Multicore Parallelized Spatial Overlay Analysis Algorithm Using Vector Polygon Shape Complexity Index Optimization
文献类型：期刊论文
| 作者 | Fan, Junfu1,2; Zuo, Jiwei1; Sun, Guangwei1; Shi, Zongwen1; Gao, Yu1; Zhang, Yi3,4 |
| 刊名 | APPLIED SCIENCES-BASEL
 |
| 出版日期 | 2024-03-01 |
| 卷号 | 14期号:5页码:14 |
| 关键词 | overlay analysis shape complexity data partitioning parallel computing acceleration ratio load balancing OpenMP |
| DOI | 10.3390/app14052006 |
| 通讯作者 | Sun, Guangwei(sgw_sdut@163.com) |
| 英文摘要 | As core algorithms of geographic computing, overlay analysis algorithms typically have computation-intensive and data-intensive characteristics. It is highly important to optimize overlay analysis algorithms by parallelizing the vector polygons after reasonable data division. To address the problem of unbalanced data partitioning in the task decomposition process for parallel polygon overlay analysis and calculation, this paper presents a data partitioning method based on shape complexity index optimization, which achieves data equalization among multicore parallel computing tasks. Taking the intersection operator and difference operator of the Vatti algorithm as examples, six polygon shape indexes are selected to construct the shape complexity model, and the vector data are divided in accordance with the calculated shape complexity results. Finally, multicore parallelism is achieved based on OpenMP. The experimental results show that when a data set with a large amount of data is used, the effect of the multicore parallel execution of the Vatti algorithm's intersection operator and difference operator based on shape complexity division is clearly improved. With 16 threads, compared with the serial algorithm, speedups of 29 times and 32 times can be obtained. Compared with the traditional multicore parallel algorithm based on polygon number division, the speed can be improved by 33% and 29%, and the load balancing index is reduced. For a data set with a small amount of data, the acceleration effect of this method is similar to that of traditional methods involving multicore parallelism. |
| 资助项目 | National Natural Science Foundation of China |
| WOS研究方向 | Chemistry ; Engineering ; Materials Science ; Physics |
| 语种 | 英语 |
| WOS记录号 | WOS:001182861000001 |
| 出版者 | MDPI |
| 资助机构 | National Natural Science Foundation of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/203703]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Sun, Guangwei |
| 作者单位 | 1.Shandong Univ Technol, Sch Civil Engn & Geomat, Zibo 255000, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 3.Shandong Agr & Engn Univ, Coll Land & Resources & Surveying & Mapping Engn, Jinan 250100, Peoples R China 4.Cent South Univ, Sch Geosci & Info Phys, Changsha 410083, Peoples R China |
| 推荐引用方式 GB/T 7714 | Fan, Junfu,Zuo, Jiwei,Sun, Guangwei,et al. Multicore Parallelized Spatial Overlay Analysis Algorithm Using Vector Polygon Shape Complexity Index Optimization[J]. APPLIED SCIENCES-BASEL,2024,14(5):14. |
| APA | Fan, Junfu,Zuo, Jiwei,Sun, Guangwei,Shi, Zongwen,Gao, Yu,&Zhang, Yi.(2024).Multicore Parallelized Spatial Overlay Analysis Algorithm Using Vector Polygon Shape Complexity Index Optimization.APPLIED SCIENCES-BASEL,14(5),14. |
| MLA | Fan, Junfu,et al."Multicore Parallelized Spatial Overlay Analysis Algorithm Using Vector Polygon Shape Complexity Index Optimization".APPLIED SCIENCES-BASEL 14.5(2024):14. |
入库方式： OAI收割
来源：地理科学与资源研究所
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