Descrizione del progetto
Un passo in avanti artificiale per la tecnologia dei veicoli autonomi
Dati i recenti progressi dell’apprendimento artificiale, molti cercano di utilizzare questa tecnologia per altri campi. Uno dei campi che mostra un grande potenziale in questo senso è il settore dei veicoli autonomi. Queste automobili senza conducente potrebbero fornire grandi vantaggi al settore dei trasporti, riducendo il traffico, gli incidenti, i costi di viaggio e il tempo. Sfortunatamente, le attività correnti di apprendimento profondo necessarie affinché i veicoli autonomi funzionino in modo efficiente e sicuro consumano in modo eccessivo l’energia e il processore per i modelli attuali. Il progetto Hailo-8, finanziato dall’UE, si propone di sviluppare un’alternativa, denominata proprio Hailo-8, che garantirebbe un minor consumo di spazio, energia e costi, consentendo anche il progresso delle tecnologie per veicoli autonomi.
Obiettivo
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.
Campo scientifico
- engineering and technologymechanical engineeringvehicle engineeringautomotive engineeringautonomous vehicles
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringcomputer hardwarecomputer processors
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
- natural sciencescomputer and information sciencesdata sciencedata processing
- natural sciencescomputer and information sciencesartificial intelligencecomputational intelligence
Programma(i)
Argomento(i)
Invito a presentare proposte
Vedi altri progetti per questo bandoBando secondario
H2020-SMEInst-2018-2020-2
Meccanismo di finanziamento
SME-2 - SME instrument phase 2Coordinatore
6789139 TEL-AVIV
Israele
L’organizzazione si è definita una PMI (piccola e media impresa) al momento della firma dell’accordo di sovvenzione.