@inproceedings{194a598cfb4947bf84e8e5bfcf646082,
title = "Towards a model to estimate the reliability of large-scale hybrid supercomputers",
abstract = "Supercomputers stand as a fundamental tool for developing our understanding of the universe. State-of-the-art scientific simulations, big data analyses, and machine learning executions require high performance computing platforms. Such infrastructures have been growing lately with the addition of thousands of newly designed components, calling their resiliency into question. It is crucial to solidify our knowledge on the way supercomputers fail. Other recent studies have highlighted the importance of characterizing failures on supercomputers. This paper aims at modelling component failures of a supercomputer based on Mixed Weibull distributions. The model is built using a real-life multi-year failure record from a leadership-class supercomputer. Using several key observations from the data, we designed an analytical model that is robust enough to represent each of the main components of supercomputers, yet it is flexible enough to alter the composition of the machine and be able to predict resilience of future or hypothetical systems.",
keywords = "Failure analysis, Failure modelling, Fault tolerance, Resilience",
author = "Elvis Rojas and Esteban Meneses and Terry Jones and Don Maxwell",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020.; 26th International European Conference on Parallel and Distributed Computing, Euro-Par 2020 ; Conference date: 24-08-2020 Through 28-08-2020",
year = "2020",
doi = "10.1007/978-3-030-57675-2_3",
language = "Ingl{\'e}s",
isbn = "9783030576745",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "37--51",
editor = "Maciej Malawski and Krzysztof Rzadca",
booktitle = "Euro-Par 2020",
}