SmartWatts：面向容器的自校准软件定义功率计
SmartWatts: Self-Calibrating Software-Defined Power Meter for Containers
AI总结：
本文提出轻量级功率监控系统 SmartWatts，通过在线校准自动调整 CPU 和 DRAM 功率模型，无需先验训练或硬件设备即可零成本部署，实现高精度的容器运行时功率估算。
摘要：
为了最大化数据中心的能效，对软件活动进行细粒度功率监控变得不可避免。特别是，实现容器的最优调度需要部署软件定义功率计，以超越 Power Distribution Units (PDU) 或 Intel 的 Running Average Power Limit (RAPL) 等硬件功率监控传感器的粒度，从而提供软件容器粒度上的活动功率估算。然而，定义用于估算功耗的底层功率模型仍是一个漫长且脆弱的过程，且与主机紧密耦合。为了克服这些限制，本文提出了 SmartWatts：一个轻量级功率监控系统，它采用在线校准自动调整 CPU 和 DRAM 功率模型，以最大化容器运行时功率估算的准确性。与最先进的技术不同，SmartWatts 不需要任何先验训练阶段或硬件设备来配置功率模型，因此可以零成本部署在包括最新功率优化在内的广泛机器上。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
