Fluid Simulation with Adaptive Staggered Power Particles on GPUs

This paper extends the recently proposed power-particle-based fluid simulation method with staggered discretization, GPU implementation, and adaptive sampling, largely enhancing the efficiency and usability of the method. In contrast to the original formulation which uses co-located pressures and velocities, in this paper, a staggered scheme is adapted to the Power Particles to benefit visual details and computing efficiency. Meanwhile, we propose a novel facet-based power diagrams construction algorithm suitable for parallelization and explore its GPU implementation, achieving an order of magnitude boost in performance over the existing code library. In addition, to utilize the potential of Power Particles to control individual cell volume, we apply adaptive particle sampling to improve the detail level with varying resolution. The proposed method can be entirely carried out on GPUs, and our extensive experiments validate our method both in terms of efficiency and visual quality.