DCGrid: An Adaptive Grid Structure ... (I3D 2022) – Conference Presentation

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#DCGrid: An #AdaptiveGrid Structure for Memory-Constrained #FluidSimulation on the #GPU (#I3D2022)

Wouter Raateland¹, Torsten Hädrich², Jorge Alejandro Amador Herrera², Daniel T. Banuti³, Wojciech Pałubicki⁴, Sören Pirk⁵, Klaus Hildebrandt¹, Dominik L. Michels²

¹#TUDelft
²#KAUST Visual Computing Center
³#UNM
⁴#UAM
⁵#Google Research

Project Page: http://computationalsciences.org/publications/raateland-2022-dc-grid.html

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.

Видео DCGrid: An Adaptive Grid Structure ... (I3D 2022) – Conference Presentation канала KAUST Computational Sciences