{"title":"数据并行空间连接算法","authors":"E. Hoel, H. Samet","doi":"10.1109/ICPP.1994.82","DOIUrl":null,"url":null,"abstract":"Efficient data-parallel spatial join algorithms for bucket PMR quadtrees and R-trees, common spatial data structures, are given. The domain consists of planar line segment data (i.e., Bureau of the Census TIGER/Line files). Parallel algorithms for map intersection and a spatial range query are described. The algorithms are implemented using the scan model of parallel computation on the hypercube architecture of the Connection Machine.","PeriodicalId":162043,"journal":{"name":"1994 International Conference on Parallel Processing Vol. 3","volume":"268 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1994-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"44","resultStr":"{\"title\":\"Data-Parallel Spatial Join Algorithms\",\"authors\":\"E. Hoel, H. Samet\",\"doi\":\"10.1109/ICPP.1994.82\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Efficient data-parallel spatial join algorithms for bucket PMR quadtrees and R-trees, common spatial data structures, are given. The domain consists of planar line segment data (i.e., Bureau of the Census TIGER/Line files). Parallel algorithms for map intersection and a spatial range query are described. The algorithms are implemented using the scan model of parallel computation on the hypercube architecture of the Connection Machine.\",\"PeriodicalId\":162043,\"journal\":{\"name\":\"1994 International Conference on Parallel Processing Vol. 3\",\"volume\":\"268 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1994-08-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"44\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1994 International Conference on Parallel Processing Vol. 3\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPP.1994.82\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1994 International Conference on Parallel Processing Vol. 3","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPP.1994.82","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Efficient data-parallel spatial join algorithms for bucket PMR quadtrees and R-trees, common spatial data structures, are given. The domain consists of planar line segment data (i.e., Bureau of the Census TIGER/Line files). Parallel algorithms for map intersection and a spatial range query are described. The algorithms are implemented using the scan model of parallel computation on the hypercube architecture of the Connection Machine.
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