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Dual-Metric Partitioning with Adaptive Kernel Execution for Efficient GCN Acceleration
Graph Convolutional Networks (GCNs) are widely used for large graph-structured data, including social, citation, and e-commerce networks, but their deployment is constrained by irregular memory access and severe GPU workload imbalance. These challenges arise in two dimensions: width imbalance from p
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