THESSALONIKIS EL (THESSALONIKI) coordinator 666˙875.00
2    IBM RESEARCH GMBH CH (RUESCHLIKON) participant 502˙750.00
3    UNIVERSITY OF SOUTHAMPTON UK (SOUTHAMPTON) participant 465˙777.00
4    COMMUNAUTE D' UNIVERSITES ET ETABLISSEMENTS UNIVERSITE BOURGOGNE - FRANCHE - COMTE FR (BESANCON) participant 420˙000.00
5    EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH CH (ZUERICH) participant 397˙910.00
6    INTERUNIVERSITAIR MICRO-ELECTRONICA CENTRUM BE (LEUVEN) participant 375˙353.00
7    CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS FR (PARIS) participant 345˙492.00
8    GESELLSCHAFT FUR ANGEWANDTE MIKRO UND OPTOELEKTRONIK MIT BESCHRANKTERHAFTUNG AMO GMBH DE (AACHEN) participant 317˙500.00
9    MELLANOX TECHNOLOGIES LTD - MLNX IL (YOKNEAM) participant 306˙550.00
10    VPIPHOTONICS GMBH DE (BERLIN) participant 201˙250.00

Map

 Project objective

PlasmoniAC invests in neuromorphic computing towards sustaining processing power and energy efficiency scaling, adopting the best-in-class material and technology platforms for optimizing computational power, size and energy at every of its constituent functions. It employs the proven high-bandwidth and low-loss credentials of photonic interconnects together with the nm-size memory function of memristor nanoelectronics, bridging them by introducing plasmonics as the ideal technology for offering photonic-level bandwidths and electronic-level footprint computations within ultra-low energy consumption envelopes. Following a holistic hardware/software co-design approach, PlasmoniAC targets the following objectives: i) to elevate plasmonics into a computationally-credible platform with Nx100Gb/s bandwidth, um2-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 100Gb/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, v) to embrace them into a properly adapted Deep Learning training model suite, ultimately delivering a neuromorphic plasmonic software design library, and vi) to apply them on IT security-oriented applications for threat and malware detection. Succeeding in its targets will release a powerful artificial plasmonic neuron suite with up to 3 orders of magnitude higher computational efficiencies per neuron and 1 and 6 orders of magnitude higher energy and footprint efficiencies, respectively, compared to the top state-of-the-art neuromorphic machines.

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The information about "PLASMONIAC" are provided by the European Opendata Portal: CORDIS opendata.

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