Preprocessing of system monitoring data for workload analysis of HPC systems

Authors

DOI:

https://doi.org/10.26089/NumMet.v22r314

Keywords:

supercomputing, supercomputers, system monitoring data analysis, system monitoring data cleaning, system monitoring data reduction

Abstract

HPC systems are complex in architecture and contain millions of components. To ensure reliable operation and efficient output, functioning of most subsystems should be supervised. This is done on the basis of collected data from various logging and monitoring systems. This means that different data sources are used, and accordingly, data analysis can face multiple issues processing this data.

Some of the data subsets can be incorrect due to the malfunctioning of used sensors, monitoring system data aggregation errors, etc. This is why it is crucial to preprocess such monitoring data before analyzing it, taking into the consideration the analysis goals. The aim of this paper is, being based on the MSU HPC Center monitoring data, to propose an approach to data preprocessing of HPC monitoring systems, giving some real life examples of issues that may be faced, and recommendations for further analysis of similar datasets.

Author Biographies

M.I. Martyshov

D.A. Nikitenko

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Published

23-09-2021

How to Cite

Martyshov M.I., Nikitenko D.A. Preprocessing of System Monitoring Data for Workload Analysis of HPC Systems // Numerical Methods and Programming (Vychislitel’nye Metody i Programmirovanie). 2021. 22. 230-238. doi 10.26089/NumMet.v22r314

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Section

Parallel software tools and technologies

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