Formulation and Practical Solution for the Optimization of Memory Accesses in Embedded Vision Systems
Khadija Hadj Salem, Yann Kieffer, Stéphane Mancini
Citation: Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 8, pages 609–617 (2016)
Abstract. The design of modern-day electronic devices carry many interesting optimization challenges, one of which is the efficient access to the image memory. For some particular cases of image treatments, Mancini and Rousseau (Proc.DATE, 2012) have proposed a software system, called Memory Management Optimization (MMOpt), that creates adhoc memory hierarchies for accelerating the accesses to the memories holding the image on which image treatments are applied. It splits input and output images into tiles, and prefetches the input tiles into local buffers for faster accesses.
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