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
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