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XeMPUPiL: Towards a Performance-aware Power Capping Orchestrator for the Xen Hypervisor.

機(jī)譯：XeMPUPiL：面向Xen Hypervisor的性能感知功率上限協(xié)調(diào)器。

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摘要

In the era of Cloud Computing, services and computational power are provided in an as a Service (aaS) fashion, reducing the need of buying, building and maintaining proprietary systems. In the last few years, many services moved from being proprietary to the as a Service paradigm: this, together with virtualization techniques, allows multiple applications to easily run on the same machine. However, the burden of costs optimization is left to the Cloud Provider, that still faces the problem of consolidating multiple workloads on the same infrastructure. As power consumption remains one of the most impacting costs of any digital system, several approaches have been explored in literature to cope with power caps, trying to maximize the performance of the hosted applications. These approaches were usually classified in two macro families, the software and hardware techniques. The former family is typically adopted when the goal consists in minimizing the power consumption, while providing the best possible performance for the running workloads. This approaches are characterized by obtaining high efficiency, but lacks in timeliness. Instead, the latter family is exploited when there are strict constraints regarding the power budget and the main goal consists in respecting them, while trying to maximize the performance of the running applications. In this case, the main characteristic consists in respecting the concept of timeliness, totally neglecting the concept of efficiency. In this thesis, we present results and opportunities obtained towards a performance-aware power capping orchestrator for the Xen hypervisor, that exploit a novel emerging family introduced in the literature: the hybrid approach. This fresh set of techniques aims to adopt synergically and concurrently both hardware and software approaches in order to achieve at the same time the concept of efficiency and timeliness, masking the weak spots of the two common approaches when adopter alone. The proposed solution, called XeMPUPiL, uses the Intel RAPL hardware interface to set a strict limit on the processor's power consumption, while a software-level ODA control loop performs an exploration of the available resource allocations to find the most power efficient one for the running workload. We show how XeMPUPiL is able to achieve higher performance under different power caps for almost all the different classes of benchmarks analyzed (e.g., CPU-, memory- and IO-bound).
機(jī)譯：在云計(jì)算時(shí)代，服務(wù)和計(jì)算能力以即服務(wù)（aaS）的方式提供，從而減少了購(gòu)買，構(gòu)建和維護(hù)專有系統(tǒng)的需求。在過去的幾年中，許多服務(wù)從專有模式轉(zhuǎn)變?yōu)椤胺?wù)即服務(wù)”范例：結(jié)合虛擬化技術(shù)，這使得多個(gè)應(yīng)用程序可以輕松地在同一臺(tái)計(jì)算機(jī)上運(yùn)行。但是，成本優(yōu)化的重?fù)?dān)留給了云提供商，該提供商仍面臨在同一基礎(chǔ)架構(gòu)上整合多個(gè)工作負(fù)載的問題。由于功耗仍然是任何數(shù)字系統(tǒng)中影響最大的成本之一，因此在文獻(xiàn)中已經(jīng)探索了幾種方法來應(yīng)對(duì)功率上限，從而試圖最大化托管應(yīng)用程序的性能。這些方法通常分為兩個(gè)宏系列，即軟件和硬件技術(shù)。當(dāng)目標(biāo)是最大程度地降低功耗，同時(shí)為運(yùn)行的工作負(fù)載提供最佳性能時(shí)，通常采用前者系列。該方法的特征在于獲得高效率，但是缺乏及時(shí)性。取而代之的是，在對(duì)功率預(yù)算有嚴(yán)格限制且主要目標(biāo)在于尊重它們的同時(shí)，試圖使正在運(yùn)行的應(yīng)用程序的性能最大化，從而利用后者。在這種情況下，主要特征在于尊重及時(shí)性的概念，而完全忽略了效率的概念。在本文中，我們介紹了Xen虛擬機(jī)管理程序針對(duì)性能感知的功率上限協(xié)調(diào)器的成果和機(jī)遇，該性能開發(fā)器利用了文獻(xiàn)中介紹的新型新興家族：混合方法。這套新技術(shù)旨在同時(shí)并發(fā)地采用硬件和軟件方法，以便同時(shí)實(shí)現(xiàn)效率和及時(shí)性的概念，從而掩蓋了僅采用者時(shí)兩種常見方法的弱點(diǎn)。提議的解決方案稱為XeMPUPiL，它使用Intel RAPL硬件接口對(duì)處理器的功耗設(shè)置了嚴(yán)格的限制，而軟件級(jí)的ODA控制循環(huán)對(duì)可用的資源分配進(jìn)行了探索，以找到最節(jié)能的運(yùn)行資源。工作量。我們展示了XeMPUPiL如何在幾乎所有不同類別的基準(zhǔn)測(cè)試（例如CPU限制，內(nèi)存限制和IO限制）下在不同功率上限下實(shí)現(xiàn)更高的性能。

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  • 作者

    Arnaboldi, Marco.;

  • 作者單位

    University of Illinois at Chicago.;

  • 授予單位 University of Illinois at Chicago.;
  • 學(xué)科 Computer science.
  • 學(xué)位 M.S.
  • 年度 2017
  • 頁碼 90 p.
  • 總頁數(shù) 90
  • 原文格式 PDF
  • 正文語種 eng
  • 中圖分類 遙感技術(shù);
  • 關(guān)鍵詞

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