On the Evaluation of Contention-Aware List Schedulers on Multicore Cluster

Abstract

Parallel applications composed of a set of tasks that follow a partial precedence order represent an important class of scientific applications. In high performance computing, environments dedicated to scientific applications are composed of clusters of multicore machines, which consist typically of a set of processing cores that partially share a hierarchy of cache memory. Harnessing the available memory is crucial to achieve good performance in these clusters. This paper proposes strategies based on the list scheduling framework to schedule application tasks on individual cores of multicore clusters. Our idea is to minimize the execution time of the application, by taking into consideration cache contention. Experiments with a representative set of applications show that the scheduling algorithms with contention-aware mechanisms can improve significantly the application performance.