Communication-Aware Scheduling of Data-Parallel Tasks on Multicore Architectures

Abstract

Task scheduling has a significant impact on multicore computing systems. This paper studies scheduling of data-parallel tasks on multicore architectures. Unlike traditional task scheduling, this work allows individual tasks to run on multiple cores in a data-parallel fashion. In this paper, the inter-task communication overhead is taken into account during scheduling. The communication happens if main threads of two tasks with data-dependencies are mapped onto the different processors. This paper proposes two methods for data-parallel task scheduling with communication overhead. One is two-step method, which schedules tasks without communication and then assigns threads in the task on cores. The other is integrated method, which performs task scheduling and thread assignment simultaneously. Both of the two methods are based on integer linear programming. The proposed methods are evaluated through experiments and encouraging results are obtained.