GPU-based parallel algorithm for particle contact detection and its application in self-compacting concrete flow simulations

In the present paper, we propose a novel parallel graphic processing unit (GPU)-friendly algorithm for contact detection. We develop a GPU-discrete element method (GPU–DEM) platform for self-compacting concrete (SCC) flow simulations. The algorithm takes full advantage of the parallel architecture of the GPU and can rapidly perform contact detection than that using CPU algorithm. Its scalability and robustness make it suitable for particle contact detection for different particle size distributions. The proposed GPU–DEM platform implements all the steps of DEM on GPU, which prevents the transfer of data between GPU and CPU. The proposed methodology is expected to be relevant in computational mechanics with applications to SCC flow simulations, where the number of particles ranges from millions to billions.

► The GPU algorithm for contact detection is tremendous faster than CPU algorithm. ► The maximum speed-up ratio can reach 73. ► We establish a GPU–DEM platform to execute SCC flow simulations on the GPU. ► The GPU–DEM platform implements all the steps of DEM on the GPU.