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  KEYWORD

Software development techniques for resilient embedded GPUs

keywords GPU, NVIDIA, ACCELERATOR, GPU, PEDESTRIAN RECOGNITION, DEPENDABILITY, SAFETY

Reference persons LUCA STERPONE

Research Groups GR-05 - ELECTRONIC CAD & RELIABILITY GROUP - CAD

Description Autonomous driving is today largely supported by embedded high performance General Purpose Graphical Processing Unit (GPGPU) that executes image elaboration and control algorithms enabling self-driving cars. The activity of this thesis, done in collaboration with NVIDIA, is based on the development of applications and analysis of errors by the development of new fault injection methods on one of the state-of-the-art NVIDIA device (Jetson nano) which has a Maxwell NVIDIA architecture with 128 cores.

Required skills C, C++, basic Knowledge of the GPU architecture


Deadline 20/09/2019      PROPONI LA TUA CANDIDATURA




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