We present a GPU-based turbulent flow simulation by link-wise artificial compressibility method (LW-ACM). The standard implementations of the lattice Boltzmann method are limited by memory requirements due to the nature of the distribution functions employed. LW-ACM avoids the need to store the density distribution function via the use of a hybrid of LBM and finite difference method. This method, previously used only for simple cases without inlet/outlet boundary conditions, is here extended for general-purpose 3D turbulent flow via the introduction of the synthetic eddy method (SEM) as a distributed source term into the channel. A channel flow is performed to validate the implementation in this paper. Experimental results demonstrate performance on a single GPU of up to 11237 MLUPS and 4656 MLUPS in single and double precision, respectively, amongst the fastest results reported to date, demonstrating the practical opportunities this approach can offer for systematic evaluation of complex turbulent flow.
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