A multi-GPU shallow-water simulation with transport of contaminants

This work presents cost-effective multi-GPU parallel implementations of a finite volume numerical scheme for solving pollutant transport problems in bidimensional domains. The fluid is modelled by 2D shallow water equations, while the transport of pollutant is modelled by a transport equation. The 2D domain is discretized using a first order Roe finite volume scheme. Specifically, this paper presents multi-GPU implementations of both a solution that exploits recomputation on the GPU, and an optimized solution that is based on a ghost cell decoupling approach. Our multi-GPU implementations have been optimized using nonblocking communications, overlapping communications and computations, and applying ghost cell expansion in order to minimize communications. The fastest one reached a speedup of 78x using 4 GPUs on an Infiniband network with respect to a parallel execution on a multicore CPU with 6 cores and 2way hyperthreading per core. Such performance, measured using a realistic problem, enabled the calculation of solutions not only in real-time, but orders of magnitude faster than the simulated time. Copyright c © 2012 John Wiley & Sons, Ltd.