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PyCLiPSM: Harnessing heterogeneous computing resources on CPUs and GPUs for accelerated digital soil mapping

文献类型：期刊论文

作者Zhang, Guiming1; Zhu, A-Xing2,3,6,7; Liu, Jing4; Guo, Shanxin5; Zhu, Yunqiang3
刊名TRANSACTIONS IN GIS
出版日期2021-02-16
页码23
ISSN号1361-1682
DOI10.1111/tgis.12730
通讯作者Zhang, Guiming(guiming.zhang@du.edu)
英文摘要Digital soil mapping (DSM) at high spatial resolutions over large areas often demands considerable computing power. This study aims to harness the heterogeneous computing resources on multi-core central processing units (CPUs) and graphics processing units (GPUs) to accelerate DSM by implementing PyCLiPSM, a parallel version of the iPSM (individual predictive soil mapping) algorithm which represents the type of geospatial algorithms that is data- and compute-intensive and highly parallelizable. PyCLiPSM was implemented in Python based on the PyOpenCL parallel programming library, which runs on any operating system and exploits the computing power of both CPUs and GPUs. Experiments show that PyCLiPSM can effectively leverage multi-core CPUs and GPUs to speed up DSM tasks. PyCLiPSM is open-source and freely available. Using PyCLiPSM as an example, we advocate implementing parallel geospatial algorithms using the PyOpenCL framework to harness the heterogeneous computing resources available to researchers and practitioners for accelerated geospatial analysis.
资助项目University of Denver ; National Natural Science Foundation of China[41601212] ; National Natural Science Foundation of China[41871300]
WOS研究方向Geography
语种英语
WOS记录号WOS:000618617500001
出版者WILEY
资助机构University of Denver ; National Natural Science Foundation of China
源URL[http://ir.igsnrr.ac.cn/handle/311030/160637]  
专题中国科学院地理科学与资源研究所
通讯作者Zhang, Guiming
作者单位1.Univ Denver, Dept Geog & Environm, Denver, CO USA
2.Univ Wisconsin, Dept Geog, Madison, WI 53706 USA
3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China
4.Santa Monica Coll, Earth Sci Dept, Santa Monica, CA USA
5.Chinese Acad Sci, Shenzhen Inst Adv Technol, Ctr Geospatial Informat, Shenzhen, Peoples R China
6.Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing, Peoples R China
7.Nanjing Normal Univ, Sch Geog, Nanjing, Peoples R China
推荐引用方式
GB/T 7714		 Zhang, Guiming,Zhu, A-Xing,Liu, Jing,et al. PyCLiPSM: Harnessing heterogeneous computing resources on CPUs and GPUs for accelerated digital soil mapping[J]. TRANSACTIONS IN GIS,2021:23.
APA Zhang, Guiming,Zhu, A-Xing,Liu, Jing,Guo, Shanxin,&Zhu, Yunqiang.(2021).PyCLiPSM: Harnessing heterogeneous computing resources on CPUs and GPUs for accelerated digital soil mapping.TRANSACTIONS IN GIS,23.
MLA Zhang, Guiming,et al."PyCLiPSM: Harnessing heterogeneous computing resources on CPUs and GPUs for accelerated digital soil mapping".TRANSACTIONS IN GIS (2021):23.

入库方式： OAI收割

来源：地理科学与资源研究所

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