Detecting sharing patterns in industrial parallel applications for embedded heterogeneous multicore systems

Abstract

Embedded devices are becoming more and more present everywhere. Moreover, mobile devices are becoming also more computationally powerful. These embedded architectures present new challenges since they execute several applications that must preserve security, allow sharing information in a coherent way, to be scalable and provide the required levels of performance, while at the same time they must be power efficient. The vIrtical project focuses on these challenges. In this context, as a starting point, we tackle the characterization of applications targeted for the hardware platform developed, that is, a heterogeneous multicore SoC. The aim is to analyze memory sharing patterns in order to exploit them to make the coherence protocols more scalable and power-efficient. We have identified that 60% of the accessed blocks are data, and from those only 40% require coherence maintenance. © 2013 Springer-Verlag.