Abstract
Distributed computing technology has been widely used to solve complex problems appearing in parallel processing systems. Job scheduling is very important in many distributed computing systems, like grid systems and high performance computers. Their performance is directly related to the efficiency of the distributed computing systems. Modeling them and analyzing their performance can provide quantitative performance metrics and predictions, which are helpful to guide capacity planning and scheduling optimization. In this paper, we study job scheduling systems widespread in high performance computing systems and propose a coloured Petri net method for analyzing their performance, which can be easily implemented in CPN software by potential users. We also propose an approximative modeling technique so as to reduce the model size. As a model-based performance analysis method, our method is low cost and highly flexible. Experimental results show that our method is feasible and can be applied to more complex and large-scale systems.
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Acknowledgments
The authors would like to thank the anonymous referees for their comments and suggestions. This work is partially supported by the National Science Foundation of China (NSFC) under grant No. 91418206.
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Li, Z., Jiao, L., Hu, X. (2015). Performance Analysis for Job Scheduling in Hierarchical HPC Systems: A Coloured Petri Nets Method. In: Wang, G., Zomaya, A., Martinez, G., Li, K. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2015. Lecture Notes in Computer Science(), vol 9531. Springer, Cham. https://doi.org/10.1007/978-3-319-27140-8_19
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DOI: https://doi.org/10.1007/978-3-319-27140-8_19
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