{"title":"高精度分布式存储器并行特征值求解器初步研究","authors":"Toshiyuki Imamura, S. Yamada, M. Machida","doi":"10.1109/SC.Companion.2012.255","DOIUrl":null,"url":null,"abstract":"This study covers the design and implementation of a DD (double-double) extended parallel eigenvalue solver, namely QPEigenK. We extended most of underlying numerical software layers from BLAS, LAPACK, and ScaLAPACK as well as MPI. Preliminary results show that QPEigenK performs on several platforms, and shows good accuracy and parallel efficiency. We can conclude that the DD format is reasonable data format instead of real (16) format from the viewpoint of programming and performance.","PeriodicalId":6346,"journal":{"name":"2012 SC Companion: High Performance Computing, Networking Storage and Analysis","volume":"85 1","pages":"1454-1455"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Abstract: Preliminary Report for a High Precision Distributed Memory Parallel Eigenvalue Solver\",\"authors\":\"Toshiyuki Imamura, S. Yamada, M. Machida\",\"doi\":\"10.1109/SC.Companion.2012.255\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study covers the design and implementation of a DD (double-double) extended parallel eigenvalue solver, namely QPEigenK. We extended most of underlying numerical software layers from BLAS, LAPACK, and ScaLAPACK as well as MPI. Preliminary results show that QPEigenK performs on several platforms, and shows good accuracy and parallel efficiency. We can conclude that the DD format is reasonable data format instead of real (16) format from the viewpoint of programming and performance.\",\"PeriodicalId\":6346,\"journal\":{\"name\":\"2012 SC Companion: High Performance Computing, Networking Storage and Analysis\",\"volume\":\"85 1\",\"pages\":\"1454-1455\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 SC Companion: High Performance Computing, Networking Storage and Analysis\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SC.Companion.2012.255\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 SC Companion: High Performance Computing, Networking Storage and Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SC.Companion.2012.255","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Abstract: Preliminary Report for a High Precision Distributed Memory Parallel Eigenvalue Solver
This study covers the design and implementation of a DD (double-double) extended parallel eigenvalue solver, namely QPEigenK. We extended most of underlying numerical software layers from BLAS, LAPACK, and ScaLAPACK as well as MPI. Preliminary results show that QPEigenK performs on several platforms, and shows good accuracy and parallel efficiency. We can conclude that the DD format is reasonable data format instead of real (16) format from the viewpoint of programming and performance.
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