Name
Abstract | ||
|---|---|---|
We introduce efficient, large scale fluid simulation on GPU hardware using the fluid-implicit particle (FLIP) method over a sparse hierarchy of grids represented in NVIDIA((R)) GVDB Voxels. Our approach handles tens of millions of particles within a virtually unbounded simulation domain. We describe novel techniques for parallel sparse grid hierarchy construction and fast incremental updates on the GPU for moving particles. In addition, our FLIP technique introduces sparse, work efficient parallel data gathering from particle to voxel, and a matrix-free GPU-based conjugate gradient solver optimized for sparse grids. Our results show that our method can achieve up to an order of magnitude faster simulations on the GPU as compared to FLIP simulations running on the CPU. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1111/cgf.13350 | COMPUTER GRAPHICS FORUM |
Field | DocType | Volume |
Computing Methodologies,Computer science,Theoretical computer science,Computational science | Journal | 37.0 |
Issue | ISSN | Citations |
2.0 | 0167-7055 | 3 |
PageRank | References | Authors |
0.36 | 28 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kui Wu | 1 | 318 | 18.44 |
| Nghia Truong | 2 | 3 | 1.04 |
| Cem Yuksel | 3 | 264 | 30.15 |
| Rama Hoetzlein | 4 | 15 | 1.71 |