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
Link To Document :
بازگشت