MQ-GNN: A Multi-Queue Pipelined Architecture for Scalable and Efficient GNN Training
Graph Neural Networks (GNNs) are powerful tools for learning graph-structured data, but their scalability is hindered by inefficient mini-batch generation, data transfer bottlenecks, and costly inter-GPU synchronization. Existing training frameworks fail to overlap these stages, leading to suboptima...
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| Auteurs principaux: | , |
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| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
IEEE
2025-01-01
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| Collection: | IEEE Access |
| Sujets: | |
| Accès en ligne: | https://ieeexplore.ieee.org/document/10877815/ |
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