• DocumentCode
    3636168
  • Title

    Team-Based Message Logging: Preliminary Results

  • Author

    Esteban Meneses;Celso L. Mendes;Laxmikant V. Kalé

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
  • fYear
    2010
  • Firstpage
    697
  • Lastpage
    702
  • Abstract
    Fault tolerance will be a fundamental imperative in the next decade as machines containing hundreds of thousands of cores will be installed at various locations. In this context, the traditional checkpoint/restart model does not seem to be a suitable option, since it makes all the processors roll back to their latest checkpoint in case of a single failure in one of the processors. In-memory message logging is an alternative that avoids this global restoration process and instead replays the messages to the failed processor. However, there is a large memory overhead associated with message logging because each message must be logged so it can be played back if a failure occurs. In this paper, we introduce a technique to alleviate the demand of memory in message logging by grouping processors into teams. These teams act as a failure unit: if one team member fails, all the other members in that team roll back to their latest checkpoint and start the recovery process. This eliminates the need to log message contents within teams. The savings in memory produced by this approach depend on the characteristics of the application, the number of messages sent per computation unit and size of those messages. We present promising results for multiple benchmarks. As an example, the NPB-CG code running class D on 512 cores manages to reduce the memory overhead of message logging by 62%.
  • Keywords
    "Protocols","Clouds","Grid computing","Computer science","USA Councils","Fault tolerance","Context modeling","Memory management","Frequency","Resumes"
  • Publisher
    ieee
  • Conference_Titel
    Cluster, Cloud and Grid Computing (CCGrid), 2010 10th IEEE/ACM International Conference on
  • Print_ISBN
    978-1-4244-6987-1
  • Type

    conf

  • DOI
    10.1109/CCGRID.2010.110
  • Filename
    5493401