{"title":"Parallel SDDM with Communication-Avoiding BICGSTAB for Large-Scale 3D Scattering Problems","authors":"Mingfei Fan, Rui-Qing Liu, Ming-lin Yang, X. Sheng","doi":"10.23919/ACES48530.2019.9060447","DOIUrl":null,"url":null,"abstract":"In the parallel finite element domain decomposition methods (FEM-DDM), one of the key step is to solve the reduced linear system defined on the subdomain interfaces iteratively using a Krylov subspace method such as the biconjugate gradient stabilized (BICGSTAB) method. In each iteration of BICGSTAB, multiple global MPI communication collectives are required, which are becoming increasingly expensive when many processors are used on modern computers, especially on a large-scale system. To address this limitation, a communication-avoiding variant of BICGSTAB (CA-BICGSTAB) is realized and implemented to minimize global communication therefore improve massively parallel efficiency of the FEM-DDM in this paper. A series of numerical examples are presented to demonstrate the superior performance of CA-BICGSTAB over conventional BICGSTAB.","PeriodicalId":247909,"journal":{"name":"2019 International Applied Computational Electromagnetics Society Symposium - China (ACES)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Applied Computational Electromagnetics Society Symposium - China (ACES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/ACES48530.2019.9060447","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In the parallel finite element domain decomposition methods (FEM-DDM), one of the key step is to solve the reduced linear system defined on the subdomain interfaces iteratively using a Krylov subspace method such as the biconjugate gradient stabilized (BICGSTAB) method. In each iteration of BICGSTAB, multiple global MPI communication collectives are required, which are becoming increasingly expensive when many processors are used on modern computers, especially on a large-scale system. To address this limitation, a communication-avoiding variant of BICGSTAB (CA-BICGSTAB) is realized and implemented to minimize global communication therefore improve massively parallel efficiency of the FEM-DDM in this paper. A series of numerical examples are presented to demonstrate the superior performance of CA-BICGSTAB over conventional BICGSTAB.