Abstract
Massively parallel simulations generate increasing volumes of large data, whose exploitation requires large storage resources, efficient network and increasingly large post-processing facilities. In the coming era of exascale computations, there is an emerging need for new data analysis and visualization strategies. In order to meet these challenges, an original solution based on Python and open-source libraries has been developed. It is shown to make it possible to embed analysis and visualization into the code and efficiently shorten the exploitation of massively parallel computations. Applications are given for direct numerical simulations of turbulent and transitional flows.
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Acknowledgements
The authors thank the computer center P2CHPD at “Université Claude Bernard Lyon 1”, member of the “Fédération Lyonnaise de Modélisation et Sciences Numériques” (FLMSN), for providing computer facilities.
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Cadiou, A., Buffat, M., Di Pierro, B., Penven, L.L., Pera, C. (2018). A New Strategy for Analysis and Visualization of Massively Parallel Computations of Turbulent and Transitional Flows. In: Deville, M., et al. Turbulence and Interactions. TI 2015. Notes on Numerical Fluid Mechanics and Multidisciplinary Design, vol 135. Springer, Cham. https://doi.org/10.1007/978-3-319-60387-2_9
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DOI: https://doi.org/10.1007/978-3-319-60387-2_9
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