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Proceedings Paper

A highly scalable parallel computation strategy and optimized implementation for Fresnel Seismic Tomography
Author(s): Yongan Gao; Changhai Zhao; Chuang Li ; Haihua Yan; Liang Zhao
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Paper Abstract

Fresnel Seismic Tomography which uses a huge amount of seismic data is an efficient methodology of researching three-dimensional structure of earth. However, in practical application, it confronts with two key challenges of enormous data volume and huge computation. It is difficult to accomplish computation tasks under normal operating environment and computation strategies. In this paper, a Job-By-Application parallel computation strategy, which uses MPI (Message Passing Interface) and Pthread hybrid programming models based on the cluster, is designed to implement Fresnel seismic tomography, this method can solve the problem of allocating tasks dynamically, improve the load balancing and scalability of the system effectively; and we adopted the cached I/O strategy to accommodate the limited memory resources. Experimental results demonstrated that the program implemented on these strategies could completed the actual job within the idea time, the running of the program was stable, achieved load balancing, showed a good speedup and could adapt to the hardware environment of insufficient memory.

Paper Details

Date Published: 13 March 2013
PDF: 10 pages
Proc. SPIE 8783, Fifth International Conference on Machine Vision (ICMV 2012): Computer Vision, Image Analysis and Processing, 87831R (13 March 2013); doi: 10.1117/12.2021194
Show Author Affiliations
Yongan Gao, BeiHang Univ. (China)
Changhai Zhao, BeiHang Univ. (China)
Chuang Li , BeiHang Univ. (China)
Haihua Yan, BeiHang Univ. (China)
Liang Zhao, Geophysical Prospecting Equipment Co., Ltd. (China)

Published in SPIE Proceedings Vol. 8783:
Fifth International Conference on Machine Vision (ICMV 2012): Computer Vision, Image Analysis and Processing
Yulin Wang; Liansheng Tan; Jianhong Zhou, Editor(s)

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