Preprints
https://doi.org/10.5194/gmd-2024-152
https://doi.org/10.5194/gmd-2024-152
Submitted as: development and technical paper
 | 
16 Oct 2024
Submitted as: development and technical paper |  | 16 Oct 2024
Status: this preprint is currently under review for the journal GMD.

LISFLOOD-FP 8.2: GPU-accelerated multiwavelet discontinuous Galerkin solver with dynamic resolution adaptivity for rapid, multiscale flood simulation

Alovya Chowdhury and Georges Kesserwani

Abstract. The second-order discontinuous Galerkin (DG2) solver of the shallow water equations in LISFLOOD-FP 8.0 is well-suited for predicting small-scale transients that emerge in rapid, multiscale floods caused by impact events like tsunamis. However, this DG2 solver can only be used for simulations on a uniform grid where it may yield inefficient runtimes even when using its graphics processing unit (GPU) parallelised version (GPU-DG2). To maximise runtime reduction, the LISFLOOD-FP 8.2 version integrates GPU parallelised dynamic (in time) grid resolution adaptivity of multiwavelets (MW) with the DG2 solver (GPU-MWDG2). The GPU-MWDG2 solver requires selecting a maximum refinement level, L, based on size and resolution of the Digital Elevation Model (DEM) and an error threshold, ε ≤ 10-3, to preserve similar accuracy as a GPU-DG2 simulation on a uniform grid. The accuracy and efficiency of dynamic GPU-MWDG2 adaptivity is assessed for four tsunami-induced flooding test cases involving increasingly complex tsunamis: from single-wave impact events to wave trains. At ε = 10-3, the GPU-MWDG2 simulations yield predictions similar to the GPU-DG2 simulations but using ε = 10-4 can improve the accuracy in velocity-related predictions. In terms of efficiency, the GPU-MWDG2 simulations show progressively larger speedups over the GPU-DG2 simulations from L ≥ 10, which become significant (≥ 3.3- and 4.5-fold at ε = 10-4 and 10-3 , respectively) for simulating a single-wave impact event. The LISFLOOD-FP 8.2 code is open source, DOI: 10.5281/zenodo.4073010, as well as the simulation data and the input files and scripts to reproduce them, DOI: 10.5281/zenodo.13909072, with additional documentation at https://www.seamlesswave.com/Adaptive (last accessed: 9 October 2024).

Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.
Alovya Chowdhury and Georges Kesserwani

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2024-152', Anonymous Referee #1, 18 Oct 2024
  • RC2: 'Comment on gmd-2024-152', Anonymous Referee #2, 11 Nov 2024
  • RC3: 'Comment on gmd-2024-152', Anonymous Referee #3, 30 Nov 2024
Alovya Chowdhury and Georges Kesserwani
Alovya Chowdhury and Georges Kesserwani

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Short summary
LISFLOOD-FP 8.2 is a framework for running real-world simulations of rapid, multiscale floods driven by impact events like tsunamis. It builds on the LISFLOOD-FP 8.0 and 8.1 papers published in GMD: whereas LISFLOOD-FP 8.0 focussed on GPU-parallelisation, and LISFLOOD-FP 8.1 focussed on static mesh adaptivity of (multi)wavelets, LISFLOOD-FP 8.2 combines GPU-parallelisation with multiwavelet dynamic mesh adaptivity to drastically reduce simulation runtimes, achieving up to a 4.5-fold speedup.