Аннотация
Having information such as an estimation of the processing time or possibility of system outage (abnormal behaviour) helps to assist to monitor system performance and to predict its next state. The current cyber-infrastructure of the ATLAS Production System presents computing conditions in which contention for resources among high-priority data analyses happens routinely, that might lead to significant workload and data handling interruptions. The lack of the possibility to monitor and to predict the behaviour of the analysis process (its duration) and system's state itself provides motivation for a focus on design of the built-in situational awareness analytic tools.
| Язык оригинала | Английский |
|---|---|
| Номер статьи | 032051 |
| Журнал | Journal of Physics: Conference Series |
| Том | 1085 |
| Номер выпуска | 3 |
| DOI | |
| Состояние | Опубликовано - 18 окт 2018 |
| Опубликовано для внешнего пользования | Да |
| Событие | 18th International Workshop on Advanced Computing and Analysis Techniques in Physics Research, ACAT 2017 - Seattle, Соединенные Штаты Америки Продолжительность: 21 авг 2017 → 25 авг 2017 |
ASJC Scopus subject areas
- Physics and Astronomy(all)
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Цитировать
Barreiro Megino, F. H., Borodin, M., Golubkov, D., Grigorieva, M., Gubin, M., Klimentov, A., Korchuganova, T., Maeno, T., Padolski, S., & Titov, M. (2018). Predictive analytics tools to adjust and monitor performance metrics for the ATLAS Production System. Journal of Physics: Conference Series, 1085(3), [032051]. https://doi.org/10.1088/1742-6596/1085/3/032051