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     Research Journal of Applied Sciences, Engineering and Technology


Accelerating 3D Visualization in Reservoir Modeling System with Programmable Hardware

1Lin Liu, 2Yumei Ning and 3Desheng Li
1Software Institute East China Institute of Technology, Nan Chang 330013, China
2School of Computer Science and Technology, Xidian University, Xi’an 710071, Shanxi, China
3School of Science, Anhui Science and Technology University, Fengyang 233100, China
Research Journal of Applied Sciences, Engineering and Technology  2013  22:5194-5200
http://dx.doi.org/10.19026/rjaset.5.4264  |  © The Author(s) 2013
Received: July 27, 2012  |  Accepted: September 12, 2012  |  Published: May 25, 2013

Abstract

This study presents a new method on 3D visualization in reservoir modeling system by using the computation power of modern programmable Graphics hardware (GPU). The proposed scheme is devised to achieve parallel processing of massive reservoir logging data. By taking advantage of the GPU's parallel processing capability, moreover, the performance of our scheme is discussed in comparison with that of the implementation entirely running on CPU. Experimental results clearly show that the proposed parallel processing can remarkably accelerate the data clustering task. Especially, although data-transferring from GPU to CPU is generally costly, acceleration by GPU is significant to save the total execution time of data-clustering and also significantly alleviates the computing load on CPU.

Keywords:

Graphics Processing Unit (GPU), massive data, reservoir modeling, 3D visualization,


References


Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.

ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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