P. Lin, M. Bettencourt, S. Domino, T. Fisher, M. Hoemmen, Jonathan J. Hu, E. Phipps, A. Prokopenko, S. Rajamanickam, C. Siefert, E. Cyr, S. Kennon
{"title":"Towards Extreme-Scale Simulations with Next-Generation Trilinos: A Low Mach Fluid Application Case Study","authors":"P. Lin, M. Bettencourt, S. Domino, T. Fisher, M. Hoemmen, Jonathan J. Hu, E. Phipps, A. Prokopenko, S. Rajamanickam, C. Siefert, E. Cyr, S. Kennon","doi":"10.1109/IPDPSW.2014.166","DOIUrl":null,"url":null,"abstract":"Trilinos is an object-oriented software framework for the solution of large-scale, complex multi-physics engineering and scientific problems. While the original version of Trilinos was designed for highly scalable solutions for large problems, the need for increasingly higher fidelity simulations has pushed the problem sizes beyond what could have been envisioned two decades ago. When problem sizes exceed a billion elements even highly scalable applications and solver stacks require a complete revision. The next-generation Trilinos employs C++ templates in order to solve arbitrarily large problems and enable extreme-scale simulations. We present a case study that involves integration of Trilinos with an engineering application (Sierra low Mach module/Nalu), involving the simulation of low Mach fluid flow for problems of size up to nine billion elements. Through the use of improved algorithms and better software engineering practices, we demonstrate good weak scaling for the matrix assembly and solve for the engineering application for up to a nine billion element fluid flow large eddy simulation (LES) problem on unstructured meshes with a 27 billion row matrix on 131,072 cores of a Cray XE6 platform.","PeriodicalId":153864,"journal":{"name":"2014 IEEE International Parallel & Distributed Processing Symposium Workshops","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Parallel & Distributed Processing Symposium Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IPDPSW.2014.166","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
Trilinos is an object-oriented software framework for the solution of large-scale, complex multi-physics engineering and scientific problems. While the original version of Trilinos was designed for highly scalable solutions for large problems, the need for increasingly higher fidelity simulations has pushed the problem sizes beyond what could have been envisioned two decades ago. When problem sizes exceed a billion elements even highly scalable applications and solver stacks require a complete revision. The next-generation Trilinos employs C++ templates in order to solve arbitrarily large problems and enable extreme-scale simulations. We present a case study that involves integration of Trilinos with an engineering application (Sierra low Mach module/Nalu), involving the simulation of low Mach fluid flow for problems of size up to nine billion elements. Through the use of improved algorithms and better software engineering practices, we demonstrate good weak scaling for the matrix assembly and solve for the engineering application for up to a nine billion element fluid flow large eddy simulation (LES) problem on unstructured meshes with a 27 billion row matrix on 131,072 cores of a Cray XE6 platform.