University of North Carolina at Chapel Hill1 University of California, Berkeley2 Intel Corporation3
SIGGRAPH Asia 2012
Simulating fluids in large-scale scenes with appreciable quality using
state-of-the-art methods can lead to high memory and compute
requirements. Since memory requirements are proportional to the
product of domain dimensions, simulation performance is limited
by memory access, as solvers for elliptic problems are not compute-bound on modern systems. This is a significant concern for large-scale scenes. To reduce the memory footprint and memory/compute
ratio, vortex singularity bases can be used. Though they form a
compact bases for incompressible vector fields, robust and efficient
modeling of nonrigid obstacles and free-surfaces can be challenging
with these methods.
We propose a hybrid domain decomposition approach that couples Eulerian velocity-based simulations with vortex singularity simulations. Our formulation reduces memory footprint by using smaller Eulerian domains with compact vortex bases, thereby improving the memory/compute ratio, and simulation performance by more than 1000x for single phase flows as well as significant improvements for free-surface scenes. Coupling these two heterogeneous methods also affords flexibility in using the most appropriate method for modeling different scene features, as well as allowing robust interaction of vortex methods with free-surfaces and nonrigid obstacles.
Abhinav Golas, Rahul Narain, Jason Sewall, Pavel Krajcevski, Pradeep Dubey, and Ming C. Lin, 2012. Large-scale Fluid Simulation using Velocity-Vorticity Domain Decomposition. In ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia 2012), vol. 31, no. 6.
Preprint (PDF, 3.1 MB)
Video (QuickTime, H264, 214 MB)
Abhinav Golas, Rahul Narain, Jason Sewall, Pavel Krajcevski, and Ming C. Lin, 2012. Efficient Large-scale Hybrid Fluid Simulation. ACM SIGGRAPH 2012 Technical Talks.