Innovating Works

PlasmoniAC

Financiado
Energy and Size efficient Ultra fast Plasmonic Circuits for Neuromorphic Comput...
Energy and Size efficient Ultra fast Plasmonic Circuits for Neuromorphic Computing Architectures 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 ev... 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. ver más
30/09/2023
ARISTOTLE UNIVERSI...
4M€
Duración del proyecto: 45 meses Fecha Inicio: 2019-12-05
Fecha Fin: 2023-09-30

Línea de financiación: concedida

El organismo H2020 notifico la concesión del proyecto el día 2023-09-30
Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:
ICT-06-2019: Unconventional Nanoelectronics
Cerrada hace 5 años
Presupuesto El presupuesto total del proyecto asciende a 4M€
Líder del proyecto
ARISTOTELIO PANEPISTIMIO THESSALONIKIS No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico TRL 4-5