{"title":"Coarse grained parallel next element search","authors":"Albert Chan, F. Dehne, A. Rau-Chaplin","doi":"10.1109/IPPS.1997.580919","DOIUrl":null,"url":null,"abstract":"The authors present a parallel algorithm for solving the next element search problem on a set of line segments, using a BSP like model referred to as the coarse grained multicomputer (CGM). The algorithm requires O(1) communication rounds (h-relations with h=O(n/p)), O((n/p) log n) local computation, and O((n/p) log n) storage per processor. The result implies solutions to the point location, trapezoidal decomposition and polygon triangulation problems. A simplified version for axis parallel segments requires only O(n/p) storage per processor, and they discuss an implementation of this version. As in a previous paper by Develliers and Fabri (1993), their algorithm is based on a distributed implementation of segment trees which are of size O(n log n). The paper improves on the work of Develliers and Fabri which presented a CGM algorithm for the special case of trapezoidal decomposition only and requires O((n/p)*log p*log n) local computation.","PeriodicalId":145892,"journal":{"name":"Proceedings 11th International Parallel Processing Symposium","volume":"243 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 11th International Parallel Processing Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPPS.1997.580919","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
The authors present a parallel algorithm for solving the next element search problem on a set of line segments, using a BSP like model referred to as the coarse grained multicomputer (CGM). The algorithm requires O(1) communication rounds (h-relations with h=O(n/p)), O((n/p) log n) local computation, and O((n/p) log n) storage per processor. The result implies solutions to the point location, trapezoidal decomposition and polygon triangulation problems. A simplified version for axis parallel segments requires only O(n/p) storage per processor, and they discuss an implementation of this version. As in a previous paper by Develliers and Fabri (1993), their algorithm is based on a distributed implementation of segment trees which are of size O(n log n). The paper improves on the work of Develliers and Fabri which presented a CGM algorithm for the special case of trapezoidal decomposition only and requires O((n/p)*log p*log n) local computation.