SWARM: A meta-scheduler to Minimize Job Queuing Times on Computational Grids

Jean-Alain Grunchec, Jules Hernandez-Sanchez, Sara Knott

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Some meta-schedulers query the information system of individual supercomputers in order to submit jobs to the least busy supercomputer on a computational Grid. However, this information can become outdated by the time a job starts due to changes in scheduling priorities. The MSR scheme is based on Multiple Simultaneous Requests and can take advantage of opportunities resulting from these priorities changes. This paper presents the SWARM meta-scheduler, which can speed up the execution of large sets of tasks by minimizing the job queuing time through the submission of multiple requests. Performance tests have shown that this new meta-scheduler is faster than an implementation of the MSR scheme and the gLite meta-scheduler. SWARM has been used through the GridQTL project beta-testing portal during the past year. Statistics are provided for this usage and demonstrate its capacity to achieve reliably a substantial reduction of the execution time in production conditions.
Original languageEnglish
Title of host publicationWASET
Publication statusPublished - 2009

Keywords

  • Grid Computing
  • Multiple Simultaneous Requests
  • Fault tolerance
  • GridQTL

Fingerprint

Dive into the research topics of 'SWARM: A meta-scheduler to Minimize Job Queuing Times on Computational Grids'. Together they form a unique fingerprint.

Cite this