Presentation
HPC Andragogy: Automating Batch Scheduler Feedback
DescriptionThis paper proposes a monitoring system that emails feedback to users about submitted jobs and has the capability to stop and resubmit jobs to a batch scheduler. The proposed system has been implemented for a small supercomputing environment with a mix of high-performance and high-throughput computing jobs. User feedback includes alerts for over- and under-utilization of CPU and physical memory.
This paper also discusses how predefined system thresholds were chosen, and proposes three algorithms: one algorithm for the proposed monitoring system and two algorithms for the prediction of CPU and physical memory utilization. The latter algorithms are based on users' input of the identification string (job ID) of a similar job that should have finished execution without errors. Lastly, a git repository is shared to make the code accessible for review.
This paper also discusses how predefined system thresholds were chosen, and proposes three algorithms: one algorithm for the proposed monitoring system and two algorithms for the prediction of CPU and physical memory utilization. The latter algorithms are based on users' input of the identification string (job ID) of a similar job that should have finished execution without errors. Lastly, a git repository is shared to make the code accessible for review.
Event Type
Workshop
TimeMonday, 18 November 20243:30pm - 3:55pm EST
LocationB308
Distributed Computing
Education
Emerging Technologies
Archive
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