Goswami, PrashantNordin, AdrianNylén, SimonBujack, RoxanaTierny, JulienSadlo, Filip2022-06-022022-06-022022978-3-03868-175-51727-348Xhttps://doi.org/10.2312/pgv.20221062https://diglib.eg.org:443/handle/10.2312/pgv20221062This paper presents a novel Discrete Element Method (DEM) on the GPU for efficient snow simulation. To this end, our approach employs an iterative scheme on particles that easily allows the snow density to vary vastly for simulation while still maintaining a relatively large time step. We provide computationally inexpensive ways to capture cohesion and compression in the snow that enables us to generalize the behavior of various kinds of snow (like dry, wet, etc.) by varying physical parameters within the same simulator. We achieve a speed-up of nearly eight times with one million snow particles over the existing realtime method, even while dealing with scenes containing complex object boundaries. Furthermore, our simulator not only retains stability at these large time steps but also improves upon the physical behavior of the existing method. We have also conducted a user evaluation of our approach, where a majority of the participants voted in favor of its realism value for computer games.Attribution 4.0 International LicenseCCS Concepts: Computing methodologies --> Physical simulationComputing methodologiesPhysical simulation10.2312/pgv.2022106219-2911 pages