Abstract
This work looks at analyzing I/O traffic of users' jobs on a HPC machine for a period of time. Monitoring tools are collecting the data in a continuous basis on the HPC system. We looked at aggregate I/O data usage patterns of users' jobs on the system both on the parallel shared Lustre file system and the node-local SSDs. Data mining tools are then applied to analyze the I/O usage pattern data in an attempt to tie the data to particular codes that produced those I/O behaviors from users' jobs.
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CITATION STYLE
Nazrul, S. S., Huang, C., Tatineni, M., Wolter, N., Mishin, D., Cooper, T., & Majumdar, A. (2019). Analyzing IO usage patterns of user jobs to improve overall HPC system efficiency. In Communications in Computer and Information Science (Vol. 964, pp. 91–102). Springer Verlag. https://doi.org/10.1007/978-981-13-7729-7_7
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