Improved FVM for two-layer shallow-water models: Application to the Strait of Gibraltar
Advances in Engineering Software
Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation)
Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation)
Journal of Computational and Applied Mathematics
Two-Layer Shallow Water System: A Relaxation Approach
SIAM Journal on Scientific Computing
Simulation of shallow-water systems using graphics processing units
Mathematics and Computers in Simulation
Finite-Volume Solvers for a Multilayer Saint-Venant System
International Journal of Applied Mathematics and Computer Science - Scientific Computation for Fluid Mechanics and Hyperbolic Systems
Shallow water simulations on multiple GPUs
PARA'10 Proceedings of the 10th international conference on Applied Parallel and Scientific Computing - Volume 2
An MPI-CUDA implementation of an improved Roe method for two-layer shallow water systems
Journal of Parallel and Distributed Computing
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The two-layer shallow water system is used as the numerical model to simulate several phenomena related to geophysical flows such as the steady exchange of two different water flows, as occurs in the Strait of Gibraltar, or the tsunamis generated by underwater landslides. The numerical solution of this model for realistic domains imposes great demands of computing power and modern Graphics Processing Units (GPUs) have demonstrated to be a powerful accelerator for this kind of computationally intensive simulations. This work describes an accelerated implementation of a first order well-balanced finite volume scheme for 2D two-layer shallow water systems using GPUs supporting the CUDA (Compute Unified Device Architecture) programming model and double precision arithmetic. This implementation uses the CUDA framewok to exploit efficiently the potential fine-grain data parallelism of the numerical algorithm. Two versions of the GPU solver are implemented and studied: one using both single and double precision, and another using only double precision. Numerical experiments show the efficiency of this CUDA solver on several GPUs and a comparison with an efficient multicore CPU implementation of the solver is also reported.