用恒温器对机架式服务器的热概况进行建模和管理

Jeonghwan Choi, Youngjae Kim, A. Sivasubramaniam, J. Srebric, Qian Wang, Joonwon Lee
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引用次数: 59

摘要

高功率密度和高工作温度对元件故障率的影响是温度感知计算的关键驱动因素。计算机架构师和系统软件设计师需要了解他们的建议的热后果,并开发降低操作温度的技术,以减少瞬态和永久组件故障。用于理解设计的温度影响的工具主要局限于研究包装和冷却机制的工业,很少有学术研究人员可以使用这些工具集。开发这样的工具是一项艰巨的任务,因为它通常需要跨越架构、系统软件、热力学和冷却系统的跨领域专业知识。认识到需要这样的工具,已经有了在微体系结构级别上对处理器温度建模的工作,这些工作可以很容易地被计算机架构师用于处理器设计。然而,在学术/研究社区中,缺乏这样的工具来进行处理器之外的架构/系统研究——服务器箱、机架甚至机房。本文介绍了一种详细的基于计算流体力学的三维热建模工具,称为ThermoStat,用于机架式服务器系统。使用这个工具,我们建立了一个20(每个节点都有双至强处理器)节点机架服务器系统的模型,并在服务器/机架的不同点使用超过30个温度传感器测量来验证它。我们使用该工具进行了几个实验,以显示不同的负载条件如何影响热剖面,并说明该工具如何帮助设计动态热管理技术
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling and Managing Thermal Profiles of Rack-mounted Servers with ThermoStat
High power densities and the implications of high operating temperatures on the failure rates of components are key driving factors of temperature-aware computing. Computer architects and system software designers need to understand the thermal consequences of their proposals, and develop techniques to lower operating temperatures to reduce both transient and permanent component failures. Tools for understanding temperature ramifications of designs have been mainly restricted to industry for studying packaging and cooling mechanisms, with little access to such toolsets for academic researchers. Developing such tools is an arduous task since it usually requires cross-cutting areas of expertise spanning architecture, systems software, thermodynamics, and cooling systems. Recognizing the need for such tools, there has been work on modeling temperatures of processors at the micro-architectural level which can be easily understood and employed by computer architects for processor designs. However, there is a dearth of such tools in the academic/research community for undertaking architectural/systems studies beyond a processor - a server box, rack or even a machine room. This paper presents a detailed 3-dimensional computational fluid dynamics based thermal modeling tool, called ThermoStat, for rack-mounted server systems. Using this tool, we model a 20 (each with dual Xeon processors) node rack-mounted server system, and validate it with over 30 temperature sensor measurements at different points in the servers/rack. We conduct several experiments with this tool to show how different load conditions affect the thermal profile, and also illustrate how this tool can help design dynamic thermal management techniques
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