A greedy L1-imbalance rebalancing algorithm provably restores 2-constraint hypergraph partition balance and, in Mt-KaHyPar, cuts average connectivity by 11.5% versus Metis.
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2 Pith papers cite this work, alongside 344 external citations. Polarity classification is still indexing.
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GPU algorithm for hypergraph partitioning with size and distinct hyperedge constraints achieves 380x speedup and 1.2-2.0x better connectivity than sequential methods.
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High-Quality Multi-Constraint Hypergraph Partitioning via Greedy Rebalancing
A greedy L1-imbalance rebalancing algorithm provably restores 2-constraint hypergraph partition balance and, in Mt-KaHyPar, cuts average connectivity by 11.5% versus Metis.
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Hypergraph Partitioning on GPU with Distinct Incident Hyperedges and Size Constraints
GPU algorithm for hypergraph partitioning with size and distinct hyperedge constraints achieves 380x speedup and 1.2-2.0x better connectivity than sequential methods.