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Previous implementations are not fast enough to evaluate multiple scenarios for a robust, uncertainty-aware decision support. To tackle this, we exploit the capabilities of the NVIDIA Kepler architecture. We implement a scheme developed by Kurganov and Petrova (KP07) and a newer, improved version by Horv\u00e1th et al. (HWP14). The KP07 scheme is simpler but suffers from incorrect high velocities along the wet\/dry boundaries, resulting in small time steps and long simulation runtimes. The HWP14 scheme resolves this problem but comprises a more complex algorithm. Previous work has shown that HWP14 has the potential to outperform KP07, but no practical implementation has been provided. The novel shuffle-based implementation of HWP14 presented here takes advantage of its accuracy and performance capabilities for real-world usage. The correctness and performance are validated on real-world scenarios.<\/jats:p>","DOI":"10.1177\/1094342016630800","type":"journal-article","created":{"date-parts":[[2016,2,16]],"date-time":"2016-02-16T20:43:18Z","timestamp":1455655398000},"page":"379-395","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":15,"title":["Kepler shuffle for real-world flood simulations on GPUs"],"prefix":"10.1177","volume":"30","author":[{"given":"Zsolt","family":"Horv\u00e1th","sequence":"first","affiliation":[{"name":"Vienna University of Technology, Karlsplatz, Austria"},{"name":"VRVis Zentrum f\u00fcr Virtual Reality und Visualisierung Forschungs-GmbH, Vienna, Austria"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rui AP","family":"Perdig\u00e3o","sequence":"additional","affiliation":[{"name":"Vienna University of Technology, Karlsplatz, 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