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arXiv 2101.01231math.NAcs.NA
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拟Quadrature自由矩阵组区域隐式间断Galerkin方法的并行尺度变换

Parallel Scaling of the Regionally-Implicit Discontinuous Galerkin Method with Quasi-Quadrature-Free Matrix Assembly

Andrew J. Christlieb, Pierson T. Guthrey, James A. Rossmanith

摘要:

在这项工作中,我们调查的并行可扩展性的数值方法开发的Guthrey和Rossmanith [区域隐式间断Galerkin方法:提高稳定性的DG-FEM,SIAM J. Numer。Anal.(2019)]。我们开发了一个区域隐式间断伽辽金(RIDG)方法在DoGPack,这是一个开源的C++软件包间断伽辽金方法的实现。具体来说,我们开发和测试的混合型的OpenMP和MPI并行实现的DoGPack的目标,探索的效率和可扩展性的RIDG比较流行的强稳定性保持龙格库塔间断伽辽金(SSP-RKDG)方法。我们证明,RIDG方法能够隐藏与分布式内存并行性相关的通信延迟,由于这样的事实,即几乎所有的方法中涉及的工作是高度本地化的每个元素,每个区域产生本地化的预测。我们证明了增强的效率和可扩展性的RIDG方法,并将其与SSP-RKDG方法进行比较,并显示可扩展性非常高阶的计划。二维扩展研究是在密歇根州立大学网络支持研究所的机器上进行的,使用了英特尔®至强® Gold 6148 CPU@2.40 GHz CPU上的多达1440个核心。三维扩展研究是在劳伦斯利弗莫尔国家实验室的利弗莫尔计算集群上进行的,使用了英特尔至强CLX-8276 L CPU上的28672个内核,采用Omni-Path互连。

英文摘要:

In this work we investigate the parallel scalability of the numerical method developed in Guthrey and Rossmanith [The regionally implicit discontinuous Galerkin method: Improving the stability of DG-FEM, SIAM J. Numer. Anal. (2019)]. We develop an implementation of the regionally-implicit discontinuous Galerkin (RIDG) method in DoGPack, which is an open source C++ software package for discontinuous Galerkin methods. Specifically, we develop and test a hybrid OpenMP and MPI parallelized implementation of DoGPack with the goal of exploring the efficiency and scalability of RIDG in comparison to the popular strong stability-preserving Runge-Kutta discontinuous Galerkin (SSP-RKDG) method. We demonstrate that RIDG methods are able to hide communication latency associated with distributed memory parallelism, due to the fact that almost all of the work involved in the method is highly localized to each element, producing a localized prediction for each region. We demonstrate the enhanced efficiency and scalability of the of the RIDG method and compare it to SSP-RKDG methods and show extensibility to very high order schemes. The two-dimensional scaling study is performed on machines at the Institute for Cyber-Enabled Research at Michigan State University, using up to 1440 total cores on Intel(R) Xeon(R) Gold 6148 CPU @ 2.40GHz CPUs. The three dimensional scaling study is performed on Livermore Computing clusters at at Lawrence Livermore National Laboratory, using up to 28672 total cores on Intel Xeon CLX-8276L CPUs with Omni-Path interconnects.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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