{"title":"一种矩阵积算法及其在超立方体上的比较性能","authors":"C. Lin, L. Snyder","doi":"10.1109/SHPCC.1992.232648","DOIUrl":null,"url":null,"abstract":"A matrix product algorithm is studied in which one matrix operand is transposed prior to the computation. This algorithm is compared with the Fox-Hey-Otto algorithm on hypercube architectures. The Transpose algorithm simplifies communication for nonsquare matrices and for computations where the number of processors is not a perfect square. The results indicate superior performance for the Transpose algorithm.<<ETX>>","PeriodicalId":254515,"journal":{"name":"Proceedings Scalable High Performance Computing Conference SHPCC-92.","volume":"189 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1992-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":"{\"title\":\"A matrix product algorithm and its comparative performance on hypercubes\",\"authors\":\"C. Lin, L. Snyder\",\"doi\":\"10.1109/SHPCC.1992.232648\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A matrix product algorithm is studied in which one matrix operand is transposed prior to the computation. This algorithm is compared with the Fox-Hey-Otto algorithm on hypercube architectures. The Transpose algorithm simplifies communication for nonsquare matrices and for computations where the number of processors is not a perfect square. The results indicate superior performance for the Transpose algorithm.<<ETX>>\",\"PeriodicalId\":254515,\"journal\":{\"name\":\"Proceedings Scalable High Performance Computing Conference SHPCC-92.\",\"volume\":\"189 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1992-04-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Scalable High Performance Computing Conference SHPCC-92.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SHPCC.1992.232648\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Scalable High Performance Computing Conference SHPCC-92.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SHPCC.1992.232648","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A matrix product algorithm and its comparative performance on hypercubes
A matrix product algorithm is studied in which one matrix operand is transposed prior to the computation. This algorithm is compared with the Fox-Hey-Otto algorithm on hypercube architectures. The Transpose algorithm simplifies communication for nonsquare matrices and for computations where the number of processors is not a perfect square. The results indicate superior performance for the Transpose algorithm.<>