The following table provides information about the project.
THE UNIVERSITY OF EXETER
|Coordinator Country||United Kingdom [UK]|
|Total cost||3˙996˙951 €|
|EC max contribution||3˙996˙951 € (100%)|
1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
|Duration (year-month-day)||from 2018-03-01 to 2022-02-28|
Take a look of project's partnership.
|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|
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.
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The information about "FUN-COMP" are provided by the European Opendata Portal: CORDIS opendata.
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