CPI2:共享计算集群的CPU性能隔离

Xiao Zhang, Eric Tune, R. Hagmann, Rohit Jnagal, Vrigo Gokhale, J. Wilkes
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引用次数: 324

摘要

性能隔离是云计算中的一个关键挑战。不幸的是,Linux对共享资源(如处理器缓存和内存总线)中的性能干扰几乎没有防御措施,因此云中的应用程序可能会遇到由其他程序的行为引起的不可预测的性能。我们的解决方案CPI2使用硬件性能计数器获得的每指令周期(CPI)数据来识别问题,选择可能的肇事者,然后有选择地限制它们,以便受害者可以恢复到预期的行为。它通过聚合来自同一工作中多个任务的数据,自动学习正常和异常行为。我们已经在所有谷歌的共享计算集群上推出了CPI2。本文介绍了导致我们得出这一结果的分析,包括案例研究和对其解决实际生产问题的能力的大规模评估。
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CPI2: CPU performance isolation for shared compute clusters
Performance isolation is a key challenge in cloud computing. Unfortunately, Linux has few defenses against performance interference in shared resources such as processor caches and memory buses, so applications in a cloud can experience unpredictable performance caused by other programs' behavior. Our solution, CPI2, uses cycles-per-instruction (CPI) data obtained by hardware performance counters to identify problems, select the likely perpetrators, and then optionally throttle them so that the victims can return to their expected behavior. It automatically learns normal and anomalous behaviors by aggregating data from multiple tasks in the same job. We have rolled out CPI2 to all of Google's shared compute clusters. The paper presents the analysis that lead us to that outcome, including both case studies and a large-scale evaluation of its ability to solve real production issues.
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