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A Graph Neural Network Method for Fast ECO Leakage Power Optimization

  • Published:2022-01-17 Issue: Volume: Page:
  • ISSN:
  • Container-title:2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC)
  • language:
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Author:

Wang Kai1,Cao Peng1

Affiliation:

1. Southeast University,National ASIC System Engineering Technology Research Center,Nanjing,China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Jiangsu Natural Science Foundation

Publisher

IEEE

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Heterogeneous Graph Attention Network Based Statistical Timing Library Characterization with Parasitic RC Reduction;2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC);2024-01-22

2. Efficient and Accurate ECO Leakage Optimization Framework With GNN and Bidirectional LSTM;IEEE Transactions on Very Large Scale Integration (VLSI) Systems;2023-09

3. DAGSizer: A Directed Graph Convolutional Network Approach to Discrete Gate Sizing of VLSI Graphs;ACM Transactions on Design Automation of Electronic Systems;2022-12-16

4. ECO-GNN: Signoff Power Prediction using Graph Neural Networks with Subgraph Approximation;ACM Transactions on Design Automation of Electronic Systems;2022-10-27
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