Opendata, web and dolomites

ChipAI SIGNED

Energy-efficient and high-bandwidth neuromorphic nanophotonic Chips for Artificial Intelligence systems

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 ChipAI project word cloud

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

pursue    dense    bandwidth    portable    sub    requiring    artificial    pulsed    rt    intelligence    scalable    synaptic    cpu    detectors    biosensing    neuromorphic    computing    ai    optical    central    lasers    units    computers    fire    instructions    inspired    cavities    efficiency    time    consumption    bottleneck    ghz    reducing    chipai    wavelength    cpus    functional    society    perspective    emission    metal    radically    efficient    ultralow    energy    foundations    photonics    interconnects    dimensions    functions    massively    tunnelling    times    miniaturized    smaller    emulate    neurons    brain    networks    enabled    validation    fj    signals    spiking    masses    silicon    semiconductor    inefficient    light    detection    resonant    billion    biological    explicit    powered    leds    architecture    algorithms    neural    tested    revolutionized    lay    conventional    sources    uses    spike    lt    nanostructures    optically    internet    neuron    economically    interconnected    life    transforming    detect    implementing    encoding    substrates    gt    compact    network    platform    faster    cheap    nanoscale    imaging    linear    confinement    extremely    links    rates    offline   

Project "ChipAI" data sheet

The following table provides information about the project.

Coordinator
LABORATORIO IBERICO INTERNACIONAL DE NANOTECNOLOGIA 

Organization address
address: AVENIDA MESTRE JOSE VEIGA
city: BRAGA
postcode: 4715-330
website: www.inl.int

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 Portugal [PT]
 Total cost 3˙892˙005 €
 EC max contribution 3˙892˙005 € (100%)
 Programme 1. H2020-EU.1.2.1. (FET Open)
 Code Call H2020-FETOPEN-2018-2019-2020-01
 Funding Scheme RIA
 Starting year 2019
 Duration (year-month-day) from 2019-03-01   to  2022-02-28

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    LABORATORIO IBERICO INTERNACIONAL DE NANOTECNOLOGIA PT (BRAGA) coordinator 653˙625.00
2    UNIVERSITY OF GLASGOW UK (GLASGOW) participant 660˙222.00
3    TECHNISCHE UNIVERSITEIT EINDHOVEN NL (EINDHOVEN) participant 604˙701.00
4    UNIVERSITY OF STRATHCLYDE UK (GLASGOW) participant 539˙925.00
5    IBM RESEARCH GMBH CH (RUESCHLIKON) participant 509˙156.00
6    IQE plc UK (Cardiff) participant 380˙000.00
7    FCIENCIAS.ID - ASSOCIACAO PARA A INVESTIGACAO E DESENVOLVIMENTO DE CIENCIAS PT (LISBON) participant 287˙500.00
8    UNIVERSITAT DE LES ILLES BALEARS ES (PALMA DE MALLORCA) participant 256˙875.00

Map

 Project objective

The same way the internet revolutionized our society, the rise of Artificial Intelligence (AI) that can learn without the need of explicit instructions is transforming our life. AI uses brain inspired neural network algorithms powered by computers. However, these central processing units (CPU) are extremely energy inefficient at implementing these tasks. This represents a major bottleneck for energy efficient, scalable and portable AI systems. Reducing the energy consumption of the massively dense interconnects in existing CPUs needed to emulate complex brain functions is a major challenge. ChipAI aims at developing a nanoscale photonics-enabled technology capable of deliver compact, high-bandwidth and energy efficiency CPUs using optically interconnected spiking neuron-like sources and detectors. ChipAI will pursue its main goal through the exploitation of Resonant Tunnelling (RT) semiconductor nanostructures embedded in sub-wavelength metal cavities, with dimensions 100 times smaller over conventional devices, for efficient light confinement, emission and detection. Key elements developed are non-linear RT nanoscale lasers, LEDs, detectors, and synaptic optical links on silicon substrates to make an economically viable technology. This platform will be able to fire and detect neuron-like light-spiking (pulsed) signals at rates 1 billion times faster than biological neurons (>10 GHz per spike rates) and requiring ultralow energy (<10 fJ). This radically new architecture will be tested for spike-encoding information processing towards validation for use in artificial neural networks. This will enable the development of real-time and offline portable AI and neuromorphic (brain-like) CPUs. In perspective, ChipAI will not only lay the foundations of the new field of neuromorphic optical computing, as will enable new non-AI functional applications in biosensing, imaging and many other fields where masses of cheap miniaturized pulsed sources and detectors are needed.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "CHIPAI" 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 "CHIPAI" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.1.2.1.)

NARCISO (2019)

NAtuRal instability of semiConductors thIn SOlid films for sensing and photonic applications

Read More  

BRIEFING (2018)

Bridging the FET Innovation Gap

Read More  

QUEFORMAL (2019)

Quantum Engineering for Machine Learning

Read More