{"title":"基于PVM的一维流动方程共轭梯度和高斯-赛德尔并行算法的时序比较","authors":"Luke Olszewski","doi":"10.1145/1122018.1122055","DOIUrl":null,"url":null,"abstract":"The development of parallel processing came about due to the ineffectiveness of a single processor to accommodate the solutions of large scale problems in a reasonable amount of time. In this paper, we shall introduce one such problem, and discuss the implementation of two parallel algorithms applied to the linear approximations. This study will illustrate how an approximation method which has a faster rate of convergence may not necessarily produce the best solution time.","PeriodicalId":349974,"journal":{"name":"ACM-SE 33","volume":"21 12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A timing comparison of the conjugate gradient and Gauss-Seidel parallel algorithms in a one-dimensional flow equation using PVM\",\"authors\":\"Luke Olszewski\",\"doi\":\"10.1145/1122018.1122055\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The development of parallel processing came about due to the ineffectiveness of a single processor to accommodate the solutions of large scale problems in a reasonable amount of time. In this paper, we shall introduce one such problem, and discuss the implementation of two parallel algorithms applied to the linear approximations. This study will illustrate how an approximation method which has a faster rate of convergence may not necessarily produce the best solution time.\",\"PeriodicalId\":349974,\"journal\":{\"name\":\"ACM-SE 33\",\"volume\":\"21 12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-03-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM-SE 33\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1122018.1122055\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM-SE 33","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1122018.1122055","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A timing comparison of the conjugate gradient and Gauss-Seidel parallel algorithms in a one-dimensional flow equation using PVM
The development of parallel processing came about due to the ineffectiveness of a single processor to accommodate the solutions of large scale problems in a reasonable amount of time. In this paper, we shall introduce one such problem, and discuss the implementation of two parallel algorithms applied to the linear approximations. This study will illustrate how an approximation method which has a faster rate of convergence may not necessarily produce the best solution time.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
