  This paper shows the development of a multi-GPU version of a time-explicit
finite volume solver for the Shallow-Water Equations (SWE) on a multi-GPU
architecture. MPI is combined with CUDA-Fortran in order to use as many GPUs as
needed. The METIS library is leveraged to perform a domain decomposition on the
2D unstructured triangular meshes of interest. A CUDA-Aware OpenMPI version is
adopted to speed up the messages between the MPI processes. A study of both
speed-up and efficiency is conducted; first, for a classic dam-break flow in a
canal, and then for two real domains with complex bathymetries: the Mille
\^Iles river and the Montreal archipelago. In both cases, meshes with up to 13
million cells are used. Using 24 to 28 GPUs on these meshes leads to an
efficiency of 80% and more. Finally, the multi-GPU version is compared to the
pure MPI multi-CPU version, and it is concluded that in this particular case,
about 100 CPU cores would be needed to achieve the same performance as one GPU.
