Yawn:数据中心应用程序的CPU空闲状态调控器

Erfan Sharafzadeh, Seyed Alireza Sanaee Kohroudi, Esmail Asyabi, M. Sharifi
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引用次数: 9

摘要

空闲状态调控器部分关闭空闲cpu,允许它们进入称为空闲状态的状态以节省电力。但是,退出这些空闲状态会对任务的执行造成延迟,并加剧尾部延迟。Menu是Linux默认的空闲状态调控器,它根据历史数据和磁盘I/O信息预测空闲时间,以选择适当的空闲状态。我们的实验表明,Menu可以节省电力,但代价是牺牲尾部延迟,这使得它不适合承载对延迟敏感的应用程序的数据中心。在本文中,我们提出了Yawn的初始设计,这是一个空闲状态调节器,旨在减少尾部延迟而不牺牲功率。Yawn利用在线机器学习技术,根据从影响空闲的所有参数(包括网络I/O)收集的信息来预测空闲时间,从而产生更准确的预测,从而减少响应时间。初步的基准测试结果表明,Yawn将Memcached请求的第99个延迟百分位数减少了40%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Yawn: A CPU Idle-state Governor for Datacenter Applications
Idle-state governors partially turn off idle CPUs, allowing them to go to states known as idle-states to save power. Exiting from these idle-sates, however, imposes delays on the execution of tasks and aggravates tail latency. Menu, the default idle-state governor of Linux, predicts periods of idleness based on the historical data and the disk I/O information to choose proper idle-sates. Our experiments show that Menu can save power, but at the cost of sacrificing tail latency, making Menu an inappropriate governor for data centers that host latency-sensitive applications. In this paper, we present the initial design of Yawn, an idle-state governor that aims to mitigate tail latency without sacrificing power. Yawn leverages online machine learning techniques to predict the idle periods based on information gathered from all parameters affecting idleness, including network I/O, resulting in more accurate predictions, which in turn leads to reduced response times. Preliminary benchmarking results demonstrate that Yawn reduces the 99th latency percentile of Memcached requests by up to 40%.
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