{"title":"在Intel iPSC/860上实现共轭梯度法的有效存储和通信方案","authors":"D. Anderson, L. Sattler","doi":"10.1109/DMCC.1991.633309","DOIUrl":null,"url":null,"abstract":"The conjugate gradient method for solving the system of linear equations arising during a finite element analysis has gained renewed interest with the advent of distributed memory computers. In this paper a method will be described which minimizes storage by taking advantage of symmetry and sparsity and minimizes communication overhead by using asynchronous message passing. The data structure necessary to implement this procedure follows naturally frotn the finite element mesh. Test results show near linear speedup for a suflciently large matrix.","PeriodicalId":313314,"journal":{"name":"The Sixth Distributed Memory Computing Conference, 1991. Proceedings","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Effective Storage and Communication Schemes for Implementation of the Conjugate Gradient Method on an Intel iPSC/860\",\"authors\":\"D. Anderson, L. Sattler\",\"doi\":\"10.1109/DMCC.1991.633309\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The conjugate gradient method for solving the system of linear equations arising during a finite element analysis has gained renewed interest with the advent of distributed memory computers. In this paper a method will be described which minimizes storage by taking advantage of symmetry and sparsity and minimizes communication overhead by using asynchronous message passing. The data structure necessary to implement this procedure follows naturally frotn the finite element mesh. Test results show near linear speedup for a suflciently large matrix.\",\"PeriodicalId\":313314,\"journal\":{\"name\":\"The Sixth Distributed Memory Computing Conference, 1991. Proceedings\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Sixth Distributed Memory Computing Conference, 1991. Proceedings\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DMCC.1991.633309\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Sixth Distributed Memory Computing Conference, 1991. Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DMCC.1991.633309","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Effective Storage and Communication Schemes for Implementation of the Conjugate Gradient Method on an Intel iPSC/860
The conjugate gradient method for solving the system of linear equations arising during a finite element analysis has gained renewed interest with the advent of distributed memory computers. In this paper a method will be described which minimizes storage by taking advantage of symmetry and sparsity and minimizes communication overhead by using asynchronous message passing. The data structure necessary to implement this procedure follows naturally frotn the finite element mesh. Test results show near linear speedup for a suflciently large matrix.
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