Laboratoire de Mécanique des Fluides et d'Acoustique - UMR 5509

LMFA - UMR 5509
Laboratoire de Mécanique des Fluides et d’Acoustique
Lyon
France


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Accueil > Équipes > Turbulence & Instabilités > Publications T&I et posters doctorants > Publications T&I 2020

Article dans J. of Physics : Conf. Series (2020)

In situ analysis and visualization of massively parallel simulations of transitional and turbulent flows

Anne Cadiou, Marc Buffat, Christophe Pera, Bastien Di Pierro, Frédéric Alizard & Lionel Le Penven

In situ analysis and visualization of massively parallel simulations of transitional and turbulent flows

The increase of computational resources with the generalization of massively parallel supercomputers benefits to various fields of physics among which turbulence and fluid mechanics, making it possible to increase time and space accuracy and gain further knowledge in fundamental mechanisms. Parametric studies, high fidelity statistics, high resolutions, can be realized. However, this access poses many problems in terms of data management, analysis and visualization. Traditional workflow, consisting of writing raw data on disks and performing post-processing to extract physical quantities of interest, considerably slows down the analysis, if not becomes impossible, because of data transfer, storage and re-accessibility issues. This is particularly difficult when it comes to visualization. Usage has to be revisited to maintain consistency with the accuracy of the computation step and in this context, in situ processing is a promising approach. We developed an in situ analysis and visualization strategy with an hybrid method for transitional and turbulent flow analysis with a pseudo-spectral solver. It is shown to have a low impact on computational time with a reasonable increase of resource usage, while enriching data exploration. Large time sequences have been analyzed. This could not have been achieved with the traditional workflow. Moreover, computational steering has been performed with real-time adjustment of the simulations, thereby getting closer to a numerical experiment process.

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