{"title":"并行系统自适应数值积分算法的评价","authors":"Rudolf Schürer, A. Uhl","doi":"10.1080/1063719031000088012","DOIUrl":null,"url":null,"abstract":"Parallel adaptive algorithms for the approximation of a multi-dimensional integral over an hyper-rectangular region are described. Algorithms with centralized global region collection are compared to algorithms using local region collections. The latter algorithms should result in better scalability since global communication is avoided. Both types of algorithms are compared to quasi-Monte Carlo integration. Tests are performed using Genz's test functions and speed-up results are given.","PeriodicalId":406098,"journal":{"name":"Parallel Algorithms and Applications","volume":"212 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"An evaluation of adaptive numerical integration algorithms on parallel systems\",\"authors\":\"Rudolf Schürer, A. Uhl\",\"doi\":\"10.1080/1063719031000088012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Parallel adaptive algorithms for the approximation of a multi-dimensional integral over an hyper-rectangular region are described. Algorithms with centralized global region collection are compared to algorithms using local region collections. The latter algorithms should result in better scalability since global communication is avoided. Both types of algorithms are compared to quasi-Monte Carlo integration. Tests are performed using Genz's test functions and speed-up results are given.\",\"PeriodicalId\":406098,\"journal\":{\"name\":\"Parallel Algorithms and Applications\",\"volume\":\"212 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Parallel Algorithms and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/1063719031000088012\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Parallel Algorithms and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/1063719031000088012","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An evaluation of adaptive numerical integration algorithms on parallel systems
Parallel adaptive algorithms for the approximation of a multi-dimensional integral over an hyper-rectangular region are described. Algorithms with centralized global region collection are compared to algorithms using local region collections. The latter algorithms should result in better scalability since global communication is avoided. Both types of algorithms are compared to quasi-Monte Carlo integration. Tests are performed using Genz's test functions and speed-up results are given.