{"title":"异构计算集群的可扩展密集分解","authors":"Ravi Reddy, Alexey L. Lastovetsky, P. Alonso","doi":"10.1109/ISPDC.2008.10","DOIUrl":null,"url":null,"abstract":"This paper discusses the design and the implementation of the LU factorization routines included in the Heterogeneous ScaLAPACK library, which is built on top of ScaLAPACK. These routines are used in the factorization and solution of a dense system of linear equations. They are implemented using optimized PBLAS, BLACS and BLAS libraries for heterogeneous computational clusters. We present the details of the implementation as well as performance results on a heterogeneous computing cluster.","PeriodicalId":125975,"journal":{"name":"2008 International Symposium on Parallel and Distributed Computing","volume":"468 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Scalable Dense Factorizations for Heterogeneous Computational Clusters\",\"authors\":\"Ravi Reddy, Alexey L. Lastovetsky, P. Alonso\",\"doi\":\"10.1109/ISPDC.2008.10\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper discusses the design and the implementation of the LU factorization routines included in the Heterogeneous ScaLAPACK library, which is built on top of ScaLAPACK. These routines are used in the factorization and solution of a dense system of linear equations. They are implemented using optimized PBLAS, BLACS and BLAS libraries for heterogeneous computational clusters. We present the details of the implementation as well as performance results on a heterogeneous computing cluster.\",\"PeriodicalId\":125975,\"journal\":{\"name\":\"2008 International Symposium on Parallel and Distributed Computing\",\"volume\":\"468 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Symposium on Parallel and Distributed Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISPDC.2008.10\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Symposium on Parallel and Distributed Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISPDC.2008.10","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Scalable Dense Factorizations for Heterogeneous Computational Clusters
This paper discusses the design and the implementation of the LU factorization routines included in the Heterogeneous ScaLAPACK library, which is built on top of ScaLAPACK. These routines are used in the factorization and solution of a dense system of linear equations. They are implemented using optimized PBLAS, BLACS and BLAS libraries for heterogeneous computational clusters. We present the details of the implementation as well as performance results on a heterogeneous computing cluster.
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