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Financement de l’UE (3 999 459 €) : Circuits plasmoniques ultra-rapides économes en énergie et en taille pour les architectures de calcul neuromorphique Hor 01/01/2020 Programme de recherche et d'innovation de l'UE « Horizon »
Texte
Circuits plasmoniques ultra-rapides économes en énergie et en taille pour les architectures de calcul neuromorphique
PlasmoniAC invests in neuromorphic computing towards sustaining processing power and energy efficiency scaling, adopting the best-in-class material and technology platforms for optimizing computational power, size and energy at every of its constituent functions. It employs the proven high-bandwidth and low-loss credentials of photonic interconnects together with the nm-size memory function of memristor nanoelectronics, bridging them by introducing plasmonics as the ideal technology for offering photonic-level bandwidths and electronic-level footprint computations within ultra-low energy consumption envelopes. Following a holistic hardware/software co-design approach, PlasmoniAC targets the following objectives: i) to elevate plasmonics into a computationally-credible platform with Nx100Gb/s bandwidth, um2-scale size and >1014 MAC/s/W computational energy efficiency, using CMOS compatible BTO and SiOC materials for electro- and thermo-optic computational functions, ii) to blend them via a powerful 3D co-integration platform with SixNy-based photonic interconnects and with non-volatile memristor-based weight control, iii) to fabricate two different sets of 100Gb/s 16- and 8-fan-in linear plasmonic neurons, iv) to deploy a whole new class of plasmo-electronic and nanophotonic activation modules, v) to demonstrate a full-set of sin2(x), ReLU, sigmoid and tanh plasmonic neurons for feed-forward and recurrent neurons, v) to embrace them into a properly adapted Deep Learning training model suite, ultimately delivering a neuromorphic plasmonic software design library, and vi) to apply them on IT security-oriented applications for threat and malware detection. Succeeding in its targets will release a powerful artificial plasmonic neuron suite with up to 3 orders of magnitude higher computational efficiencies per neuron and 1 and 6 orders of magnitude higher energy and footprint efficiencies, respectively, compared to the top state-of-the-art neuromorphic machines.
| Aristotelio Panepistimio Thessalonikis | 666 875 € |
| Centre National de la Recherche Scientifique CNRS | 345 493 € |
| Eidgenoessische Technische Hochschule Zuerich | 397 910 € |
| Gesellschaft FUR Angewandte Mikro UND Optoelektronik MIT Beschränkterhaftung AMO GmbH | 317 500 € |
| IBM Research GmbH | 272 666 € |
| Interuniversitair Micro-Electronica Centrum | 375 354 € |
| Lumiphase AG | 230 084 € |
| Mellanox Technologies Ltd. - MLNX | 306 550 € |
| Universite Dijon Bourgogne | 0,00 € |
| Universite Marie et Louis Pasteur | 420 000 € |
| University of Southampton | 465 778 € |
| Vpiphotonics GmbH | 201 250 € |
https://cordis.europa.eu/project/id/871391
Cette annonce se réfère à une date antérieure et ne reflète pas nécessairement l’état actuel.