{"title":"用于高性能计算机的线性代数库:个人视角","authors":"J. Dongarra","doi":"10.1109/88.219856","DOIUrl":null,"url":null,"abstract":"Linpack software, which was released in 1979, for solving linear algebra problems on high-performance computers is reviewed. The Linpack benchmark and standards development are discussed. Lapack, a linear algebra library that embodies ideas of locality of reference and data reuse, is described. The algorithms design in Lapack and the advantages and future developments of Lapack are also discussed.<<ETX>>","PeriodicalId":325213,"journal":{"name":"IEEE Parallel & Distributed Technology: Systems & Applications","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Linear algebra libraries for high-performance computers: a personal perspective\",\"authors\":\"J. Dongarra\",\"doi\":\"10.1109/88.219856\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Linpack software, which was released in 1979, for solving linear algebra problems on high-performance computers is reviewed. The Linpack benchmark and standards development are discussed. Lapack, a linear algebra library that embodies ideas of locality of reference and data reuse, is described. The algorithms design in Lapack and the advantages and future developments of Lapack are also discussed.<<ETX>>\",\"PeriodicalId\":325213,\"journal\":{\"name\":\"IEEE Parallel & Distributed Technology: Systems & Applications\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Parallel & Distributed Technology: Systems & Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/88.219856\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Parallel & Distributed Technology: Systems & Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/88.219856","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Linear algebra libraries for high-performance computers: a personal perspective
Linpack software, which was released in 1979, for solving linear algebra problems on high-performance computers is reviewed. The Linpack benchmark and standards development are discussed. Lapack, a linear algebra library that embodies ideas of locality of reference and data reuse, is described. The algorithms design in Lapack and the advantages and future developments of Lapack are also discussed.<>