{"title":"海报:基于矩阵分解的泊松方程共轭梯度求解器","authors":"Hang Liu, J. Seo, R. Mittal","doi":"10.1109/SC.Companion.2012.287","DOIUrl":null,"url":null,"abstract":"Finding a fast solver for the Poisson equation is important for many scientific applications. In this work, we design and develop a matrix decomposition based Conjugate Gradient (CG) solver, which leverages Graphics Processing Unit (GPU) clusters to accelerate the calculation of the Poisson equation. Our experiments show that the new CG solver is highly scalable and achieves significant speedup over a CPU-based Multi-Grid (MG) solver.","PeriodicalId":6346,"journal":{"name":"2012 SC Companion: High Performance Computing, Networking Storage and Analysis","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2012-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Poster: Matrix Decomposition Based Conjugate Gradient Solver for Poisson Equation\",\"authors\":\"Hang Liu, J. Seo, R. Mittal\",\"doi\":\"10.1109/SC.Companion.2012.287\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Finding a fast solver for the Poisson equation is important for many scientific applications. In this work, we design and develop a matrix decomposition based Conjugate Gradient (CG) solver, which leverages Graphics Processing Unit (GPU) clusters to accelerate the calculation of the Poisson equation. Our experiments show that the new CG solver is highly scalable and achieves significant speedup over a CPU-based Multi-Grid (MG) solver.\",\"PeriodicalId\":6346,\"journal\":{\"name\":\"2012 SC Companion: High Performance Computing, Networking Storage and Analysis\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-11-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"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.2012.287\",\"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.2012.287","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Poster: Matrix Decomposition Based Conjugate Gradient Solver for Poisson Equation
Finding a fast solver for the Poisson equation is important for many scientific applications. In this work, we design and develop a matrix decomposition based Conjugate Gradient (CG) solver, which leverages Graphics Processing Unit (GPU) clusters to accelerate the calculation of the Poisson equation. Our experiments show that the new CG solver is highly scalable and achieves significant speedup over a CPU-based Multi-Grid (MG) solver.
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