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Scheduling parallel jobs on multicore clusters using CPU oversubscription

Published: 01 June 2014 Publication History

Abstract

Job scheduling strategies in multiprocessing systems aim to minimize waiting times of jobs while satisfying user requirements in terms of number of execution units. However, the lack of flexibility in the requests leaves the scheduler a reduced margin of action for scheduling decisions. Many of such decisions consist on just moving ahead some specific jobs in the wait queue. In this work, we propose a job scheduling strategy that improves the overall performance and maximizes resource utilization by allowing jobs to adapt to variations in the load through CPU oversubscription and backfilling. The experimental evaluations include both real executions on multicore clusters and simulations of workload traces from real production systems. The results show that our strategy provides significant improvements over previous proposals like Gang Scheduling with Backfilling, especially in medium to high workloads with strong variations.

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Cited By

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  • (2019)Checkpoint/restart approaches for a thread-based MPI runtimeParallel Computing10.1016/j.parco.2019.02.00685:C(204-219)Online publication date: 1-Jul-2019
  • (2019)Task PackingJournal of Parallel and Distributed Computing10.1016/j.jpdc.2019.08.003134:C(37-49)Online publication date: 1-Dec-2019
  • (2015)Addressing characterization methods for memory contention aware co-schedulingThe Journal of Supercomputing10.1007/s11227-014-1374-871:4(1451-1483)Online publication date: 1-Apr-2015

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Information & Contributors

Information

Published In

cover image The Journal of Supercomputing
The Journal of Supercomputing  Volume 68, Issue 3
June 2014
629 pages

Publisher

Kluwer Academic Publishers

United States

Publication History

Published: 01 June 2014

Author Tags

  1. Application reconfiguration
  2. CPU oversubscription
  3. Job scheduling
  4. MPI
  5. Malleability
  6. Multicore clusters

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Cited By

View all
  • (2019)Checkpoint/restart approaches for a thread-based MPI runtimeParallel Computing10.1016/j.parco.2019.02.00685:C(204-219)Online publication date: 1-Jul-2019
  • (2019)Task PackingJournal of Parallel and Distributed Computing10.1016/j.jpdc.2019.08.003134:C(37-49)Online publication date: 1-Dec-2019
  • (2015)Addressing characterization methods for memory contention aware co-schedulingThe Journal of Supercomputing10.1007/s11227-014-1374-871:4(1451-1483)Online publication date: 1-Apr-2015

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