{"title":"并行矩阵乘法中大小矩阵的问题","authors":"C. Piano","doi":"10.1080/1063719031000087996","DOIUrl":null,"url":null,"abstract":"In this paper we discuss the case in which, using the generalized Cannon's algorithm, it is possible to reduce communications in matrix multiplication. We then apply reduction of communications to the case in which we have to multiply large matrices, in particular rectangular matrices. Two strategies are proposed to solve the problem of multiplying two large squared matrices. For the case in which we have to deal with small matrices, some methods are proposed to use the entire number of processors.","PeriodicalId":406098,"journal":{"name":"Parallel Algorithms and Applications","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The problem of small and large matrices in parallel Matrix Multiplication\",\"authors\":\"C. Piano\",\"doi\":\"10.1080/1063719031000087996\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we discuss the case in which, using the generalized Cannon's algorithm, it is possible to reduce communications in matrix multiplication. We then apply reduction of communications to the case in which we have to multiply large matrices, in particular rectangular matrices. Two strategies are proposed to solve the problem of multiplying two large squared matrices. For the case in which we have to deal with small matrices, some methods are proposed to use the entire number of processors.\",\"PeriodicalId\":406098,\"journal\":{\"name\":\"Parallel Algorithms and Applications\",\"volume\":\"81 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Parallel Algorithms and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/1063719031000087996\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Parallel Algorithms and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/1063719031000087996","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The problem of small and large matrices in parallel Matrix Multiplication
In this paper we discuss the case in which, using the generalized Cannon's algorithm, it is possible to reduce communications in matrix multiplication. We then apply reduction of communications to the case in which we have to multiply large matrices, in particular rectangular matrices. Two strategies are proposed to solve the problem of multiplying two large squared matrices. For the case in which we have to deal with small matrices, some methods are proposed to use the entire number of processors.
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