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Fun-COMP SIGNED

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

Total Cost €

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EC-Contrib. €

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Partnership

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Project "Fun-COMP" data sheet

The following table provides information about the project.

Coordinator
THE UNIVERSITY OF EXETER 

Organization address
address: THE QUEEN'S DRIVE NORTHCOTE HOUSE
city: EXETER
postcode: EX4 4QJ
website: www.ex.ac.uk

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 United Kingdom [UK]
 Project website http://www.fun-comp.org
 Total cost 3˙996˙951 €
 EC max contribution 3˙996˙951 € (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-2017-1
 Funding Scheme RIA
 Starting year 2018
 Duration (year-month-day) from 2018-03-01   to  2022-02-28

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    THE UNIVERSITY OF EXETER UK (EXETER) coordinator 607˙766.00
2    INTERUNIVERSITAIR MICRO-ELECTRONICA CENTRUM BE (LEUVEN) participant 616˙550.00
3    WESTFAELISCHE WILHELMS-UNIVERSITAET MUENSTER DE (MUENSTER) participant 611˙000.00
4    THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD UK (OXFORD) participant 604˙015.00
5    THALES SA FR (COURBEVOIE) participant 588˙550.00
6    IBM RESEARCH GMBH CH (RUESCHLIKON) participant 555˙770.00
7    CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS FR (PARIS) participant 413˙300.00

Map

 Project 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.

 Deliverables

List of deliverables.
Website for access by general public made live Websites, patent fillings, videos etc. 2020-01-14 14:25:13
Second cross-disciplinary training session and associated training webinars/videos Websites, patent fillings, videos etc. 2020-01-14 14:27:04
Article published in popular scientific/technical magazine/website Websites, patent fillings, videos etc. 2020-01-14 14:25:15
Extended unit-cell with WDM capability demonstrated Documents, reports 2020-01-14 14:26:58
Report on fabrication and performance of first-generation basic N-vN unit-cell devices Documents, reports 2020-01-14 14:26:59
Web-based report and animations of N-vN device simulations Websites, patent fillings, videos etc. 2020-01-14 14:27:01
First cross-disciplinary training session and associated training webinars/videos Websites, patent fillings, videos etc. 2020-01-14 14:26:56

Take a look to the deliverables list in detail:  detailed list of Fun-COMP deliverables.

 Publications

year authors and title journal last update
List of publications.
2018 Syed Ghazi Sarwat, Nathan Youngblood, Yat-Yin Au, Jan A. Mol, C. David Wright, Harish Bhaskaran
Engineering Interface-Dependent Photoconductivity in Ge 2 Sb 2 Te 5 Nanoscale Devices
published pages: 44906-44914, ISSN: 1944-8244, DOI: 10.1021/acsami.8b17602
ACS Applied Materials & Interfaces 10/51 2019-10-30
2019 Andrew Katumba, Xin Yin, Joni Dambre, Peter Bienstman
A Neuromorphic Silicon Photonics Nonlinear Equalizer For Optical Communications With Intensity Modulation and Direct Detection
published pages: 2232-2239, ISSN: 0733-8724, DOI: 10.1109/jlt.2019.2900568
Journal of Lightwave Technology 37/10 2019-10-30
2019 Syed Ghazi Sarwat, Zengguang Cheng, Nathan Youngblood, Mohd Sharizal Alias, Sapna Sinha, Jamie Warner, Harish Bhaskaran
Strong Opto-Structural Coupling in Low Dimensional GeSe 3 Films
published pages: 7377-7384, ISSN: 1530-6984, DOI: 10.1021/acs.nanolett.9b03039
Nano Letters 19/10 2019-10-30
2019 Xuan Li, Nathan Youngblood, Carlos Ríos, Zengguang Cheng, C. David Wright, Wolfram HP Pernice, Harish Bhaskaran
Fast and reliable storage using a 5  bit, nonvolatile photonic memory cell
published pages: 1, ISSN: 2334-2536, DOI: 10.1364/optica.6.000001
Optica 6/1 2019-10-30
2018 Zengguang Cheng, Carlos Ríos, Nathan Youngblood, C. David Wright, Wolfram H. P. Pernice, Harish Bhaskaran
Device-Level Photonic Memories and Logic Applications Using Phase-Change Materials
published pages: 1802435, ISSN: 0935-9648, DOI: 10.1002/adma.201802435
Advanced Materials 30/32 2019-10-30
2018 Delphin Dodane, Jérôme Bourderionnet, Sylvain Combrié, Alfredo de Rossi
Fully embedded photonic crystal cavity with Q=06 million fabricated within a full-process CMOS multiproject wafer
published pages: 20868, ISSN: 1094-4087, DOI: 10.1364/oe.26.020868
Optics Express 26/16 2019-10-30

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The information about "FUN-COMP" are provided by the European Opendata Portal: CORDIS opendata.

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