D.A.V.I.D.E.大数据驱动的精细电源和性能监控支持

Andrea Bartolini, Andrea Borghesi, Antonio Libri, Francesco Beneventi, D. Gregori, S. Tinti, Cosimo Gianfreda, Piero Altoe
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引用次数: 22

摘要

在向百亿亿次超级计算系统的竞争中,系统面临着限制系统效率的重要挑战。总而言之,由于Dennard的扩展结束而导致的电力和能源消耗开始显示出它们对限制超级计算机峰值性能和成本效益的影响。在本文中,我们提出并描述了一种基于一组硬件和软件扩展的新方法,用于细粒度监测功率并将其聚合以实现快速分析和可视化。我们提出了一种使用MQTT通信层、NoSQL数据库、细粒度监控和未来AI技术来测量和控制功率和性能的交钥匙系统。这种方法被显示为D.A.V.I.D.E.超级计算机的一个综合特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The D.A.V.I.D.E. big-data-powered fine-grain power and performance monitoring support
On the race toward exascale supercomputing systems are facing important challenges which limit the efficiency of the system. Among all, power and energy consumption fueled by the end of Dennard's scaling start to show their impact on limiting supercomputers peak performance and cost effectiveness. In this paper we present and describe a new methodology based on a set of HW and SW extensions for fine-grain monitoring of power and aggregation of them for fast analysis and visualization. We propose a turn-key system which uses MQTT communication layer, NoSQL database, fine grain monitoring and in future AI technology to measure and control power and performance. This methodology is shown as an integrated feature of the D.A.V.I.D.E. supercomputing machine.
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