Innovating Works

NEUROPULS

Financiado
NEUROmorphic energy-efficient secure accelerators based on Phase change material...
NEUROmorphic energy-efficient secure accelerators based on Phase change materials aUgmented siLicon photonicS The growing need to transfer massive amounts of data among multitudes of interconnected devices for e.g., self-driving vehicles, IoT or industry 4.0 has led to a quest towards low-power and secure approaches to locally processing... The growing need to transfer massive amounts of data among multitudes of interconnected devices for e.g., self-driving vehicles, IoT or industry 4.0 has led to a quest towards low-power and secure approaches to locally processing data. Neuromorphic computing, a brain-inspired approach, addresses this need by radically changing the processing of information. Although neuromorphic electrical computing systems offer advantages in terms of CMOS implementations and scalability, they inherit limitations of conventional electronics such as low energy-efficiency, high latency and low bandwidth density. Besides, such systems often require robust security layers for e.g., safety-critical applications. Security layers based on memory-stored secret keys are prone to several types of memory-accessing attacks. Therefore, silicon hardware approaches for security primitives such as physical unclonable functions (PUFs) are currently investigated because of their absence of long-term digital memory storage. Although electronic PUFs have received major attention thanks to their native CMOS implementation, for secure authentication they are prone to machine learning and side-channel attacks due to their CMOS technology. The NEUROPULS project aims to build next-generation low-power and secure edge-computing systems by developing novel photonic computing architectures and security layers based on photonic PUFs in augmented silicon photonics CMOS-compatible platforms. The integration of emerging non-volatile phase change materials for synapses/neurons and III-V materials for on-chip spiking sources, for the first time, will allow to build novel neuromorphic accelerators featuring RISC-V compliant interfaces for smooth adoption and programmability. Optimal performance will be achieved thanks to a novel full-system simulation platform for design space exploration. Three relevant use-cases will be considered for benchmarking to demonstrate 2 orders of magnitude energy efficiency improvement. ver más
31/12/2026
CNRS
8M€
Duración del proyecto: 49 meses Fecha Inicio: 2022-11-24
Fecha Fin: 2026-12-31

Línea de financiación: concedida

El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2022-11-24
Línea de financiación objetivo El proyecto se financió a través de la siguiente ayuda:
HORIZON-CL4-2021-DIGITAL-EMERGING-01-01: Ultra-low-power, secure processors for edge computing (RIA)
Cerrada hace 3 años
Presupuesto El presupuesto total del proyecto asciende a 8M€
Líder del proyecto
CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE... No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico TRL 4-5