DEEP OSCILLATORY NEURAL NETWORKS COMPUTING AND LEARNING THROUGH THE DYNAMICS OF RF NEURONS INTERCONNECTED BY RF SPINTRONIC SYNAPSES

Objective

The goal of RadioSpin is to build a hardware neural network that computes using neural dynamics as in the brain, has a deep layered architecture as in the neocortex, but runs and learns faster, by seven orders of magnitude. For this purpose, we will use ultrafast radio-frequency (RF) oscillators to imitate the rich, reconfigurable dynamics of biological neurons. Within the RadioSpin project, we will develop a new breed of nanosynapses, based on spintronics technology, that directly process the RF signals sent by neurons and interconnects them layer-wise. We will demonstrate and benchmark our concept by building a lab-scale prototype that co-integrates for the first time CMOS RF neurons with spintronic RF synapses. We will develop brain-inspired algorithms harnessing oscillations, synchrony and edge-of-chaos for computing and show that they can run on RadioSpin deep network RF technology. Finally, we will benchmark RadioSpin technology for biomedical and RF fingerprinting applications where fast and low energy consumption classification of RF signals are key.
To achieve its ambitious goals RadioSpin brings together frontier researchers along the entire chain of neuromorphic engineering, from material science (spintronic nanodevices), physics (non-linear dynamics), electronics (RF CMOS design), computer science (artificial intelligence algorithms), and microwave signal processing. Two innovative companies bring real-life use-cases (microwave mammography and IoT RF fingerprinting). The scientific experts are further complemented by experts in the field of innovation, commercial deployment and IP monetisation, as well as communication and public engagement.

Field of science

• /engineering and technology/electrical engineering, electronic engineering, information engineering/electronic engineering/signal processing
• /medical and health sciences/clinical medicine/cancer/breast cancer
• /natural sciences/physical sciences/electromagnetism and electronics/spintronics
• /natural sciences/computer and information sciences/artificial intelligence/computational intelligence

Programme(s)

• H2020-EU.1.2.2. - FET Proactive

Topic(s)

• FETPROACT-09-2020 - Neuromorphic computing technologies

Call for proposal

H2020-FETPROACT-2020-01
See other projects for this call

Funding Scheme

RIA - Research and Innovation action

Coordinator

UNIVERSITE DE BORDEAUX

Address

Place Pey Berland 35
33000 Bordeaux
France

Activity type

Higher or Secondary Education Establishments

EU contribution

€ 898 526,25

Participants (5)

CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS

France

EU contribution

€ 611 510

Address

Rue Michel Ange 3
75794 Paris

Activity type

Research Organisations

LABORATORIO IBERICO INTERNACIONAL DE NANOTECNOLOGIA

Portugal

EU contribution

€ 726 562,50

Address

Avenida Mestre Jose Veiga Congredados
4715 330 Braga

Activity type

Research Organisations

THALES

France

EU contribution

€ 681 172,50

Address

Tour Carpe Diem Place Des Corolles Esplanade Nord
92400 Courbevoie

Activity type

Private for-profit entities (excluding Higher or Secondary Education Establishments)

UMBRIA BIOENGINEERING TECNOLOGIES SOCIETA A RESPONSABILITA LIMITATA

Italy

EU contribution

€ 673 062,50

Address

Via Santa Maria Della Spina 25
06081 Frazione Rivotorto

Activity type

Private for-profit entities (excluding Higher or Secondary Education Establishments)

CLANCY HAUSSLER RITA

Austria

EU contribution

€ 282 108,75

Address

Trins 46
6152 Trins

Activity type

Private for-profit entities (excluding Higher or Secondary Education Establishments)