A GPU accelerated code for fluid flow simulations algorithm

The advances of graphics processing units (GPU) technology have granted a recent enhancement in the parallel programming field. However, the use of GPU devices in fluid flow simulations is still in the development phase. The present paper proposes a CUDA-C-based simulation algorithm to demonstrate GPU devices potential in solving the Navier-Stokes equations. The proposed methodology is exemplified on a classical approach of the lid-driven cavity problem. This paper uses different grid resolutions and Reynolds numbers to investigate the performance of the proposed method against state-of-the-art techniques. The results show that the SOR-M procedure has contributed to the enhancement of the convergence rate. In particular, a time reduction of about 22.5\% is achieved when the SOR-M algorithm is applied. Moreover, the overall method has shown to be 13-25 times faster than CPU-based codes. In conclusion, the SOR-M procedure can significantly increase the GPU performance in solving fluid flow problems.