By the same authors

From the same journal

An Unstructured CFD Mini-Application for the Performance Prediction of a Production CFD Code

Research output: Contribution to journalArticlepeer-review



Publication details

JournalConcurrency and Computation: Practice and Experience
DateAccepted/In press - 24 Jun 2019
DateE-pub ahead of print - 12 Jul 2019
DatePublished (current) - 25 May 2020
Issue number10
Number of pages14
Early online date12/07/19
Original languageEnglish


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.

Bibliographical note

© 2019 The Authors

    Research areas

  • computational fluid dynamics, high performance computing, mini-application, performance analysis, performance modeling, scientific computing

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