A distributed equivariant GNN with a neighbor-minimizing graph partitioner scales electronic-structure (Hamiltonian) prediction to 512 GPUs and 190,000 atoms, with an 87% weak-scaling efficiency.
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Distributed Equivariant Graph Neural Networks for Large-Scale Electronic Structure Prediction
A distributed equivariant GNN with a neighbor-minimizing graph partitioner scales electronic-structure (Hamiltonian) prediction to 512 GPUs and 190,000 atoms, with an 87% weak-scaling efficiency.