Monitoring and Analysis of Power Consumption on HPC Clusters using XDMoD
Monitoring and Analysis of Power Consumption on HPC Clusters using XDMoD
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DOI：
10.1145/3311790.3396624
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发表时间：
2020-07
期刊：
影响因子：
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通讯作者：
Joseph P. White;Martins D. Innus;R. L. Deleon;Matthew D. Jones;T. Furlani
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作者：
Joseph P. White;Martins D. Innus;R. L. Deleon;Matthew D. Jones;T. Furlani
作为NSF资助的XMS项目的一部分，我们正在开发用于HPC基础设施审计和分析的工具和技术。这包括一套工具，用于根据从计算节点收集的性能指标分析HPC作业。虽然对用户来说可能并不突出，但HPC系统的能耗是维护成本的重要部分，并且占系统计算成本的很大一部分。我们为开源XDMoD工具链添加了对能源使用分析的支持。这允许HPC中心直接向HPC利益相关者提供有关功耗的信息。这包括为最终用户提供有关其工作的能源使用信息，以及提供数据，以允许HPC中心工作人员分析系统的能源使用如何与其他系统参数相关。我们解释了如何将能量指标添加到XDMoD中，并描述了我们在1400节点学术HPC集群中克服的问题。我们提出了一个分析14个月的数据收集的真实的工作的集群。我们对数据进行了机器学习分析，并展示了能源使用与其他系统性能指标的关系。
As part of the NSF funded XMS project we are developing tools and techniques for the audit and analysis of HPC infrastructure. This includes a suite of tools for the analysis of HPC jobs based on performance metrics collected from compute nodes. Although it may not be salient to the user, the energy consumption of an HPC system is an important part of the cost of maintenance and contributes a substantial fraction of the cost of calculations done with the system. We added support for energy usage analysis to the open-source XDMoD tool chain. This allows HPC centers to provide information directly to HPC stakeholders about the power consumption. This includes providing end users with energy usage information about their jobs as well as providing data to allow HPC center staff to analyze how the energy usage of the system is related to other system parameters. We explain how energy metrics were added to XDMoD and describe the issues we overcame in instrumenting a 1400 node academic HPC cluster. We present an analysis of 14 months of data collected on real jobs on the cluster. We performed a machine learning analysis of the data and show how energy usage is related to other system performance metrics.