{"id":323396,"date":"2016-11-16T20:38:34","date_gmt":"2016-11-17T04:38:34","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=323396"},"modified":"2018-10-16T20:18:50","modified_gmt":"2018-10-17T03:18:50","slug":"speculation-aware-cluster-scheduling","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/speculation-aware-cluster-scheduling\/","title":{"rendered":"Speculation-aware Cluster Scheduling"},"content":{"rendered":"

Stragglers are a crucial roadblock to achieving predictable performance in today\u2019s clusters. Speculation has been widelyadopted 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.<\/p>\n","protected":false},"excerpt":{"rendered":"

Stragglers are a crucial roadblock to achieving predictable performance in today\u2019s clusters. Speculation has been widelyadopted 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 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