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cs.AR2023
A Survey of Graph Pre-processing Methods: From Algorithmic to Hardware Perspectives
Zhengyang Lv, Mingyu Yan, Xin Liu +4
Graph-related applications have experienced significant growth in academia and industry, driven by the powerful representation capabilities of graph. However, efficiently executing…
cs.AR2023
HiHGNN: Accelerating HGNNs through Parallelism and Data Reusability Exploitation
Runzhen Xue, Dengke Han, Mingyu Yan +8
Heterogeneous graph neural networks (HGNNs) have emerged as powerful algorithms for processing heterogeneous graphs (HetGs), widely used in many critical fields. To capture both st…