A. Genz, Zongli Lin, Charles Jones, Dali Luo, Thorsten Prenzel
{"title":"Fast Givens在MATLAB中很慢","authors":"A. Genz, Zongli Lin, Charles Jones, Dali Luo, Thorsten Prenzel","doi":"10.1145/122286.122288","DOIUrl":null,"url":null,"abstract":"Numerical results show that a straightforward implementation in MATLAB of an algorithm for the Fast Givens QR Factorization of an m x n matrix takes more time than an implementation of an algorithm that uses ordinary Givens transformations. Results of timing experiments for various operations in MATLAB are reported and models are constructed to explain why the standard theoretical analysis based on flop counts does not account for the actual times for the algorithms.","PeriodicalId":177516,"journal":{"name":"ACM Signum Newsletter","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1991-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Fast Givens goes slow in MATLAB\",\"authors\":\"A. Genz, Zongli Lin, Charles Jones, Dali Luo, Thorsten Prenzel\",\"doi\":\"10.1145/122286.122288\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Numerical results show that a straightforward implementation in MATLAB of an algorithm for the Fast Givens QR Factorization of an m x n matrix takes more time than an implementation of an algorithm that uses ordinary Givens transformations. Results of timing experiments for various operations in MATLAB are reported and models are constructed to explain why the standard theoretical analysis based on flop counts does not account for the actual times for the algorithms.\",\"PeriodicalId\":177516,\"journal\":{\"name\":\"ACM Signum Newsletter\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1991-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Signum Newsletter\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/122286.122288\",\"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 Signum Newsletter","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/122286.122288","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Numerical results show that a straightforward implementation in MATLAB of an algorithm for the Fast Givens QR Factorization of an m x n matrix takes more time than an implementation of an algorithm that uses ordinary Givens transformations. Results of timing experiments for various operations in MATLAB are reported and models are constructed to explain why the standard theoretical analysis based on flop counts does not account for the actual times for the algorithms.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
