Predictive analytics tools to adjust and monitor performance metrics for the ATLAS Production Systemстатья
Информация о цитировании статьи получена из
Web of Science,
Scopus
Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 26 июня 2019 г.
Авторы:
Barreiro Megino F.H.,
Borodin M.,
Golubkov D.,
Grigorieva M.,
Gubin M.,
Klimentov A.,
Korchuganova T.,
Maeno T.,
Padolski S.,
Titov M.
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.