High Performance Task Scheduling Algorithm for Heterogeneous Computing System

A key issue in obtaining high performance from a parallel program represented by a Directed A-cyclic Graph (DAG) is to efficiently mapping it into the target system. The problem is generally addressed in terms of task scheduling, where the tasks are the schedulable units of a program. The task scheduling problems have been shown to be NP-complete in general as well as several restricted cases. In order to be of practical use for large applications, scheduling algorithms must guarantee high performance by minimizing the schedule length and scheduling time. In this paper we propose a new task-scheduling algorithm namely, High Performance task Scheduling (HPS) algorithm for heterogeneous computing system with complexity O (v + e) (p+ log v), which provides optimal results for applications represented by DAGs. The performance of the algorithm is illustrated by comparing the schedule length, speedup, efficiency and the scheduling time with existing algorithms reported in this paper. The comparison study based on both randomly generated graphs and graphs of some real applications shows that HPS algorithm substantially outperforms existing algorithms.