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UID:submissions.supercomputing.org_SC20_sess146_pap286@linklings.com
SUMMARY:Waiting Game: Optimally Provisioning Fixed Resources for Cloud-Ena
 bled Schedulers
DESCRIPTION:Paper\n\nWaiting Game: Optimally Provisioning Fixed Resources 
 for Cloud-Enabled Schedulers\n\nAmbati, Bashir, Irwin, Shenoy\n\nWhile clo
 ud platforms enable users to rent computing resources on demand to execute
  their jobs, buying fixed resources is still much cheaper than renting if 
 utilization is high. Optimizing cloud costs requires users to determine ho
 w many fixed resources to buy versus rent based on their workload. In this
  paper, we introduce the concept of a waiting policy for cloud-enabled sch
 edulers, the dual of a scheduling policy, and show that the optimal cost d
 epends on this policy. We define multiple waiting policies and develop sim
 ple analytical models to reveal the trade-off among resource provisioning,
  cost and job waiting time. We evaluate the impact of these waiting polici
 es on a year-long production batch workload consisting of 14m jobs run on 
 a 14.3k-core cluster, and show that a compound waiting policy decreases th
 e cost (by 5%) and the mean job waiting time (by 7x) compared to the curre
 nt cluster.\n\nTag: Cloud and Distributed Computing, Containers, Machine L
 earning, Deep Learning and Artificial Intelligence, Resource Management an
 d Scheduling\n\nRegistration Category: Tech Program Reg Pass\n\nAward Fina
 list: Best Paper Finalist, Best Student Paper Finalists
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