DocumentCode :
2385270
Title :
Dynamic Multi-Resource Monitoring for Predictive Job Scheduling with ScoPro
Author :
Sodan, Angela C. ; Liu, Lun
Author_Institution :
Dept. of Comput. Sci., Windsor Univ., Ont.
fYear :
2005
fDate :
Sept. 2005
Firstpage :
1
Lastpage :
2
Abstract :
Modern job schedulers move towards applying dynamic approaches like time sharing or adaptive resource allocation to accommodate grid jobs or to better utilize local resources. Also, the resources may be heterogeneous and a proper distribution of the application´s workload be hard to estimate. Our ScoPro monitoring tool permits to obtain and to store resource-related behavior information for parallel applications. This information is used to create an application signature for predictive use in future runs and to dynamically check competition under time-shared execution and imbalances of workload on heterogeneous resources. ScoPro is applicable to production runs on standard clusters. As main innovative contributions ScoPro can be triggered by job-scheduling events, can monitor several coscheduled jobs concurrently for accurate prediction of slowdowns, and performs realtime short-period measurements with low intrusion during the monitoring, while avoiding any intrusion overhead for the non-monitored part of the job execution
Keywords :
parallel processing; resource allocation; ScoPro monitoring tool; adaptive resource allocation; parallel application; predictive job scheduling; Adaptive scheduling; Computer science; Computerized monitoring; Dynamic scheduling; Modems; Performance evaluation; Processor scheduling; Production; Resource management; Time sharing computer systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cluster Computing, 2005. IEEE International
Conference_Location :
Burlington, MA
ISSN :
1552-5244
Print_ISBN :
0-7803-9486-0
Electronic_ISBN :
1552-5244
Type :
conf
DOI :
10.1109/CLUSTR.2005.347013
Filename :
4154141
Link To Document :
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