{"title":"向量超立方体上特殊线性系统的迭代解","authors":"L. G. Pillis, J. Petersen, J. Pillis","doi":"10.1145/63047.63130","DOIUrl":null,"url":null,"abstract":"An Intel Hypercube implementation of a new stationary iterative method developed by one of us (JdP) is presented. This algorithm finds the solution vector <italic>x</italic> for the invertible <italic>n</italic> × <italic>n</italic> linear system <italic>Ax</italic> = (<italic>I - B</italic>)<italic>x</italic> = <italic>f</italic> where <italic>A</italic> has real spectrum. The solution method converges quickly because the Jacobi iteration matrix <italic>B</italic> is replaced by an equivalent iteration matrix with a smaller spectral radius. The parallel algorithm partitions <italic>A</italic> row-wise among all the processors in order to keep memory load to a minimum and to avoid duplicate computations. With the introduction of vector hardware to the Hypercube, more modifications have been made to the implementation algorithm in order to exploit that hardware and reduce run-time even further. Example problems and timings will be presented.","PeriodicalId":299435,"journal":{"name":"Conference on Hypercube Concurrent Computers and Applications","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1989-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"An iterative solution to speical linear systems on a vector hypercube\",\"authors\":\"L. G. Pillis, J. Petersen, J. Pillis\",\"doi\":\"10.1145/63047.63130\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An Intel Hypercube implementation of a new stationary iterative method developed by one of us (JdP) is presented. This algorithm finds the solution vector <italic>x</italic> for the invertible <italic>n</italic> × <italic>n</italic> linear system <italic>Ax</italic> = (<italic>I - B</italic>)<italic>x</italic> = <italic>f</italic> where <italic>A</italic> has real spectrum. The solution method converges quickly because the Jacobi iteration matrix <italic>B</italic> is replaced by an equivalent iteration matrix with a smaller spectral radius. The parallel algorithm partitions <italic>A</italic> row-wise among all the processors in order to keep memory load to a minimum and to avoid duplicate computations. With the introduction of vector hardware to the Hypercube, more modifications have been made to the implementation algorithm in order to exploit that hardware and reduce run-time even further. Example problems and timings will be presented.\",\"PeriodicalId\":299435,\"journal\":{\"name\":\"Conference on Hypercube Concurrent Computers and Applications\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1989-01-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Conference on Hypercube Concurrent Computers and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/63047.63130\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference on Hypercube Concurrent Computers and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/63047.63130","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
摘要
本文提出了一种新的平稳迭代方法(JdP)的Intel Hypercube实现。该算法求出可逆n × n线性系统Ax = (I - B)x = f的解向量x,其中A具有实数谱。由于将Jacobi迭代矩阵B替换为谱半径更小的等价迭代矩阵,求解方法收敛速度快。并行算法在所有处理器之间按行划分A,以便将内存负载保持在最小并避免重复计算。随着向Hypercube引入矢量硬件,对实现算法进行了更多修改,以便利用该硬件并进一步减少运行时间。将介绍示例问题和时间安排。
An iterative solution to speical linear systems on a vector hypercube
An Intel Hypercube implementation of a new stationary iterative method developed by one of us (JdP) is presented. This algorithm finds the solution vector x for the invertible n × n linear system Ax = (I - B)x = f where A has real spectrum. The solution method converges quickly because the Jacobi iteration matrix B is replaced by an equivalent iteration matrix with a smaller spectral radius. The parallel algorithm partitions A row-wise among all the processors in order to keep memory load to a minimum and to avoid duplicate computations. With the introduction of vector hardware to the Hypercube, more modifications have been made to the implementation algorithm in order to exploit that hardware and reduce run-time even further. Example problems and timings will be presented.