Evaluating Dynamic Scheduling of Tasks in Mobile Architectures Using ParallelME Framework

Abstract

Recently we observe that mobile phones stopped being just devices for basic communication to become providers of many applications that require increasing performance for good user experience. Inside today’s mobile phones we find different processing units (PU) with high computational capacity, as multicore architectures and co-processors like GPUs. Libraries and run-time environments have been proposed to improve applications’ performance by taking advantage of different PUs in a transparent way. Among these environments we can highlight the ParallelME. Despite the importance of task scheduling strategies in these environments, ParallelME has implemented only the First Come Firs Serve (FCFS) strategy. In this paper we extended the ParallelME framework by implementing and evaluating two different dynamic scheduling strategies, Heterogeneous Earliest Finish Time (HEFT) and Performance-Aware Multiqueue Scheduler (PAMS). We evaluate these strategies considering synthetic applications, and compare the proposals with the FCFS. For some scenarios, PAMS was proved to be up to 39% more efficient than FCFS. These gains usually imply on lower energy consumption, which is very desirable when working with mobile architectures.