Task assignment in heterogeneous computing systems using an effective iterated greedy algorithm

  • Authors:

  • Qinma Kang;Hong He;Huimin Song

  • Affiliations:

  • Key Laboratory of Embedded System and Service Computing, Ministry of Education, Tongji University, Shanghai 201804, China and School of Information Engineering, Shandong University at Weihai, 180 ...;School of Information Engineering, Shandong University at Weihai, 180 Wenhua Xilu, Weihai 264209, China;School of Mathematics and Statistics, Shandong University at Weihai, Weihai 264209, China

  • Venue:
  • Journal of Systems and Software
  • Year:
  • 2011

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Abstract

A fundamental issue affecting the performance of a parallel application running on a heterogeneous computing system is the assignment of tasks to the processors in the system. The task assignment problem for more than three processors is known to be NP-hard, and therefore satisfactory suboptimal solutions obtainable in an acceptable amount of time are generally sought. This paper proposes a simple and effective iterative greedy algorithm to deal with the problem with goal of minimizing the total sum of execution and communication costs. The main idea in this algorithm is to improve the quality of the assignment in an iterative manner using results from previous iterations. The algorithm first uses a constructive heuristic to find an initial assignment and iteratively improves it in a greedy way. Through simulations over a wide range of parameters, we have demonstrated the effectiveness of our algorithm by comparing it with recent competing task assignment algorithms in the literature.