Lidong He, Weichang Shen, Yongjin Li, Anlei Shi, D. Zhao
{"title":"基于矩阵行、列分块条纹分解的MPI+OpenMP矩阵乘法实现及结果分析","authors":"Lidong He, Weichang Shen, Yongjin Li, Anlei Shi, D. Zhao","doi":"10.1109/CSO.2010.123","DOIUrl":null,"url":null,"abstract":"This paper outlines the MPI+OpenMPprogramming model, and implements the matrix multiplication based on rowwise and columnwise block-striped decomposition of the matrices with MPI+OpenMPprogramming model in the multi-core cluster system. Experimental results show that the running time of the parallel algorithm is reduced significantly. By further analyzing the running results, the running time is reduced obviously once again","PeriodicalId":427481,"journal":{"name":"2010 Third International Joint Conference on Computational Science and Optimization","volume":"440 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"MPI+OpenMP Implementation and Results Analysis of Matrix Multiplication Based on Rowwise and Columnwise Block-Striped Decomposition of the Matrices\",\"authors\":\"Lidong He, Weichang Shen, Yongjin Li, Anlei Shi, D. Zhao\",\"doi\":\"10.1109/CSO.2010.123\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper outlines the MPI+OpenMPprogramming model, and implements the matrix multiplication based on rowwise and columnwise block-striped decomposition of the matrices with MPI+OpenMPprogramming model in the multi-core cluster system. Experimental results show that the running time of the parallel algorithm is reduced significantly. By further analyzing the running results, the running time is reduced obviously once again\",\"PeriodicalId\":427481,\"journal\":{\"name\":\"2010 Third International Joint Conference on Computational Science and Optimization\",\"volume\":\"440 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Third International Joint Conference on Computational Science and Optimization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSO.2010.123\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Third International Joint Conference on Computational Science and Optimization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSO.2010.123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MPI+OpenMP Implementation and Results Analysis of Matrix Multiplication Based on Rowwise and Columnwise Block-Striped Decomposition of the Matrices
This paper outlines the MPI+OpenMPprogramming model, and implements the matrix multiplication based on rowwise and columnwise block-striped decomposition of the matrices with MPI+OpenMPprogramming model in the multi-core cluster system. Experimental results show that the running time of the parallel algorithm is reduced significantly. By further analyzing the running results, the running time is reduced obviously once again