Serverless workflows have emerged in FaaS platforms to represent the operational structure of traditional applications. With latency propagation effects becoming increasingly prominent, step-wise resource tuning is required to address the end-to-end Quality-of-Service (QoS) requirements. Modern processors' allowance for fine-grained Dynamic Voltage and Frequency Scaling (DVFS), coupled with the intermittent nature of serverless workflows presents a unique opportunity to reduce power while meeting QoS. In this paper, we introduce a QoS-aware DVFS framework for serverless workflows. {\Omega}kypous regulates the end-to-end latency of serverless workflows by supplying the system with the Core/Uncore frequency combination that minimizes power consumption. With Uncore DVFS enriching the efficient power configurations space, we devise a grey-box model that accurately projects functions' execution latency and power, to the applied Core and Uncore frequency combination. To the best of our knowledge, {\Omega}kypous is the first work that leverages Core and Uncore DVFS as an integral part of serverless workflows. Our evaluation on the analyzed Azure Trace, against state-of-the-art (SotA) power managers, demonstrates a power consumption reduction of 20\% while minimizing QoS violations.

翻译：无服务器工作流已在函数即服务平台中兴起，用以表征传统应用程序的运算结构。随着延迟传播效应日益显著，需要采用分步式资源调优来满足端到端的服务质量要求。现代处理器支持细粒度动态电压与频率调频，结合无服务器工作流的间歇性特征，为在满足服务质量的同时降低功耗提供了独特机遇。本文提出一种面向无服务器工作流的服务质量感知型动态电压与频率调频框架。{\Omega}kypous 通过向系统提供能够最小化功耗的核心/非核心频率组合，实现对无服务器工作流端到端延迟的调控。借助非核心动态电压与频率调频对高效功耗配置空间的扩展，我们设计了一个灰盒模型，能够根据所采用的核心与非核心频率组合，精确预测函数的执行延迟与功耗。据我们所知，{\Omega}kypous 是首个将核心与非核心动态电压与频率调频作为无服务器工作流有机组成部分的研究。基于对Azure追踪数据的评估，与现有先进功耗管理器相比，本框架在将服务质量违规最小化的同时实现了20%的功耗降低。