Spiking hybrid edge computing for robust optoelectronical signal processingbroad
SpikeHERO · Horizon Europe grant · 2025-10-01–2029-09-30
EC contribution
Total cost
Beneficiaries
About the data
Source: CORDIS (official EU open data), Horizon Europe. Framework HORIZON · call HORIZON-EIC-2024-PATHFINDERCHALLENGES-01 · scheme HORIZON-EIC · topic HORIZON-EIC-2024-PATHFINDERCHALLENGES-01-04. CORDIS record →
Objective
SpikeHERO’s ambitious goal is to design, experimentally realize, and validate a heterogeneous system for low-energy communication and data processing at the edge. It will pursue a holistic approach that maximally leverages a co-design process encompassing both novel integration techniques and the exploration of systems combining electrical and optical chiplets. SpikeHERO will exploit advanced integration technologies, beyond CMOS devices and non-von Neumann architectures in the form of electrical and optical Spiking Neural Networks. When used as a fiber to the edge (FTTE) system to demonstrate a novel optical interconnection, SpikeHERO will significantly reduce the energy consumption from 7-10 W to 1-2 W, while increasing the bandwidth from 10 GHz to 30 GHz. The requirements for SpikeHERO are derived from challenging use cases in the context of smart edge devices as well as inputs from industry partners. The utilized co-design process allows to optimize the overall system performance with regards to the energy efficiency of the entire system. After the overall system is specified and the subsystems are developed and tested, integration can take place through an advanced packaging solution. Besides the advances on the hardware development in SpikeHERO, a digital twin including the optical and electrical Spiking Neural Network is developed. SpikeHERO directly addresses the specific objective of the EIC challenge aimed at reducing energy consumption in smart edge devices by exploring and implementing novel materials, 3D multi-die heterogeneous integration, beyond CMOS devices, and non-von Neumann architectures. The project proposes a unique integration of optical and electrical Spiking Neural Networks that operate conjointly to enhance processing speed and power efficiency, setting a new standard for energy-efficient computing at the edge.
Beneficiaries (4)
| Organisation | Country | Role | EC contribution | SME |
|---|---|---|---|---|
| FRAUNHOFER GESELLSCHAFT ZUR FORDERUNG DER ANGEWANDTEN FORSCHUNG EV | DE | coordinator | €1,461,312 | |
| TECHNISCHE UNIVERSITEIT EINDHOVEN | NL | participant | €1,362,230 | |
| HEWLETT PACKARD ENTERPRISE BELGIUM | BE | participant | €871,250 | |
| ARGOTECH AS | CZ | participant | €535,014 | Yes |
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