Abstract
As High Performance Computing (HPC) systems get closer to exascale performance, job dispatching strategies become critical for keeping system utilization high while keeping waiting times low for jobs competing for HPC system resources. In this paper, we take a data-driven approach and investigate whether better dispatching decisions can be made by transforming the log data produced by an HPC system into useful knowledge about its workload. In particular, we focus on job duration, develop a data-driven approach to job duration prediction, and analyze the effect of different prediction approaches in making dispatching decisions using a real workload dataset collected from Eurora, a hybrid HPC system. Experiments on various dispatching methods show promising results.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
