Abstract
Smoothed Particle Hydrodynamics (SPH) is a numerical method commonly used in Computational Fluid Dynamics (CFD) to simulate complex free-surface flows. Simulations with this mesh-free particle method far exceed the capacity of a single processor. In this paper, as part of a dual-functioning code for either central processing units (CPUs) or Graphics Processor Units (GPUs), a parallelisation using GPUs is presented. The GPU parallelisation technique uses the Compute Unified Device Architecture (CUDA) of nVidia devices. Simulations with more than one million particles on a single GPU card exhibit speedups of up to two orders of magnitude over using a single-core CPU. It is demonstrated that the code achieves different speedups with different CUDA-enabled GPUs. The numerical behaviour of the SPH code is validated with a standard benchmark test case of dam break flow impacting on an obstacle where good agreement with the experimental results is observed. Both the achieved speed-ups and the quantitative agreement with experiments suggest that CUDA-based GPU programming can be used in SPH methods with efficiency and reliability.
Highlights
In the study of fluid mechanics, computational fluid dynamics (CFD) has become commonplace in industry and academic research to investigate flows of great complexity
We investigate the performance of the DualSPHysics code with a standard free-surface benchmark test for smoothed particle hydrodynamics (SPH) flows, a dam-break experiment, in order to demonstrate the reliability, capability, accuracy and efficiency of the central processing units (CPUs)-Graphics Processor Units (GPUs) solver
A CPU-GPU solver named DualSPHysics has been developed to deal with free-surface flow problems requiring high computational cost
Summary
In the study of fluid mechanics, computational fluid dynamics (CFD) has become commonplace in industry and academic research to investigate flows of great complexity. Numerous meshless methods have appeared and grown in popularity as they can be applied to problems that are highly nonlinear in arbitrarily complex geometries and are difficult for mesh-based methods. Instead of using a mesh, the SPH method uses a set of interpolation nodes placed arbitrarily within the fluid. This gives several advantages in comparison to meshbased methods when simulating nonlinear flow phenomena. The method uses discrete approximations to interpolation integrals to transform differential equations of fluid dynamics into particle summations. More complete reviews on standard SPH can be found at [3] and [4]
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