A Research on Particle-Based Parallel Methods for Fluid Animation

In this paper, we present an acceleration strategy for Smoothed Particle Hydrodynamics (SPH) on multi-GPU platform. For single-GPU, we first use a neighborhood search algorithm of compacting cell index combined with spatial domain characteristics. For multi-GPU, we focus on the changing patterns of SPH's computational time. Simple dynamic load balancing algorithm works well because the computational time of each time step changes slowly compared to previous time step. By further optimizing dynamic load balancing algorithm and the communication strategy among GPUs, a nearly linear speedup is achieved in different scenarios with a scale of millions particles. The quality and efficiency of our methods are demonstrated using multiple scenes with different particle numbers.