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Functionally scaled computing technology: From novel devices to non-von Neumann architectures and algorithms for a connected intelligent world

Objective

The Fun-COMP project aims to develop a new wave of industry-relevant technologies that will extend the limits facing mainstream processing and storage approaches. We will do this by delivering innovative nanoelectronic and nanophotonic devices and systems that fuse together the core information processing tasks of computing and memory, that incorporate in hardware the ability to learn adapt and evolve, that are designed from the bottom-up to take advantage of the huge benefits, in terms of increases in speed/bandwidth and reduction in power consumption, promised by the emergence of Silicon photonic systems. We will develop basic information processing building blocks that draw inspiration from biological approaches, providing computing primitives that can mimic the essential features of brain-like synapses and neurons to deliver a new foundation for fast, low-power, functionally-scaled computing based around non-von Neumann approaches. We will combine such computing primitives into reconfigurable integrated processing networks that can implement in hardware novel, intelligent, self-learning and adaptive computational approaches - including spiking neural networks, computing-in-memory and autonomous reservoir computing – and that are capable of addressing complex real-world computational problems in fast, energy-efficient ways. We will address the application of our novel technologies to future computing imperatives, including the analysis and exploitation of ‘big data’ and the ubiquity of computing arising from the ‘Internet of Things’. To realise our goals we bring together a world-leading consortium of industrial and academic researchers whose current work in the development of future information processing and storage technologies defines the state-of-the-art.

Field of science

  • /natural sciences/computer and information sciences/artificial intelligence/computational intelligence
  • /natural sciences/computer and information sciences/data science/big data
  • /natural sciences/computer and information sciences/data science/data processing

Call for proposal

H2020-ICT-2017-1
See other projects for this call

Funding Scheme

RIA - Research and Innovation action

Coordinator

THE UNIVERSITY OF EXETER
Address
The Queen's Drive Northcote House
EX4 4QJ Exeter
United Kingdom
Activity type
Higher or Secondary Education Establishments
EU contribution
€ 607 766,25

Participants (6)

THALES
France
EU contribution
€ 588 550
Address
Tour Carpe Diem Place Des Corolles Esplanade Nord
92400 Courbevoie
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
WESTFAELISCHE WILHELMS-UNIVERSITAET MUENSTER
Germany
EU contribution
€ 611 000
Address
Schlossplatz 2
48149 Muenster
Activity type
Higher or Secondary Education Establishments
THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
United Kingdom
EU contribution
€ 604 015
Address
Wellington Square University Offices
OX1 2JD Oxford
Activity type
Higher or Secondary Education Establishments
IBM RESEARCH GMBH
Switzerland
EU contribution
€ 555 770
Address
Saeumerstrasse 4
8803 Rueschlikon
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
INTERUNIVERSITAIR MICRO-ELECTRONICA CENTRUM
Belgium
EU contribution
€ 616 550
Address
Kapeldreef 75
3001 Leuven
Activity type
Research Organisations
CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS
France
EU contribution
€ 413 300
Address
Rue Michel Ange 3
75794 Paris
Activity type
Research Organisations