Simulation of tsunamis generated by landslides using adaptive mesh refinement on GPU

Adaptive mesh refinement (AMR) is a widely used technique to accelerate computationally intensive simulations, which consists of dynamically increasing the spatial resolution of the areas of interest of the domain as the simulation advances. During the last years there have appeared many publications that tackle the implementation of AMR-based applications in GPUs in order to take advantage of their massively parallel architecture. In this paper we present the first AMR-based application implemented on GPU for the simulation of tsunamis generated by landslides by using a two-layer shallow water system. We also propose a new strategy for the interpolation and projection of the values of the fine cells in the AMR algorithm based on the fluctuations of the state values instead of the usual approach of considering the current state values. Numerical experiments on artificial and realistic problems show the validity and efficiency of the solver.