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Hierarchical Differentiable Fluid Simulation

Xiangyu Kong * , Arnaud Schoentgen , Damien Rioux-Lavoie , Paul G. Kry , Derek Nowrouzezahrai

Published in Computer Graphics Forum, 2025

Teaser

Differentiable simulation is an emerging field that offers a powerful and flexible route to fluid control. In grid-based settings, high memory consumption is a long-standing bottleneck that constrains optimization resolution. We introduce a two-step algorithm that significantly reduces memory usage: our method first optimizes for bulk forces at reduced resolution, then refines local details over sub-domains while maintaining differentiability. In trading runtime for memory, it enables optimization at previously unattainable resolutions. We validate its effectiveness and memory savings on a series of fluid control problems.

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