DCGrid
An Adaptive Grid Structure for Memory-Constrained Fluid Simulation on the GPU
Wouter Raateland (Student TU Delft)
Torsten Hädrich (King Abdullah University of Science and Technology)
Jorge Alejandro Amador Herrera (King Abdullah University of Science and Technology)
Daniel T. Banuti (University of New Mexico)
Wojciech Pałubicki (Adam Mickiewicz-Universiteit )
Sören Pirk (Google LLC)
Klaus Hildebrandt (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Dominik L. Michels (King Abdullah University of Science and Technology)
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Abstract
We introduce Dynamic Constrained Grid (DCGrid), a hierarchical and adaptive grid structure for fluid simulation combined with a scheme for effectively managing the grid adaptations. DCGrid is designed to be implemented on the GPU and used in high-performance simulations. Specifically, it allows us to efficiently vary and adjust the grid resolution across the spatial domain and to rapidly evaluate local stencils and individual cells in a GPU implementation. A special feature of DCGrid is that the control of the grid adaption is modeled as an optimization under a constraint on the maximum available memory, which addresses the memory limitations in GPU-based simulation. To further advance the use of DCGrid in high-performance simulations, we complement DCGrid with an efficient scheme for approximating collisions between fluids and static solids on cells with different resolutions. We demonstrate the effectiveness of DCGrid for smoke flows and complex cloud simulations in which terrain-atmosphere interaction requires working with cells of varying resolution and rapidly changing conditions. Finally, we compare the performance of DCGrid to that of alternative adaptive grid structures.
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