Intelligent Vehicle Perception: Toward the Integration on Embedded Many-core

Tiana Rakotovao (1, 2) , Diego Puschini (1) , Julien Mottin (1) , Lukas Rummelhard (2) , Amaury Nègre (3) , Christian Laugier (2)

1 CEA-LETI - Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information
2 CHROMA - Robots coopératifs et adaptés à la présence humaine en environnements dynamiques
3 LIG - Laboratoire d'Informatique de Grenoble

Intelligent vehicles (IVs) need a perception system to model the surrounding environment. The Hybrid Sampling Bayesian Occupancy Filter (HSBOF) is a perception algorithm monitoring a grid-based model of the environment called " occupancy grid ". It is a highly data-parallel algorithm and requires a high computational performance to be executed in reasonable time. It is currently implemented in CUDA on a NVIDIA GPU. However, the GPU is power consuming and its purchase cost is too high for the embedded market. In this paper, we prove that, the couple embedded many-core/OpenCL is a feasible hardware/software architecture for replacing the GPU/CUDA. Our OpenCL implementation and experimental results on a testing hardware showed that a many-core can produce an occupancy grid every 168ms while consuming 40 times less power than the GPU. The results are promising for a future integration into IVs.

Keywords: Many-core; OpenCL; perception system

Domains: Embedded Systems

Tiana Rakotovao, Diego Puschini, Julien Mottin, Lukas Rummelhard, Amaury Nègre, et al.. Intelligent Vehicle Perception: Toward the Integration on Embedded Many-core. 6th Workshop on Parallel Programming and Run-Time Management Techniques for Many-core Architectures (PARMA), Jan 2015, Amsterdam, Netherlands. ⟨10.1145/2701310.2701313⟩. ⟨cea-01199808⟩