The D.A.V.I.D.E. big-data-powered fine-grain power and performance monitoring support.

CF(2018)

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摘要
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 Dennardu0027s 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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关键词
Big Data, High Performance Computing, Fine-Grain Power and Performance Monitoring, AMESTER, BeagleBone Black
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