Approximation-Aware Scheduling on Heterogeneous Multi-core Architectures

The high performance demand of embedded systems along with restrictive thermal design power (TDP) constraint have lead to the emergence of the heterogenous multi-core architec-tures, where cores with the same instruction-set architecture but different power-performance characteristics provide new opportunities for energy-efficient computing. Heterogeneity introduces challenges in scheduling the tasks to the appropri-ate cores and selecting the frequency assignment of each core. In this paper, we introduce an approximation-aware schedul-ing framework for soft real-time tasks on the heterogeneous multi-core architectures. We consider multiple versions of a task obtained by introducing approximation in the computation to provide different levels of quality of service (QoS) versus performance tradeoffs. The additional choice of approxima-tion allows us more flexibility in meeting the performance and TDP constraints while maximizing QoS per unit of energy. I