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MeM-Scales SIGNED

Memory technologies with multi-scale time constants for neuromorphic architectures

Total Cost €

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EC-Contrib. €

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Partnership

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 MeM-Scales project word cloud

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

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Project "MeM-Scales" data sheet

The following table provides information about the project.

Coordinator
COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES 

Organization address
address: RUE LEBLANC 25
city: PARIS 15
postcode: 75015
website: www.cea.fr

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 France [FR]
 Total cost 3˙950˙628 €
 EC max contribution 3˙950˙628 € (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    COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES FR (PARIS 15) coordinator 889˙323.00
2    AGENCIA ESTATAL CONSEJO SUPERIOR DEINVESTIGACIONES CIENTIFICAS ES (MADRID) participant 569˙926.00
3    IBM RESEARCH GMBH CH (RUESCHLIKON) participant 517˙437.00
4    INTERUNIVERSITAIR MICRO-ELECTRONICA CENTRUM BE (LEUVEN) participant 439˙931.00
5    CONSIGLIO NAZIONALE DELLE RICERCHE IT (ROMA) participant 390˙857.00
6    UNIVERSITAT ZURICH CH (ZURICH) participant 388˙905.00
7    RIJKSUNIVERSITEIT GRONINGEN NL (GRONINGEN) participant 304˙378.00
8    STICHTING IMEC NEDERLAND NL (EINDHOVEN) participant 249˙868.00
9    AICTX AG CH (ZURICH) participant 200˙000.00

Map

 Project objective

'The project MeM-Scales aims at lifting neuromorphic computing in analog spiking microprocessors to an entirely new level of performance. Work in this project is based on a dedicated commitment that novel hardware and novel computational concepts must be co-evolved in a close interaction between nano-electronic device engineering, circuit and microprocessor design, fabrication technology and computing science (machine learning and nonlinear modeling). A key to reflecting 'hardware physics' in 'computational function' and vice versa is the fundamental role played by multiple timescales. Here MeM-Scales introduces a number of innovations. On the side of physical substrates, novel memory and device technologies, supporting on-chip learning over multiple timescales for both synapses and neurons, will be fabricated. To enable timescales spanning up to 9 (!) orders of magnitude both volatile memory and non-volatile memory as well as Thin Film Transistor technology will be exploited. On the side of computational theory, autonomous learning algorithms and architectures supporting computation over these wide range of timescales will be developed. These computational methods are specifically tailored to cope with the low numerical precision, parameter drift, stochasticity, and device mismatch which are inherent in analog nano-scale devices. These cross-disciplinary efforts will lead to the fabrication of an innovative hardware/software platform as a basis for future products which combine extreme power efficiency with robust cognitive computing capabilities. This new kind of computing technology will open new perspectives, for instance, for high-dimensional distributed environmental monitoring, implantable medical diagnostic microchips, wearable electronics or human-computer interfacing.'

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

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