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Research on the influence of node deployment in cluster for modeling efficiency
Author(s): Yuxiang Liu; Yang Peng; Xin Long; Maojun Zhang
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Paper 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.

Paper Details

Date Published: 31 July 2019
PDF: 6 pages
Proc. SPIE 11198, Fourth International Workshop on Pattern Recognition, 111980U (31 July 2019); doi: 10.1117/12.2540983
Show Author Affiliations
Yuxiang Liu, National Univ. of Defense Technology (China)
Yang Peng, National Univ. of Defense Technology (China)
Xin Long, National Univ. of Defense Technology (China)
Maojun Zhang, National Univ. of Defense Technology (China)


Published in SPIE Proceedings Vol. 11198:
Fourth International Workshop on Pattern Recognition
Xudong Jiang; Zhenxiang Chen; Guojian Chen, Editor(s)

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