A fine-granularity scheduling algorithm for parallel XDraw viewshed analysis |
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| Authors: | Wanfeng Dou Yanan Li Yanli Wang |
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| Institution: | 1.School of Computer Science and Technology,Nanjing Normal University,Nanjing,China;2.Jiangsu Research Center for Information Security & Privacy Technology,Nanjing,China |
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| Abstract: | Viewshed analysis is widely used in many terrain applications such as siting problem, path planning problem, and etc. But viewshed computation is very time-consuming, in particular for applications with large-scale terrain data. Parallel computing as a mainstream technique with the tremendous potential has been introduced to enhance the computation performance of viewshed analysis. This paper presents a revised parallel viewshed computation approach based on the existing serial XDraw algorithm in a distributed parallel computing environment. A layered data-dependent model for processing data dependency in the XDraw algorithm is built to explore scheduling strategy so that a fine-granularity scheduling strategy on the process-level and thread-level parallel computing model can be accepted to improve the efficiency of the viewshed computation. And a parallel computing algorithm, XDraw-L, is designed and implemented taken into account this scheduling strategy. The experimental results demonstrate a distinct improvement of computation performance of the XDraw-L algorithm in this paper compared with the coarse-partition algorithm, like XDraw-E which is presented by Song et al. (Earth Sci Inf 10(5):511–523, 2016), and XDraw-B that is the basic algorithm of serial XDraw. Our fine-granularity scheduling algorithm can greatly improve the scheduling performance of the grid cells between the layers within a triangle region. |
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