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SkyANN

Financiado

Skyrmionic Artificial Neural Networks

The Skyrmionic Artificial Neural Network (SkyANN) presents a groundbreaking paradigm for neuromorphic computing, closely emulating brain neurophysiology by combining skyrmionic quasiparticles, which mimic neurotransmitters and fac... ver más

31/12/2027

ARISTOTLE UNIVERSI...

3M€

Presupuesto del proyecto: 3M€

Líder del proyecto

ARISTOTELIO PANEPISTIMIO THESSALONIKIS No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

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Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2023-11-30

HORIZON-CL4-2023-DIGITAL-EMERGING-01-11: Low TRL research in micro-electroni... ExpectedOutcome:Projects are expected to contribute to the following outcomes:

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No hay información privada compartida para este proyecto. Habla con el coordinador.

6 Participantes

ARISTOTLE UNIVERSITY OF THES...

553.06K€ | Lider

UNIVERSITY OF MANCHESTER

N.D. | Participante

UNIVERSITE PARISSACLAY

60.64K€ | Participante

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Duración del proyecto: 49 meses Fecha Inicio: 2023-11-30
Fecha Fin: 2027-12-31

Líder del proyecto

ARISTOTELIO PANEPISTIMIO THESSALONIKIS No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 3M€

Descripción del proyecto The Skyrmionic Artificial Neural Network (SkyANN) presents a groundbreaking paradigm for neuromorphic computing, closely emulating brain neurophysiology by combining skyrmionic quasiparticles, which mimic neurotransmitters and facilitate complex computations at the synapse level, with electrical CMOS connections that simulate the propagation of action potentials among neurons for rapid and dense inter-layer connectivity. Our innovative magneto-electric devices aim to achieve energy consumption four orders of magnitude lower than CMOS technology and double the bandwidth for the same device footprint, enhancing edge inference and learning capabilities. This approach challenges contemporary neural networks implemented with CMOS digital, mixed-signal, and emerging in-memory computing technologies, which are limited by lower energy efficiency and reliability. Building on preliminary results from SkyANN partners, we plan an ambitious endeavor to develop a first-of-its-kind magneto-electric neural network, showcasing the promising potential of this novel technology. Along the way, we will refine materials, processes, design methodologies, and architectures to prepare the European micro- and nano-electronics ecosystem for the future, while supporting the EU's Green Deal vision. Our well-balanced consortium brings together complementary expertise and extensive knowledge, spanning from device physics to circuits and architectures across multiple layers of design abstraction. As a result, the SkyANN consortium is poised to facilitate the rapid transfer of fundamental discoveries to relevant industrial stakeholders, accelerating impact and reinforcing European strengths in the economically, geopolitically, and socially vital semiconductor sector.

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