{"title":"异构平台上的并行排序","authors":"G. Mateescu","doi":"10.1109/HPCSA.2002.1019143","DOIUrl":null,"url":null,"abstract":"We present a method for load balancing parallel sorting on heterogeneous networks of workstations and clusters. Load balancing is achieved by exploiting information about the available throughput of the processors. First, the problem is partitioned into subproblems such that the times taken by the processors to solve the subproblems are balanced. Determining the partition involves solving a nonlinear system for finding the subproblem sizes. Second, the data are sorted by each process and are merged by choosing a processor topology which minimizes the critical path.","PeriodicalId":111862,"journal":{"name":"Proceedings 16th Annual International Symposium on High Performance Computing Systems and Applications","volume":"46 6","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Parallel sorting on heterogeneous platforms\",\"authors\":\"G. Mateescu\",\"doi\":\"10.1109/HPCSA.2002.1019143\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a method for load balancing parallel sorting on heterogeneous networks of workstations and clusters. Load balancing is achieved by exploiting information about the available throughput of the processors. First, the problem is partitioned into subproblems such that the times taken by the processors to solve the subproblems are balanced. Determining the partition involves solving a nonlinear system for finding the subproblem sizes. Second, the data are sorted by each process and are merged by choosing a processor topology which minimizes the critical path.\",\"PeriodicalId\":111862,\"journal\":{\"name\":\"Proceedings 16th Annual International Symposium on High Performance Computing Systems and Applications\",\"volume\":\"46 6\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 16th Annual International Symposium on High Performance Computing Systems and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPCSA.2002.1019143\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 16th Annual International Symposium on High Performance Computing Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPCSA.2002.1019143","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We present a method for load balancing parallel sorting on heterogeneous networks of workstations and clusters. Load balancing is achieved by exploiting information about the available throughput of the processors. First, the problem is partitioned into subproblems such that the times taken by the processors to solve the subproblems are balanced. Determining the partition involves solving a nonlinear system for finding the subproblem sizes. Second, the data are sorted by each process and are merged by choosing a processor topology which minimizes the critical path.