Backfilling with Fairness and Slack for Parallel Job Scheduling

Abstract

Parallel job scheduling typically combines a basic policy like FCFS with backfilling, i.e. moving jobs to an earlier than their regular scheduling position if they do not delay the jobs ahead in the queue according to the rules of the backfilling approach applied. Commonly used are conservative and easy backfilling which either have worse response times but better predictability or better response times and poor predictability. The paper proposes a relaxation of conservative backfilling by permitting to shift jobs within certain constraints to backfill more jobs and reduce fragmentation and subsequently obtain better response times. At the same time, deviation from fairness is kept low and predictability remains high. The results of the experimentation evaluation show that the goals are met, with response-time performance lying as expected between conservative and easy backfilling.