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Reexen

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Ultra low cost ultra high efficiency AI processor for enabling fast and cost e...

Ultra low cost ultra high efficiency AI processor for enabling fast and cost effective deployment of edge computing applications "Since the breakthrough application of Deep Neural Networks algorithms (DNNs) to speech and image recognition, the number of applications that use DNNs has exploded, achieving the highest accuracy in a myriad of contexts (health,... ver más

30/04/2020

Cybertron

71K€

Presupuesto del proyecto: 71K€

Líder del proyecto

CYBERTRON TECH GMBH No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

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Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2020-04-30

EIC-SMEInst-2018-2020: SME instrument

I+D

Cerrada hace 5 años

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Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

Información adicional privada

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2 Participantes

Cybertron

50.00K€ | Lider

TAFESA, S.A.

1.43M€ | Participante

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Duración del proyecto: 4 meses Fecha Inicio: 2019-12-04
Fecha Fin: 2020-04-30

Líder del proyecto

CYBERTRON TECH GMBH No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 71K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto "Since the breakthrough application of Deep Neural Networks algorithms (DNNs) to speech and image recognition, the number of applications that use DNNs has exploded, achieving the highest accuracy in a myriad of contexts (health, robotics, finance, gaming, etc.). However, their superior accuracy comes at the cost of high computational complexity. Current approaches to solve this challenge are cloud-based, incurring in high power consumption and high latency, given their communication needs. Although cloud approaches are suitable for some context, they are suboptimal for real-time applications running on embedded or mobile devices (with limited battery capacity and requiring fast responses). REEXEN appears to bring a solution to this challenge: an extremely efficient AI processor (a semiconductor chip) specifically designed for supporting DNN-based edge applications. By exploiting state-of-the-art semiconductor technologies in mixed-signal circuits and in-memory processing, REEXEN obtains the best power-efficiency when executing DNN algorithms, in terms of maximum throughput per energy unit consumption (30 TOPs/W). By reducing the ""distance"" between data generation (sensors), data storage (memory) and data processing (core processor or nucleus), and by eliminating A/D conversions, REEXEN also achieves minimum latency (<10ms) and fabrication area, thus also reducing the overall cost of production. REEXEN completely aligns with the EU approach to AI, as an enabling technology that will allow the development of current industry-transversal smart services and the implementation of future new ones. Our company is 100% focused on developing next generation of ultra-low power neural network processors. From the successful results of our early prototyping for audio applications, REEXEN project will attract the best talent and additional financing to build the business around our technology and increase our company size, international presence and job generation."

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