Mapping and Frequency Joint Optimization for Energy Efficient Execution of Multiple Applications on Multicore Systems

Abstract

Run-time resource managers are essential components to optimize energy consumption in cluster-based multicore architectures. However, with the ever increasing number of functionalities supported by these architectures, it is also necessary to optimize the usage of processing resources while guaranteeing that applications' timing constraints are met. In this paper, we present a new run-time management strategy that includes both processing resource allocation and frequency tuning to optimize clusters energy consumption when multiple applications are executed concurrently. The proposed hybrid allocation process minimizes the number of used processing cores while meeting the latency constraint of each application. This approach offers a good trade-off between efficiency and complexity. The achieved energy saving has been demonstrated through various case-studies with different sets of active applications. Results show an improvement of energy saving up to 206% when compared to the literature.