Altruistic Scheduling in Multi-Resource Clusters


Robert Grandl, University of Wisconsin—Madison; Mosharaf Chowdhury, University of Michigan; Aditya Akella, University of Wisconsin—Madison; Ganesh Ananthanarayanan, Microsoft


Given the well-known tradeoffs between fairness, performance, and efficiency, modern cluster schedulers often prefer instantaneous fairness as their primary objective to ensure performance isolation between users and groups. However, instantaneous, short-term convergence to fairness often does not result in noticeable long-term benefits. Instead, we propose an altruistic, long-term approach, CARBYNE, where jobs yield fractions of their allocated resources without impacting their own completion times. We show that leftover resources collected via altruisms of many jobs can then be rescheduled to further secondary goals such as application-level performance and cluster efficiency without impacting performance isolation. Deployments and large-scale simulations show that CARBYNE closely approximates the state-of- the-art solutions (e.g., DRF) in terms of performance isolation, while providing 1:26x better efficiency and 1:59x lower average job completion time.

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@inproceedings {199388,
author = {Robert Grandl and Mosharaf Chowdhury and Aditya Akella and Ganesh Ananthanarayanan},
title = {Altruistic Scheduling in {Multi-Resource} Clusters},
booktitle = {12th USENIX Symposium on Operating Systems Design and Implementation (OSDI 16)},
year = {2016},
isbn = {978-1-931971-33-1},
address = {Savannah, GA},
pages = {65--80},
url = {},
publisher = {USENIX Association},
month = nov,

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