H-GAT: A Hardware-Efficient Accelerator for Graph Attention Networks
Recently, Graph Attention Networks (GATs) have shown good performance for representation learning on graphs. Furthermore, GAT leverage the masked self-attention mechanism to get a more advanced feature representation than the graph convolution networks (GCNs). However, GAT incurs large amounts of ir...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Tamkang University Press
2024-01-01
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| Series: | Journal of Applied Science and Engineering |
| Subjects: | |
| Online Access: | http://jase.tku.edu.tw/articles/jase-202403-27-3-0010 |