Yingchong Situ, Lixia Liu, Chandra S. Martha, Matthew E. Louis, Zhiyuan Li, A. Sameh, G. Blaisdell, A. Lyrintzis
{"title":"Reducing Communication Overhead in Large Eddy Simulation of Jet Engine Noise","authors":"Yingchong Situ, Lixia Liu, Chandra S. Martha, Matthew E. Louis, Zhiyuan Li, A. Sameh, G. Blaisdell, A. Lyrintzis","doi":"10.1109/CLUSTER.2010.31","DOIUrl":null,"url":null,"abstract":"Computational aeroacoustics (CAA) has emerged as a tool to complement theoretical and experimental approaches for robust and accurate prediction of sound levels from aircraft airframes and engines. CAA, unlike computational fluid dynamics (CFD), involves the accurate prediction of small-amplitude acoustic fluctuations and their correct propagation to the far field. In that respect, CAA poses significant challenges for researchers because the computational scheme should have high accuracy, good spectral resolution, and low dispersion and diffusion errors. A high-order compact finite difference scheme, which is implicit in space, can be used for such simulations because it fulfills the requirements for CAA. Usually, this method is parallelized using a transposition scheme; however, that approach has a high communication overhead. In this paper, we discuss the use of a parallel tridiagonal linear system solver based on the truncated SPIKE algorithm for reducing the communication overhead in our large eddy simulations. We report experimental results collected on two parallel computing platforms.","PeriodicalId":152171,"journal":{"name":"2010 IEEE International Conference on Cluster Computing","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Cluster Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CLUSTER.2010.31","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Computational aeroacoustics (CAA) has emerged as a tool to complement theoretical and experimental approaches for robust and accurate prediction of sound levels from aircraft airframes and engines. CAA, unlike computational fluid dynamics (CFD), involves the accurate prediction of small-amplitude acoustic fluctuations and their correct propagation to the far field. In that respect, CAA poses significant challenges for researchers because the computational scheme should have high accuracy, good spectral resolution, and low dispersion and diffusion errors. A high-order compact finite difference scheme, which is implicit in space, can be used for such simulations because it fulfills the requirements for CAA. Usually, this method is parallelized using a transposition scheme; however, that approach has a high communication overhead. In this paper, we discuss the use of a parallel tridiagonal linear system solver based on the truncated SPIKE algorithm for reducing the communication overhead in our large eddy simulations. We report experimental results collected on two parallel computing platforms.