首页> 外文会议>Proceedings of the 2010 11th IEEE/ACM International Conference on Grid Computing >Accurate energy accounting for shared virtualized environments using PMC-based power modeling techniques
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Accurate energy accounting for shared virtualized environments using PMC-based power modeling techniques

机译:使用基于PMC的功率建模技术对共享的虚拟环境进行准确的能源核算

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Virtualized infrastructure providers demand new methods to increase the accuracy of the accounting models used to charge their customers. Future data centers will be composed of many-core systems that will host a large number of virtual machines (VMs) each. While resource utilization accounting can be achieved with existing system tools, energy accounting is a complex task when per-VM granularity is the goal. In this paper, we propose a methodology that brings new opportunities to energy accounting by adding an unprecedented degree of accuracy on the per-VM measurements. We present a system -which leverages CPU and memory power models based in performance monitoring counters (PMCs)- to perform energy accounting in virtualized systems. The contribution of this paper is twofold. First, we show that PMC-based power modeling methods are still valid on virtualized environments. And second, we introduce a novel methodology for accounting of energy consumption in virtualized systems. In overall, the results for an Intel® Core™ 2 Duo show errors in energy estimations below the 5%. Such approach brings flexibility to the chargeback models used by service and infrastructure providers. For instance, we show that VMs executed during the same amount of time, present more than 20% differences in energy consumption even only taking into account the consumption of the CPU and the memory.
机译:虚拟化基础架构提供商需要新的方法来提高用于向客户收费的会计模型的准确性。未来的数据中心将由许多核心系统组成,每个核心系统将托管大量虚拟机(VM)。尽管可以使用现有的系统工具来实现资源利用率核算,但是当以每VM粒度为目标时,能耗核算是一项复杂的任务。在本文中,我们提出了一种方法,该方法通过为每VM测量增加前所未有的准确性为能源核算带来新的机会。我们提出了一种系统-利用基于性能监视计数器(PMC)的CPU和内存电源模型-在虚拟化系统中执行能源核算。本文的贡献是双重的。首先,我们证明基于PMC的功率建模方法在虚拟化环境中仍然有效。其次,我们介绍了一种用于虚拟化系统中能源消耗核算的新颖方法。总体而言,英特尔®酷睿™2双核处理器的结果表明能耗估算值低于5%。这种方法为服务和基础架构提供商使用的计费模型带来了灵活性。例如,我们展示了在相同的时间段内执行的虚拟机,即使仅考虑CPU和内存的消耗,其能耗也存在超过20%的差异。

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