Job monitoring and steering in D-Grid's High Energy Physics Community Grid

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • D. Lorenz - , University of Siegen (Author)
  • S. Borovac - , University of Wuppertal (Author)
  • P. Buchholz - , University of Siegen (Author)
  • H. Eichenhardt - , TUD Dresden University of Technology (Author)
  • T. Harenberg - , University of Wuppertal (Author)
  • P. Mättig - , University of Wuppertal (Author)
  • M. Mechtel - , University of Wuppertal (Author)
  • R. Müller-Pfefferkorn - , TUD Dresden University of Technology (Author)
  • R. Neumann - , TUD Dresden University of Technology (Author)
  • K. Reeves - , University of Wuppertal (Author)
  • Ch Uebing - , University of Siegen (Author)
  • W. Walkowiak - , University of Siegen (Author)
  • Th William - , Center for Information Services and High Performance Computing (ZIH) (Author)
  • R. Wismüller - , University of Siegen (Author)

Abstract

In the High Energy Physics Comunity Grid (HEPCG) of Germany's D-Grid initiative, a suite of tools supporting the user in monitoring his jobs was developed. In the HEP community many users submit large numbers of jobs. A considerable fraction of these jobs fail for various reasons. Until now, it has been hard or even impossible for the user to find the reason for the job failure. The AMon tool supports the user with a graphical web-based overview on status and resource usage of his jobs. The script wrapper JEM (Job Execution Monitor) monitors a job's environment giving detailed information about the job execution. Finally, once the job itself is running, a computational steering tool allows the user to interact with his job at runtime, to visualize intermediate results, and to modify job parameters.

Details

Original languageEnglish
Pages (from-to)308-314
Number of pages7
JournalFuture Generation Computer Systems
Volume25
Issue number3
Publication statusPublished - Mar 2009
Peer-reviewedYes

External IDs

Scopus 56149119030

Keywords

Research priority areas of TU Dresden

Keywords

  • Computational steering, Grid computing, High Energy Physics Community Grid, Job monitoring