Dynamic Parallel Job Scheduling in Multi-cluster Computing Systems

  • J. H. Abawajy
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3036)


Job scheduling is a complex problem, yet it is fundamental to sustaining and improving the performance of parallel processing systems. In this paper, we address an on-line parallel job scheduling problem in heterogeneous multi-cluster computing systems. We propose a new space-sharing scheduling policy and show that it performs substantially better than the conventional policies.


Schedule Policy Parallel Processing System Relative Performance Evaluation Partition Size Mean Response Time 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Ming, Q.X.: Effective Metacomputing using LSF MultiCluster. In: Proceedings of CCGrid, pp. 100–106 (2001)Google Scholar
  2. 2.
    Thyagaraj, T.K., Dandamudi, S.P.: An Efficient Adaptive Scheduling Scheme for Distributed Memory Multicomputers. IEEE Transactions on Parallel and Distributed Systems 12, 758–768 (2001)CrossRefGoogle Scholar
  3. 3.
    Abawajy, J.H., Dandamudi, S.P.: A Unified Resource Scheduling Approach on Cluster Computing Systems. In: Proceedings of the PDCS 2003, pp. 43–48 (2003)Google Scholar
  4. 4.
    Rosti, E., Smirni, E., Serazzi, G., Dowdy, L.W.: Analysis of Non-Work- Conserving Processor Partitioning Policies. In: Proceedings of JSSPP, pp. 165–181 (1995)Google Scholar
  5. 5.
    Abawajy, J.H., Dandamudi, S.P.: Scheduling Parallel Jobs with CPU and I/O Resource Requirements in Cluster Computing Systems. In: Proceedings of the 11th IEEE/ACM MASCOTS 2003, pp. 336–351 (2003)Google Scholar
  6. 6.
    Abawajy, J.H., Dandamudi, S.P.: Parallel Job Scheduling on Multi-Cluster Computing Systems. In: Proceedings of the IEEE Cluster, pp. 11–17 (2003)Google Scholar
  7. 7.
    Feitelson, D.G., Rudolph, L.: Toward Convergence in Job Schedulers for Parallel Supercomputers. In: Proceedings of JSSPP, pp. 1–26 (1996)Google Scholar
  8. 8.
    Feitelson, D.G., Jette, M.A.: Improved Utilization and Responsiveness with Gang Scheduling. In: Proceedings of JSSPP, pp. 238–261 (1997)Google Scholar
  9. 9.
    Ryu, K.D., Hollingsworth, J.K.: Exploiting Fine-Grained Idle Periods in Networks of Workstations. IEEE Transactions on Parallel and Distributed System 11, 683–698 (2000)CrossRefGoogle Scholar
  10. 10.
    Stergios, A.V., Sevcik, K.C.: Parallel Application Scheduling on Networks of Workstations. Journal of Parallel and Distributed Computing 43, 1159–1166 (1997)Google Scholar
  11. 11.
    Zhengao, Z., Dandamudi, S.P.: An Adaptive Space-Sharing Policy for Heterogeneous Parallel Systems. In: HPCN 2001, pp. 353–362 (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • J. H. Abawajy
    • 1
  1. 1.School of Information TechnologyDeakin UniversityGeelongAustralia

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