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vGrouper: Optimizing the Performance of Parallel Jobs in Xen by Increasing Synchronous Execution of Virtual Machines

  • Peng Jiang
  • Ligang HeEmail author
  • Shenyuan Ren
  • Junyu Li
  • Yuhua Cui
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11276)

Abstract

Xen is one of the most popular virtualization platforms nowadays, which has been broadly used by the industry. Credit scheduler, the default scheduler of Xen, was initially designed for serial jobs, which achieves good performance overall for serial jobs. Unfortunately, the parallel jobs are likely to co-exist with serial jobs in the same host in practice, the resource contention between virtual machines results in severe performance degradation of the parallel jobs. In this paper, we propose vGrouper, a progressive solution to enhance the performance of the parallel jobs. The vGrouper focuses on synchronizing the execution time of the parallel nodes in order to achieve the best performance of the parallel job. Moreover, the vGrouper guarantees that the parallel job nodes are able to run concurrently on pCPUs for the entire time slice, which maximizes the efficiency of communication between parallel nodes. A prototype of vGrouper is implemented, the experimental results demonstrate that the performance of the parallel job and resource utilization in Xen have been significantly improved.

Keywords

Xen Virtual machine Virtualization Parallel jobs Scheduling 

References

  1. 1.
    Chen, H., Jin, H., Hu, K., Huang, J.: Scheduling overcommitted VM: behavior monitoring and dynamic switching-frequency scaling. Future Gener. Comput. Syst. 29(1), 341–351 (2013).  https://doi.org/10.1016/j.future.2011.08.006. Including Special section: AIRCC-NetCoM 2009 and Special section: Clouds and Service-Oriented ArchitecturesCrossRefGoogle Scholar
  2. 2.
    Huang, W., Liu, J., Abali, B., Panda, D.K.: A case for high performance computing with virtual machines. In: Proceedings of the 20th Annual International Conference on Supercomputing, ICS 2006, pp. 125–134. ACM, New York (2006).  https://doi.org/10.1145/1183401.1183421
  3. 3.
    Shao, Z., Wang, Q., Xie, X., Jin, H., He, L.: Analyzing and improving MPI communication performance in overcommitted virtualized systems. In: 2011 IEEE 19th Annual International Symposium on Modelling, Analysis, and Simulation of Computer and Telecommunication Systems, pp. 381–389, July 2011.  https://doi.org/10.1109/MASCOTS.2011.27
  4. 4.
    Weng, C., Wang, Z., Li, M., Lu, X.: The hybrid scheduling framework for virtual machine systems. In: Proceedings of the 2009 ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments, VEE 2009, pp. 111–120. ACM, New York (2009).  https://doi.org/10.1145/1508293.1508309
  5. 5.
    Ye, K., Jiang, X., Chen, S., Huang, D., Wang, B.: Analyzing and modeling the performance in Xen-based virtual cluster environment. In: 2010 IEEE 12th International Conference on High Performance Computing and Communications, HPCC, pp. 273–280, September 2010.  https://doi.org/10.1109/HPCC.2010.79

Copyright information

© IFIP International Federation for Information Processing 2018

Authors and Affiliations

  • Peng Jiang
    • 1
  • Ligang He
    • 1
    Email author
  • Shenyuan Ren
    • 1
  • Junyu Li
    • 1
  • Yuhua Cui
    • 2
  1. 1.Department of Computer ScienceUniversity of WarwickCoventryUK
  2. 2.Shandong Worldwide Byte Security Co.Ltd.JinanChina

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