The Impact of Under-Estimated Length of Jobs on EASY-Backfill Scheduling

The issue of under-estimated length of jobs (parallel applications) on backfill-based scheduling is ignored in the current literature because users want to avoid their jobs to be killed when the requested time expires. Therefore, users prefer to over-estimate the length of their jobs. This paper sho...

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Bibliographic Details
Main Authors: Wong, A.K.L., Goscinski, A.M.
Format: Conference Proceeding
Language:English
Subjects:
Batch production systems
Clustering algorithms
Computer Clusters
Degradation
Delay effects
Delay estimation
EASY-Backfill Scheduling
Information technology
Linux
Parallel Jobs
Processor scheduling
Scheduling algorithm
Throughput
Under-Estimation
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Summary:The issue of under-estimated length of jobs (parallel applications) on backfill-based scheduling is ignored in the current literature because users want to avoid their jobs to be killed when the requested time expires. Therefore, users prefer to over-estimate the length of their jobs. This paper shows the impact of underestimated length of jobs on their execution performance in an EASY-backfill scheduling-based system. We have developed a batch job scheduler for Linux clusters that implements an enhanced EASY- backfilling algorithm in such a way that a job with an under-estimated execution time would not be killed unless it would delay other jobs. We have carried out performance evaluation by scheduling static workloads of well known MPI parallel applications on a real cluster. Our results show that most of the jobs do not have to be aborted even though their job lengths are under-estimated whereas the slowdown of jobs and the throughput of the system are only slightly degraded.
ISSN:1066-6192
2377-5750
DOI:10.1109/PDP.2008.53