Description du projet
Un pas (artificiel) en avant pour la technologie des véhicules autonomes
Avec les progrès récents de l’apprentissage artificiel, nombreux sont ceux qui cherchent à appliquer cette technologie dans d’autres domaines, notamment dans celui des véhicules autonomes (VA), qui présente un potentiel considérable. Ces voitures sans conducteur pourraient apporter de grands avantages au secteur des transports, en réduisant le trafic, les accidents, les coûts et les temps de déplacement. Malheureusement, les tâches d’apprentissage profond nécessaires à un fonctionnement sûr et efficace des VA sont trop gourmandes en énergie et en processeurs pour les modèles actuels. Le projet Hailo-8, financé par l’UE, a pour objectif de développer une alternative appelée Hailo-8 qui accaparerait moins d’espace et serait moins gourmande en énergie et en coûts, tout en permettant de faire progresser les technologies des VA.
Objectif
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.
Champ scientifique
- 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
Programme(s)
Régime de financement
SME-2 - SME instrument phase 2Coordinateur
6789139 TEL-AVIV
Israël
L’entreprise s’est définie comme une PME (petite et moyenne entreprise) au moment de la signature de la convention de subvention.