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WiseThrottling: a new asynchronous task scheduler for mitigating I/O bottleneck in large-scale datacenter servers

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Abstract

Datacenter servers are stepping into an era marked by powerful multi-/many-core processors. Severe problems such as I/O contentions in those large-scale platforms pose an unprecedented challenge. Prior studies primarily considered I/O bandwidth as a major performance bottleneck. However, our work reveals that in many cases the fundamental cause of I/O contentions is the inefficiency of OS schedulers. Particularly, the modern system is not aware of this fact and thus suffers from poor I/O performance, especially for datacenter servers. Based on our findings, we propose a new software-based scheduling approach, WiseThrottling, to reduce I/O contention. WiseThrottling performs asynchronous and self-adjustment scheduling for concurrent tasks. We evaluate our approach across a wide range of C/OpenMP/MapReduce workloads on a 64-core server in Dawning Cluster datacenter. The experimental results exhibit that WiseThrottling is effective for reducing the I/O bottleneck and it can improve the overall system performance by up to 207 %.

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Authors and Affiliations

  1. State Key Laboratory of Computer Architecture, ICT, CAS, Beijing, China

    Fang Lv, Lei Liu, Hui-min Cui, Lei Wang, Ying Liu & Xiao-bing Feng

  2. Department of Computer Science and Engineering, University of Minnesota at Twin-Cities, Minneapolis, MN, USA

    Pen-Chung Yew

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  1. Fang Lv
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  2. Lei Liu
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  3. Hui-min Cui
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  6. Xiao-bing Feng
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  7. Pen-Chung Yew
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Correspondence to Fang Lv.

Additional information

This research is supported by the National High Technology Research and Development Program of China under Grants No. 2012AA010902 and 2015AA011505; the NSFC under Grants No. 61202055, 61221062, 61303053, 61432016 and 61402445; and the National Basic Research Program of China under Grant No. 2011CB302504.

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Lv, F., Liu, L., Cui, Hm. et al. WiseThrottling: a new asynchronous task scheduler for mitigating I/O bottleneck in large-scale datacenter servers. J Supercomput 71, 3054–3093 (2015). https://doi.org/10.1007/s11227-015-1427-7

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