Simulation of shallow-water systems using graphics processing units

Lastra, Miguel; Mantas, José M.; Ureña, Cristóbal Pasadas; Castro, Manuel J.; Garcia-Rodriguez, Jose

doi:10.1016/j.matcom.2009.09.012

Cited by 40 publications

(21 citation statements)

References 16 publications

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“…There are previous works to port finite volume one-layer shallow water solvers to a GPU by using a graphics-specific programming language [4,5,6], but currently most of the proposals to simulate shallow flows on a single GPU are based on the CUDA programming model. A CUDA solver for onelayer system based on the first order finite volume scheme presented in [7] is described in [8] to deal with structured regular meshes.…”

Section: Introductionmentioning

confidence: 99%

An MPI-CUDA implementation of an improved Roe method for two-layer shallow water systems

Asunción

Mantas

Castro

et al. 2012

Journal of Parallel and Distributed Computing

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The numerical solution of two-layer shallow water systems is required to simulate accurately stratified fluids, which are ubiquitous in nature: they appear in atmospheric flows, ocean currents, oil spills, etc. Moreover, the implementation of the numerical schemes to solve these models in realistic scenarios imposes huge demands of computing power. In this paper, we tackle the acceleration of these simulations in triangular meshes by exploiting the combined power of several CUDA-enabled GPUs in a GPU cluster. For that purpose, an improvement of a path conservative Roe-type finite volume scheme which is specially suitable for GPU implementation is presented, and a distributed implementation of this scheme which uses CUDA and MPI to exploit the potential of a GPU cluster is developed. This implementation overlaps MPI communication with CPU-GPU memory transfers and GPU computation to increase efficiency. Several numerical experiments, performed on a cluster of modern CUDA-enabled GPUs, show the efficiency of the distributed solver.

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Section: Introductionmentioning

confidence: 99%

An MPI-CUDA implementation of an improved Roe method for two-layer shallow water systems

Asunción

Mantas

Castro

et al. 2012

Journal of Parallel and Distributed Computing

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“…Both versions are implemented in C++, and the Eigen library [4] is used for operating with matrices. We also have compared the CUDA implementations with the Cg program described in [7]. We have used the double data type in CPU.…”

Section: Resultsmentioning

confidence: 99%

“…In [6], an explicit central upwind scheme is implemented on a NVIDIA GeForce 7800 GTX card to simulate the one-layer shallow water system and a speedup from 15 to 30 is achieved with respect to a CPU implementation. An efficient implementation of the numerical scheme presented in [1] on GPUs is described in [7], obtaining two orders of magnitude speedup on a NVIDIA Geforce 8800 Ultra card with respect to a monoprocessor implementation. These previous proposals are based on the OpenGL graphics application programming interface [10] and the Cg shading language [5].…”

Section: Introductionmentioning

confidence: 99%

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Simulation of one-layer shallow water systems on multicore and CUDA architectures

2010

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The numerical solution of shallow water systems is useful for several applications related to geophysical flows, but the big dimensions of the domains suggests the use of powerful accelerators to obtain numerical results in reasonable times. This paper addresses how to speed up the numerical solution of a first order wellbalanced finite volume scheme for 2D one-layer shallow water systems by using modern Graphics Processing Units (GPUs) supporting the NVIDIA CUDA programming model. An algorithm which exploits the potential data parallelism of this method is presented and implemented using the CUDA model in single and double floating point precision. Numerical experiments show the high efficiency of this CUDA solver in comparison with a CPU parallel implementation of the solver and with respect to a previously existing GPU solver based on a shading language.

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“…Another important observation was that explicit schemes for hyperbolic conservation laws and balance laws are memory bound, and hence larger speedups were observed for high-resolution schemes that are more compute intensive than classical schemes like Lax-Friedrichs, Lax-Wendroff, etc. Since then, there have been several publications devoted to the use of GPUs for the shallow-water equations and other conservation and balance laws, see e.g., [1,2,5,10,15,16,22,26].…”

Section: Introductionmentioning

confidence: 99%

Simulation and visualization of the Saint-Venant system using GPUs

Brodtkorb

Hagen

Lie

et al. 2010

Comput. Visual Sci.

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We consider three high-resolution schemes for computing shallow-water waves as described by the SaintVenant system and discuss how to develop highly efficient implementations using graphical processing units (GPUs). The schemes are well-balanced for lake-at-rest problems, handle dry states, and support linear friction models. The first two schemes handle dry states by switching variables in the reconstruction step, so that bilinear reconstructions are computed using physical variables for small water depths and conserved variables elsewhere. In the third scheme, reconstructed slopes are modified in cells containing dry zones to ensure non-negative values at integration points. We discuss how single and double-precision arithmetics affect accuracy and efficiency, scalability and resource utilization for our implementations, and demonstrate that all three schemes map very well to current GPU hardware. We have also implemented direct and close-to-photo-realistic visualization of simulation results on the GPU, giving visual simulations with interactive speeds for reasonably-sized grids.

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Simulation of shallow-water systems using graphics processing units

Cited by 40 publications

References 16 publications

An MPI-CUDA implementation of an improved Roe method for two-layer shallow water systems

An MPI-CUDA implementation of an improved Roe method for two-layer shallow water systems

Simulation of one-layer shallow water systems on multicore and CUDA architectures

Simulation and visualization of the Saint-Venant system using GPUs

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