DCGrid

An Adaptive Grid Structure for Memory-Constrained Fluid Simulation on the GPU

Journal Article (2022)
Author(s)

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 - Computer Graphics and Visualisation)

Dominik L. Michels (King Abdullah University of Science and Technology)

Research Group
Computer Graphics and Visualisation
DOI related publication
https://doi.org/10.1145/3522608
More Info
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Publication Year
2022
Language
English
Research Group
Computer Graphics and Visualisation
Issue number
1
Volume number
5
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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.