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Using ESPRESO as Linear Solver Library for Third Party FEM Tools for Solving Large Scale Problems

机译:使用ESPRESO作为第三方FEM工具的线性求解器库来解决大规模问题

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ESPRESO is a FEM package that includes a Hybrid Total FETI (HTFETI) linear solver targeted at solving large scale engineering problems. The scalability of the solver was tested on several of the world's largest supercomputers. To provide our scalable implementation of HTFETI algorithms to all potential users, a simple С API was developed and is presented. The paper describes API methods, compilation and linking process. As a proof of concept we interfaced ESPRESO with the CSC ELMER solver and compared its performance with the ELMER FETI solver. HTFETI performs two level decomposition, which significantly improves both memory utilization and solver performance. To select optimal second level decomposition we have developed a performance model that controls decomposition automatically. This is a major simplification for all users that ensures optimal solver settings. We show that the ESPRESO HTFETI solver is up to 3.7 times faster than the ELMER FETI solver when running on 13 500 MPI processes (the 614 compute nodes of the Salomon supercomputer) and solving 1.5 billion unknown problems of 3D linear elasticity.
机译:ESPRESO是一个FEM软件包,其中包括一个旨在解决大规模工程问题的混合式总FETI(HTFETI)线性求解器。求解器的可伸缩性已在世界上几台最大的超级计算机上进行了测试。为了向所有潜在用户提供HTFETI算法的可扩展实现,开发并展示了一个简单的СAPI。本文介绍了API方法,编译和链接过程。作为概念验证,我们将ESPRESO与CSC ELMER求解器连接起来,并将其性能与ELMER FETI求解器进行了比较。 HTFETI执行两级分解,从而显着提高了内存利用率和求解器性能。为了选择最佳的二级分解,我们开发了一种可自动控制分解的性能模型。这是对所有用户的主要简化,可确保最佳求解器设置。我们显示,当在13 500 MPI进程(所罗门超级计算机的614计算节点)上运行并解决15亿个未知的3D线性弹性问题时,ESPRESO HTFETI求解器的速度比ELMER FETI求解器快3.7倍。

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