Skip to Main content Skip to Navigation
New interface
Conference papers

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

Abstract : 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.
Document type :
Conference papers
Complete list of metadata

Cited literature [7 references]  Display  Hide  Download
Contributor : Julien MOTTIN Connect in order to contact the contributor
Submitted on : Wednesday, September 16, 2015 - 11:17:36 AM
Last modification on : Wednesday, July 6, 2022 - 4:19:48 AM
Long-term archiving on: : Tuesday, December 29, 2015 - 7:28:38 AM


Files produced by the author(s)




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⟩



Record views


Files downloads