Towards an Automatic Prediction of Image Processing Algorithms Performances on Embedded Heterogeneous Architectures

Romain Saussard (1, 2) , Boubker Bouzid (2) , Marius Vasiliu (1) , Roger Reynaud (1)

1 IEF - Institut d'électronique fondamentale
2 Technocentre Renault [Saint-Quentin-en-Yvelines]

Image processing algorithms are widely used in the automotive field for ADAS (Advanced Driver Assistance System) purposes. To embed these algorithms, semiconductor companies offer heterogeneous architectures which are composed of different processing units, often with massively parallel computing unit. However, embedding complex algorithms on these SoCs (System on Chip) remains a difficult task due to heterogeneity, it is not easy to decide how to allocate parts of a given algorithm on processing units of a given SoC. In order to help automotive industry in embedding algorithms on heterogeneous architectures, we propose a novel approach to predict performances of image processing algorithms on different computing units of a given heterogeneous SoC. Our methodology is able to predict a more or less wide interval of execution time with a degree of confidence using only high level description of algorithms to embed, and a few characteristics of computing units.

Mots clés: Heterogeneous Architectures; Performance Prediction; Image Processing

Domaines: Systèmes embarqués; Calcul parallèle, distribué et partagé [cs.DC]; Traitement des images [eess.IV]

Romain Saussard, Boubker Bouzid, Marius Vasiliu, Roger Reynaud. Towards an Automatic Prediction of Image Processing Algorithms Performances on Embedded Heterogeneous Architectures. 2015 International Conference on Parallel Processing Workshops (ICPPW), Sep 2015, Beijing, China. ⟨10.1109/ICPPW.2015.14⟩. ⟨hal-01244398⟩