GPU Cluster for High Performance Computing
Proceedings of the 2004 ACM/IEEE conference on Supercomputing
TeraFLOP computing on a desktop PC with GPUs for 3D CFD
International Journal of Computational Fluid Dynamics - Mesoscopic Methods And Their Applications To CFD
LBM based flow simulation using GPU computing processor
Computers & Mathematics with Applications
VECPAR'10 Proceedings of the 9th international conference on High performance computing for computational science
A new approach to the lattice Boltzmann method for graphics processing units
Computers & Mathematics with Applications
The TheLMA project: Multi-GPU implementation of the lattice Boltzmann method
International Journal of High Performance Computing Applications
Multi-GPU implementation of the lattice Boltzmann method
Computers & Mathematics with Applications
Editorial: Mesoscopic Methods in Engineering and Science
Computers & Mathematics with Applications
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Interpolated bounce-back boundary conditions for the lattice Boltzmann method (LBM) make the accurate representation of complex geometries possible. In the present work, we describe an implementation of a linearly interpolated bounce-back (LIBB) boundary condition for graphics processing units (GPUs). To validate our code, we simulated the flow past a sphere in a square channel. At low Reynolds numbers, results are in good agreement with experimental data. Moreover, we give an estimate of the critical Reynolds number for transition from steady to periodic flow. Performance recorded on a single node server with eight GPU based computing devices ranged up to 2.63x10^9 fluid node updates per second. Comparison with a simple bounce-back version of the solver shows that the impact of LIBB on performance is fairly low.