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graph partitioning

Graph Partitioning is generally the first step of distributed graph computing tasks. The targets are load-balance and minimizing the communication volume.

Papers

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Showing 31–40 of 208 papers

TitleStatusHype
A Random-Key Optimizer for Combinatorial Optimization—0
VLSI Hypergraph Partitioning with Deep Learning—0
Towards Faster Graph Partitioning via Pre-training and Inductive InferenceCode0
Revisiting Surgical Instrument Segmentation Without Human Intervention: A Graph Partitioning ViewCode0
Quantum Annealing based Power Grid Partitioning for Parallel Simulation—0
LSM-GNN: Large-scale Storage-based Multi-GPU GNN Training by Optimizing Data Transfer Scheme—0
Distributed Training of Large Graph Neural Networks with Variable Communication Rates—0
Causal Discovery over High-Dimensional Structured Hypothesis Spaces with Causal Graph PartitioningCode0
FastGAS: Fast Graph-based Annotation Selection for In-Context Learning—0
A random-key GRASP for combinatorial optimizationCode0
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