论文标题
智能瓦特:容器的自校准软件定义的功率计
SmartWatts: Self-Calibrating Software-Defined Power Meter for Containers
论文作者
论文摘要
对软件活动的细粒度监控是不可避免的,可以最大程度地提高数据中心的功率使用效率。特别是,实现容器的最佳安排需要部署软件定义的电源〜米,以超越硬件功率监控传感器的粒度,例如功率分配单元(PDU)或英特尔的运行平均功率限制(RAPL),以在软件范围的粒度〜容器粒度范围内提供功能估算的功率估算。但是,估计功耗的基础功率模型的定义仍然是一个漫长而脆弱的过程,并紧密耦合到主机机器。 为了克服这些局限性,本文介绍了智能瓦特:一种轻巧的功率监控系统,该系统采用在线校准来自动调整CPU和DRAM功率模型,以最大程度地提高容器运行时电源估算的准确性。与最先进的技术不同,智能瓦特不需要任何先验培训阶段或硬件设备来配置电源模型,因此可以免费部署在包括最新电源优化在内的各种机器上。
Fine-grained power monitoring of software activities becomes unavoidable to maximize the power usage efficiency of data centers. In particular, achieving an optimal scheduling of containers requires the deployment of software-defined power~meters to go beyond the granularity of hardware power monitoring sensors, such as Power Distribution Units (PDU) or Intel's Running Average Power Limit (RAPL), to deliver power estimations of activities at the granularity of software~containers. However, the definition of the underlying power models that estimate the power consumption remains a long and fragile process that is tightly coupled to the host machine. To overcome these limitations, this paper introduces SmartWatts: a lightweight power monitoring system that adopts online calibration to automatically adjust the CPU and DRAM power models in order to maximize the accuracy of runtime power estimations of containers. Unlike state-of-the-art techniques, SmartWatts does not require any a priori training phase or hardware equipment to configure the power models and can therefore be deployed on a wide range of machines including the latest power optimizations, at no cost.