Speculation-aware Cluster Scheduling

Abstract

Stragglers are a crucial roadblock to achieving predictable performance in today's clusters. Speculation has been widely adopted in order to mitigate the impact of stragglers; however speculation mechanisms are designed and operated independently of job scheduling when, in fact, scheduling a speculative copy of a task has a direct impact on the resources available for other jobs. In this work, based on a simple model and its analysis, we design Hopper, a job scheduler that is speculation-aware, i.e., that integrates the tradeoffs associated with speculation into job scheduling decisions.

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