Real-time I/O-monitoring of hpc applications with SIOX, elasticsearch, grafana and FUSE

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Abstract

The starting point for our work was a demand for an overview of application’s I/O behavior, that provides information about the usage of our HPC “Mistral”. We suspect that some applications are running using inefficient I/O patterns, and probably, are wasting a significant amount of machine hours. To tackle the problem, we focus on detection of poor I/O performance, identification of these applications, and description of I/O behavior. Instead of gathering I/O statistics from global system variables, like many other monitoring tools do, in our approach statistics come directly from I/O interfaces POSIX, MPI, HDF5 and NetCDF. For interception of I/O calls we use an instrumentation library that is dynamically linked with LD_PRELOAD at program startup. The HPC on-line monitoring framework is built on top of open source software: Grafana, SIOX, Elasticsearch and FUSE. This framework collects I/O statistics from applications and mount points. The latter is used for non-intrusive monitoring of virtual memory allocated with mmap(), i.e., no code adaption is necessary. The framework is evaluated showing its effectiveness and critically discussed.

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APA

Betke, E., & Kunkel, J. (2017). Real-time I/O-monitoring of hpc applications with SIOX, elasticsearch, grafana and FUSE. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10524 LNCS, pp. 174–186). Springer Verlag. https://doi.org/10.1007/978-3-319-67630-2_15

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