Opendata, web and dolomites

NEoteRIC SIGNED

NEuromorphic Reconfigurable Integrated photonic Circuits as artificial image processor

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 NEoteRIC project word cloud

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

boundaries    resolution    gframe    speed    optical    single    holistic    connections    energy    volatile    machine    spanning    transistor    relies    restructure    recurrent    paradigms    routes    neumann    technological    reconfigurable    rewire    paramount    networks    unlock    incorporates    neural    circuit    lower    incorporate    magnitude    upscaling    enhancement    dense    exhibiting    stratagem    modalities    sec    stretch    pushing    power    marginal    excellence    resonators    platform    computational    utilized    primary    consumption    unconventional    reservoir    merits    chips    image    orders    silicon    paving    proliferating    ring    performance    von    pixel    architectural    shifters    incorporation    chip    inter    demanding    merge    rate    multiple    imaging    classification    tested    innovations    powerful    consuming    generation    neuromorphic    convolutional    frame    fpgas    spatial    push    electronic    photonic    simultaneous    architectures    time    computing    mzis    neoteric    deep    fpga    cornerstone    reconfigurability    components    learning    simultaneously   

Project "NEoteRIC" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITAT POLITECNICA DE VALENCIA 

Organization address
address: CAMINO DE VERA SN EDIFICIO 3A
city: VALENCIA
postcode: 46022
website: www.upv.es

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 Spain [ES]
 Total cost 3˙965˙394 €
 EC max contribution 3˙965˙394 € (100%)
 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    UNIVERSITAT POLITECNICA DE VALENCIA ES (VALENCIA) coordinator 580˙000.00
2    IBM RESEARCH GMBH CH (RUESCHLIKON) participant 747˙950.00
3    COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES FR (PARIS 15) participant 512˙532.00
4    PANEPISTIMIO AIGAIOU EL (MYTILINI) participant 435˙312.00
5    EULAMBIA ADVANCED TECHNOLOGIES MONOPROSOPI ETAIRIA PERIORISMENIS EFTHINIS EL (AG PARASKEYI) participant 410˙000.00
6    TERAMOUNT LTD IL (JERUSALEM) participant 392˙750.00
7    ETHNIKO KENTRO EREVNAS KAI TECHNOLOGIKIS ANAPTYXIS EL (THERMI THESSALONIKI) participant 361˙875.00
8    UNIVERSITEIT GENT BE (GENT) participant 328˙812.00
9    PROPHESEE FR (PARIS) participant 196˙162.00

Map

 Project objective

NEoteRIC’s primary objective is the generation of holistic photonic machine learning paradigms that will address demanding imaging applications in an unconventional approach providing paramount frame rate increase, classification performance enhancement and orders of magnitude lower power consumption compared to the state-of-the-art machine learning approaches. NEoteRIC’s implementation stratagem incorporates multiple innovations spanning from the photonic “transistor” level and extending up to the system architectural level, thus paving new, unconventional routes to neuromorphic performance enhancement. The technological cornerstone of NEoteRIC relies on the development and upscaling of a high-speed reconfigurable photonic FPGA-like circuit that will incorporate highly-dense and fully reconfigurable key silicon photonic components (ring resonators, MZIs, etc.). High-speed reconfigurability will unlock the ability to restructure the photonic components and rewire inter-component connections. Through NEoteRIC the integrated photonic FPGAs will be strengthened by the incorporation of novel marginal-power consuming non-volatile high-speed phase shifters that will push the boundaries of energy consumption. NEoteRIC’s “unconventional” chips will be utilized as a proliferating neuromorphic computational platform that will merge the merits of photonic and electronic technology and will allow the all-optical implementation of powerful non-von Neumann architectures such as Reservoir Computing, Recurrent Neural Networks, Deep Neural Networks and Convolutional Neural Networks simultaneously by the same photonic chip. The in-project excellence will be tested through demanding high impact application such as high frame-rate image analysis and in particular single-pixel time-stretch modalities thus pushing the boundaries of state-of-the-art; exhibiting simultaneous high spatial resolution and Gframe/sec processing rate.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "NEOTERIC" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

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

More projects from the same programme (H2020-EU.2.1.1.)

TheFSM (2020)

The Food Safety Market: an SME-powered industrial data platform to boost the competitiveness of European food certification

Read More  

MedPhab (2020)

Photonics Solutions at Pilot Scale for Accelerated Medical Device Development

Read More  

5E (2019)

Federating European Electronics Ecosystems for Competitive Electronics Industries

Read More