• DocumentCode
    3287620
  • Title

    Selective monitoring using performance metric predicates

  • Author

    Fineman, Charles E. ; Hontalas, Philip J.

  • Author_Institution
    NASA Ames Res. Center, Moffett Field, CA, USA
  • fYear
    1992
  • fDate
    26-29 Apr 1992
  • Firstpage
    162
  • Lastpage
    165
  • Abstract
    The field of parallel processing is going through an important evolution in technology characterized by a significant increase in the number of processors within such systems. As the number of processors increases, the conventional techniques for monitoring the performance of parallel systems will produce large amounts of data in the form of event trace files. The authors propose one possible solution to this data size problem: performance metric predicates. These predicates permit the user to define performance parameters that control the output of event trace data during the application´s execution time. The authors assert that the use of performance metric predicates provides a powerful and useful tool for the control of event trace data output from large, complex systems
  • Keywords
    parallel processing; performance evaluation; data size; event trace files; execution time; parallel processing; performance metric predicates; performance monitoring; performance parameters; Control systems; Data visualization; Degradation; Measurement; Monitoring; NASA; Parallel processing; Portable media players; Programming profession; Space technology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Scalable High Performance Computing Conference, 1992. SHPCC-92, Proceedings.
  • Conference_Location
    Williamsburg, VA
  • Print_ISBN
    0-8186-2775-1
  • Type

    conf

  • DOI
    10.1109/SHPCC.1992.232655
  • Filename
    232655