Multiple-queue backfilling scheduling with priorities and reservations for parallel systems
ACM SIGMETRICS Performance Evaluation Review
Multiple-Queue Backfilling Scheduling with Priorities and Reservations for Parallel Systems
JSSPP '02 Revised Papers from the 8th International Workshop on Job Scheduling Strategies for Parallel Processing
Coscheduling in Clusters: Is It a Viable Alternative?
Proceedings of the 2004 ACM/IEEE conference on Supercomputing
Self-Adaptive Scheduler Parameterization via Online Simulation
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
A runtime resolution scheme for priority boost conflict in implicit coscheduling
The Journal of Supercomputing
A comprehensive performance and energy consumption analysis of scheduling alternatives in clusters
The Journal of Supercomputing
Selective preemption strategies for parallel job scheduling
International Journal of High Performance Computing and Networking
The hybrid scheduling framework for virtual machine systems
Proceedings of the 2009 ACM SIGPLAN/SIGOPS international conference on Virtual execution environments
Advance reservation policies for workflows
JSSPP'06 Proceedings of the 12th international conference on Job scheduling strategies for parallel processing
Optimal job packing, a backfill scheduling optimization for a cluster of workstations
The Journal of Supercomputing
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We focus on non-FCFS job scheduling policies for parallel systems that allow jobs to backfill, i.e., to move ahead in the queue, given that they do not delay certain previously submitted jobs. Consistent with commercial schedulers that maintain multiple queues where jobs are assigned according to the user-estimated duration, we propose a self-adapting backfilling policy that maintains multiple job queues to separate short from long jobs. The proposed policy adjusts its configuration parameters by continuously monitoring the system and quickly reacting to sudden fluctuations in the workload arrival pattern and/or severe changes in resource demands. Detailed performance comparisons via simulation using actual Supercomputing traces from the Parallel Workload Archive indicate that the proposed policy consistently outperforms traditional backfilling.