X-MeshGraphNet trains large physics-surrogate GNNs by partitioning graphs with halo regions, builds graphs from point clouds instead of meshes, and demonstrates scaling to 512 GPUs on car aerodynamics.
Learning reduced-order models for cardiovascular simulations with graph neural networks,
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X-MeshGraphNet: Scalable Multi-Scale Graph Neural Networks for Physics Simulation
X-MeshGraphNet trains large physics-surrogate GNNs by partitioning graphs with halo regions, builds graphs from point clouds instead of meshes, and demonstrates scaling to 512 GPUs on car aerodynamics.