Examination of supercomputer system jobs flow dynamic characteristics
Keywords:
supercomputer, performance, efficiency, dynamic characteristics, supercomputer system load, monitoring, resource manager PDF (in Russian) (134KB) PDF. zip (in Russian) (115KB)Abstract
The article presents the supercomputer jobs flow dynamic characteristics monitoring system implemented on the «SKIF MSU Chebyshev» supercomputer at present. The proposed approach to the analysis allows one to get an adequate estimate of actual properties of the job flow efficiently and technologically simply. It allows one to gain a better understanding of the supercomputer resources utilization, to identify shortcomings in the supercomputer architecture, and to find possible directions of its optimization.
References
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- MongoDB (http://www.mongodb.org/).
- Cassandra (http://cassandra.apache.org/).
- Cleo Cluster Batch System (http://sourceforge.net/projects/cleo-bs/).
- SLURM: A Highly Scalable Resource Manager (https://computing.llnl.gov/linux/slurm/).
- Антонов А.С. СКИФ МГУ - основа Суперкомпьютерного комплекса Московского университета // Вторая Международная научная конференция «Суперкомпьютерные системы и их применение» (SSA’2008).
- Linux load averages, for example from top and uptime commands, can be massively incorrect on the low side (http://www.smythies.com/ doug/network/load_average/original.html).
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Published
11-11-2013
How to Cite
Антонов А., Жуматий С., Никитенко Д., Стефанов К., Теплов А., Швец П. Examination of Supercomputer System Jobs Flow Dynamic Characteristics // Numerical Methods and Programming (Vychislitel’nye Metody i Programmirovanie). 2013. 14. 104-108
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Section
Section 2. Programming
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