• DocumentCode
    2441890
  • Title

    A scheduling framework for large-scale, parallel, and topology-aware applications

  • Author

    Kravtsov, Valentin ; Bar, Pavel ; Carmeli, David ; Schuster, Assaf ; Swain, Martin

  • Author_Institution
    Comput. Sci. Dept., Technion - Israel Inst. of Technol., Haifa, Israel
  • fYear
    2010
  • fDate
    19-23 April 2010
  • Firstpage
    1
  • Lastpage
    12
  • Abstract
    Scheduling of large-scale, distributed topology-aware applications requires that not only the properties of the requested machines be considered, but also the properties of the machines´ interconnections. This requirement severely complicates the scheduling process, as even a matching between a single multi-processors task and available machines in a single time slot becomes an NP-complete problem with no polynomial approximation. In this paper we propose a complete scheduling framework for multi-cluster, heterogeneous environments that provides, in practice, an efficient solution for the scheduling of topology-aware applications. The proposed framework is very flexible as it is composed of pluggable components and can be easily configured to support a variety of scheduling policies. W e also describe three novel scheduling and coallocation algorithms that were developed and plugged into the framework. The proposed scheduling framework was integrated into the QosCosGrid system, where it is used as the main decision-making module.
  • Keywords
    computational complexity; grid computing; parallel processing; resource allocation; scheduling; NP-complete problem; QosCosGrid system; coallocation algorithm; large-scale applications; machine interconnection; multicluster heterogeneous environment; parallel applications; pluggable components; polynomial approximation; scheduling policy; topology-aware applications; Application software; Cities and towns; Computer science; Grid computing; Large-scale systems; NP-complete problem; Network topology; Processor scheduling; Resource management; Systems biology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Parallel & Distributed Processing (IPDPS), 2010 IEEE International Symposium on
  • Conference_Location
    Atlanta, GA
  • ISSN
    1530-2075
  • Print_ISBN
    978-1-4244-6442-5
  • Type

    conf

  • DOI
    10.1109/IPDPS.2010.5470470
  • Filename
    5470470