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An unstructured CFD mini-application for the performance prediction of a production CFD code

机译:非结构化CFD微型应用程序,用于预测生产CFD代码的性能

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Maintaining the performance of large scientific codes is a difficult task. To aid in this task, a number of mini-applications have been developed that are more tractable to analyze than large-scale production codes while retaining the performance characteristics of them. These "mini-apps" also enable faster hardware evaluation and, for sensitive commercial codes, allow evaluation of code and system changes outside of access approval processes. In this paper, we develop MG-CFD, a mini-application that represents a geometric multigrid, unstructured computational fluid dynamics (CFD) code, designed to exhibit similar performance characteristics without sharing commercially sensitive code. We detail our experiences of developing this application using guidelines detailed in existing research and contributing further to these. Our application is validated against the inviscid flux routine of HYDRA, a CFD code developed by Rolls-Royce plc for turbomachinery design. This paper (1) documents the development of MG-CFD, (2) introduces an associated performance model with which it is possible to assess the performance of HYDRA on new HPC architectures, and (3) demonstrates that it is possible to use MG-CFD and the performance models to predict the performance of HYDRA with a mean error of 9.2% for strong-scaling studies.
机译:维持大型科学规范的性能是一项艰巨的任务。为了帮助完成此任务,已经开发了许多微型应用程序,它们比大规模生产代码更易于分析,同时保留了它们的性能特征。这些“微型应用程序”还可以加快硬件评估速度,对于敏感的商业代码,还可以在访问批准流程之外评估代码和系统更改。在本文中,我们开发了MG-CFD,这是一个微型应用程序,代表几何多网格,非结构化计算流体动力学(CFD)代码,旨在显示相似的性能特征而无需共享商业敏感的代码。我们使用现有研究中详述的指南详细介绍了开发此应用程序的经验,并对此做出了进一步贡献。我们的应用已针对HYDRA的无粘性通量例程进行了验证,该例程是由Rolls-Royce plc为涡轮机械设计开发的CFD代码。本文(1)记录了MG-CFD的发展,(2)介绍了一个相关的性能模型,通过该模型可以评估HYDRA在新的HPC架构上的性能,并且(3)证明可以使用MG-CFD CFD和性能模型可预测HYDRA的性能,对于大规模研究而言,其平均误差为9.2%。

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