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SpinENGINE SIGNED

Harnessing the Emergent Properties of Nanomagnet Ensembles for Massively Parallel Data Analysis

Total Cost €

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EC-Contrib. €

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Partnership

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Project "SpinENGINE" data sheet

The following table provides information about the project.

Coordinator
NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET NTNU 

Organization address
address: HOGSKOLERINGEN 1
city: TRONDHEIM
postcode: 7491
website: www.ntnu.no

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 Norway [NO]
 Total cost 3˙001˙826 €
 EC max contribution 3˙001˙826 € (100%)
 Programme 1. H2020-EU.1.2.1. (FET Open)
 Code Call H2020-FETOPEN-2018-2019-2020-01
 Funding Scheme RIA
 Starting year 2020
 Duration (year-month-day) from 2020-01-01   to  2023-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET NTNU NO (TRONDHEIM) coordinator 831˙495.00
2    UNIVERSITEIT GENT BE (GENT) participant 607˙150.00
3    THE UNIVERSITY OF SHEFFIELD UK (SHEFFIELD) participant 594˙961.00
4    IBM RESEARCH GMBH CH (RUESCHLIKON) participant 576˙042.00
5    EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH CH (ZUERICH) participant 392˙177.00

Map

 Project objective

The SpinENGINE project will lay the foundations for a new, massively parallel, computational platform based on emergent behaviour in large nanomagnet ensembles. The project will develop an efficient, highly scalable, and easily reproducible platform meeting the data analysis challenges in our increasingly data-rich society. We will build upon our recent discoveries and use complex, nonlinear, and highly tunable interactions in such ensembles to realize a hardware platform for “Reservoir Computing”, a biologically-inspired computational approach. Our critical hypothesis is that the synergies between the inherent properties of nanomagnet ensembles and those required for reservoir computing will enable the efficient creation of a highly adaptive computational platform for the analysis of complex, dynamic data sets. This has the potential to greatly outperform current approaches using conventional CMOS hardware.

SpinENGINE will bring together a multidisciplinary team of researchers with expertise in computer science, condensed matter physics, material science, computational modelling, and high-resolution microscopy. This will enable us to simultaneously explore the fundamental behaviours of nanomagnet ensembles and understand how these can be harnessed for useful computation. By the end of the project, we aim to fabricate a proof-of-concept device capable of solving pattern recognition and classification problems, and, in collaboration with our industrial partner, IBM, produce a roadmap to the further scaling and commercialization of our computational platform. Success in the SpinENGINE project will have vast implications for data analysis at all scales, ranging from low power computation in the simplest sensor node to accelerated data processing in the most complex supercomputer.

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The information about "SPINENGINE" are provided by the European Opendata Portal: CORDIS opendata.

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