Advertisement

Applying Variable Neighborhood Search Algorithm to Multicore Task Scheduling Problem

  • Chang Wang
  • Jiang Jiang
  • Xianbin Xu
  • Xing Han
  • Qiang Cao
Part of the Communications in Computer and Information Science book series (CCIS, volume 396)

Abstract

The emergence of multicore processors makes multicore task scheduling a focus of researchers. Since the multicore task scheduling problem is NP-hard, in most cases only approximate algorithms can be adopted to resolve it. This paper provides a detail analysis of the four aspects of applying variable neighborhood search algorithm (VNSA) to the multicore task scheduling problem. We further give a solution: (1) we propose a general solution model named task assignment matrix (TAM) (2) and define relevant element swap operations between the TAM instances; (3) then we present a construction method of the neighborhood and the neighborhood set; (4) finally we introduce a local search strategy for the neighborhood set. We have proved the effectiveness of this scheme through experiments. The results show that the scheduled tasks with different communication to computation ratio have a 1.079-4.258 times performance improvement.

Keywords

VNSA multicore processor task scheduling 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Hill, M.D., Marty, M.R.: Amdahl’s Law in the Multicore Era. Computer 41, 33–38 (2008)CrossRefGoogle Scholar
  2. 2.
    Lusa, A., Potts, C.A.: Variable Neighbourhood Search Algorithm for the Constrained Task Allocation Problem. Journal of the Operational Research Society 59, 812–822 (2007)CrossRefGoogle Scholar
  3. 3.
    Geng, X., Xu, G., Wang, D.: A Task Scheduling Algorithm Based on Multicore Processors. In: 2011 International Conference on Mechatronic Science, Electric Engineering and Computer (MEC), pp. 942–945 (2011)Google Scholar
  4. 4.
    Song, F., YarKhan, A., Dongarra, J.: Dynamic Task Scheduling for Linear Algebra Algorithms on Distributed-Memory Multicore Systems. In: Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis (2009)Google Scholar
  5. 5.
    Chen, W., Hung, H.: Energy-efficient Scheduling of Periodic Real-time Tasks for Reliable Multicore Systems. In: Electrical and Control Engineering (ICECE), pp. 5887–5890 (2011)Google Scholar
  6. 6.
    Mladenovic, N., Hansen, P.: Variable Neighborhood Search. Computers & Operations Research 24, 1097–1100 (1997)MathSciNetCrossRefzbMATHGoogle Scholar
  7. 7.
    Blum, C.: Metaheuristics in Combinatorial Optimization: Overview and Conceptual Comparison. ACM Computing Surveys (CSUR) 35, 268–308 (2003)CrossRefGoogle Scholar
  8. 8.
    Hansen, P., Mladenović, N.: Variable Neighborhood Search: Principles and Applications. European Journal of Operational Research 130, 449–467 (2001)MathSciNetCrossRefzbMATHGoogle Scholar
  9. 9.
    Cheng, H.: A High Efficient Task Scheduling Algorithm Based on Heterogeneous Multi-Core Processor. In: 2010 2nd Database Technology and Applications (DBTA), pp. 26–29 (2010)Google Scholar
  10. 10.
    Ilavarasan, E., Thambidurai, P.: Low Complexity Performance Effective Task Scheduling Algorithm for Heterogeneous Computing Environments. Journal of Computer Sciences 3, 94–103 (2007)Google Scholar
  11. 11.
    Kwok, Y.-K., Ahmad, I.: Efficient Scheduling of Arbitrary Task Graphs to Multiprocessors Using a Parallel Genetic Algorithm. Journal of Parallel and Distributed Computing 47, 58–77 (1997)CrossRefGoogle Scholar
  12. 12.
    Kwok, Y.: Benchmarking the Task Graph Scheduling Algorithms. In: Parallel Processing Symposium, IPPS/SPDP 1998, pp. 531–537 (1998)Google Scholar
  13. 13.
    Olteanu, A., Marin, A.: Generation and Evaluation of Scheduling DAGs: How to Provide Similar Evaluation 1, 57–66 (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Chang Wang
    • 1
  • Jiang Jiang
    • 1
  • Xianbin Xu
    • 2
  • Xing Han
    • 1
  • Qiang Cao
    • 1
  1. 1.School of MicroelectronicsShanghai Jiao Tong University ShanghaiChina
  2. 2.School of ComputerWuhan University WuhanChina

Personalised recommendations