Research on the influence of node deployment in cluster for modeling efficiency

Yuxiang Liu; Yang Peng; Xin Long; Maojun Zhang

doi:10.1117/12.2540983

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31 July 2019 Research on the influence of node deployment in cluster for modeling efficiency

Yuxiang Liu, Yang Peng, Xin Long, Maojun Zhang

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Proceedings Volume 11198, Fourth International Workshop on Pattern Recognition; 111980U (2019) https://doi.org/10.1117/12.2540983
Event: Fourth International Workshop on Pattern Recognition, 2019, Nanjing, China

Abstract

With the rapid development of oblique photography (OP) in recent years, the accuracy of reality modeling has increased, which has led to a surge in computational complexity. To solve the problem, a lot of reality modeling software adopts the strategy of cluster parallel computing for modeling. In this paper, the regression analysis method is used to study the influence of the configuration of the compute nodes in the cluster, which aims at improving the computational efficiency of the cluster for the 3D reconstruction task. Furthermore, the M/M/S queuing model in queuing theory is used to model the multi-task assignment of the cluster, and the mathematical model between compute nodes and performance of the cluster is established, which achieves the effective quantitative evaluation of the cluster computing efficiency. Experiments show that the CPU performance of the compute nodes is the most critical hardware factor affecting the efficiency of the cluster.

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Yuxiang Liu, Yang Peng, Xin Long, and Maojun Zhang "Research on the influence of node deployment in cluster for modeling efficiency", Proc. SPIE 11198, Fourth International Workshop on Pattern Recognition, 111980U (31 July 2019); https://doi.org/10.1117/12.2540983

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