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Deep Analysis of Job State Statistics on Lomonosov-2 Supercomputerстатья
Статья опубликована в журнале из списка RSCI Web of Science
Информация о цитировании статьи получена из
Scopus
Статья опубликована в журнале из списка Web of Science и/или Scopus
Дата последнего поиска статьи во внешних источниках: 5 декабря 2018 г.
- Авторы: Dmitry Nikitenko, Vadim Voevodin, Sergey Zhumatiy
- Журнал: Supercomputing Frontiers and Innovations
- Том: 5
- Номер: 2
- Год издания: 2018
- Первая страница: 4
- Последняя страница: 10
- DOI: 10.14529/jsfi180201
- Аннотация: It is a common knowledge that the increasingly growing capabilities of HPC systems are always limited by a number of efficiency related issues. The reasons can be very different: hardware failures, incorrect job scheduling, peculiarities of algorithm, chosen programming technology specifics, etc. Most of these issues can be detected after precise analysis, but is a very resourceful way to study every application run. Therefore we performed less complicated analysis of the whole supercomputer job flow. In this paper we share our experience of analyzing user applications’ job states assigned by the SLURM resource manager that is used on the Lomonosov-2 system at Supercomputing center of Lomonosov Moscow State University. The statistics on job states was collected and it revealed that the ratio of correctly finished jobs (with the COMPLETED state) was rather low. The jobs owners were asked if the distribution of their jobs’ states is normal regarding their applications. This user feedback was processed, and some new ways of efficiency gain were revealed as the result.
- Добавил в систему: Никитенко Дмитрий Александрович
Прикрепленные файлы
| № | Имя | Описание | Имя файла | Размер | Добавлен |
|---|---|---|---|---|---|
| 1. | Полный текст | 183-1112-1-PB.pdf | 252,3 КБ | 8 апреля 2019 [dan] |