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Hailo-8

Financiado

Cerrado

End to end hardware implementation of Artificial Neural Networks for Edge Comput...

End to end hardware implementation of Artificial Neural Networks for Edge Computing in Autonomous Vehicles Autonomous Vehicles (AVs) present a great opportunity for the transport sector to reduce accidents, traffic congestion, time of travel and travel costs. However, for effectiveness, AVs need to process large amounts of data collect... ver más

31/08/2020

HAILOTECH

3M€

Presupuesto del proyecto: 3M€

Líder del proyecto

HAILO TECHNOLOGIES LTD No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

Ver 7 Participantes

Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2020-08-31

EIC-SMEInst-2018-2020: SME instrument

I+D

Cerrada hace 7 años

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Información adicional privada

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

7 Participantes

HAILOTECH

2.10M€ | Lider

COMERCIAL NICEM EXINTE

613.56K€ | Participante

FRANCISCO ALBERO

718.48K€ | Participante

INDUSTRIAS LANEKO

704.13K€ | Participante

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Duración del proyecto: 18 meses Fecha Inicio: 2019-02-27
Fecha Fin: 2020-08-31

Líder del proyecto

HAILO TECHNOLOGIES LTD No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 3M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto Autonomous Vehicles (AVs) present a great opportunity for the transport sector to reduce accidents, traffic congestion, time of travel and travel costs. However, for effectiveness, AVs need to process large amounts of data collected by the vehicle sensors at the edge, which requires a very powerful processor capable of computing Deep Learning (DL) tasks. This is currently lacking in the market as evidenced by the inefficiencies in current processors in processing big data at the edge in real time. Most processors for edge computing are currently reliant on CPU and GPU architectures which are challenged by Deep Learning tasks. The processors have low computational capabilities which increases their latencies (processing times). This leads to heat dissipation problems and high power consumption. The processors are also rigged with complexities that raise development costs and the price of the processors. The processors are also not easily scalable, which makes it difficult for miniaturisation. Hailo-Tech has developed Hailo-8, which is specifically designed to optimise Edge Computing processor capabilities to allow neural network deployment through enhancing processor computational efficiency, resulting in higher capacity within the constraints of an edge device. Hailo-8 meets the industry need of optimised edge data processing by providing a first-class ASIC micro-processor that is based on a completely new micro-architecture that can execute neural network based machine learning algorithms. Hailo-8 will provide AV owners with high computational efficiency (x1,000 compared to alternative solutions), giving an immediate response after data processing. Hailo-8 increases power efficiency by a factor of 100 and has better area and cost efficiency by a factor of 10 compared to other processors. To bring the disruptive device successfully to the market we need to further perform some technical and commercial activities which required an investment of €2.993,750 M.

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