CongestionNet: Routing Congestion Prediction Using Deep Graph Neural Networks-Reference-Cited by-同舟云学术

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CongestionNet: Routing Congestion Prediction Using Deep Graph Neural Networks

Published:2019-10 Issue: Volume: Page:
ISSN:
Container-title:2019 IFIP/IEEE 27th International Conference on Very Large Scale Integration (VLSI-SoC)
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Author:

Kirby Robert,Godil Saad,Roy Rajarshi,Catanzaro Bryan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8910139/8920290/08920342.pdf?arnumber=8920342

Cited by 47 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. Opportunities and challenges of graph neural networks in electrical engineering;Nature Reviews Electrical Engineering;2024-08-05

2. Generalizable and Relation Sensitive Netlist Representation for Analog Circuit Design;Proceedings of the Great Lakes Symposium on VLSI 2024;2024-06-12

3. ANN-based Accurate and Fast Post-Route QoR Data Prediction Methodology from Pre-Clock Tree Synthesis by Skipping CTS and Routing;2024 IEEE International Symposium on Circuits and Systems (ISCAS);2024-05-19

4. Routing Congestion Prediction in VLSI Design Using Graph Neural Networks;2024 26th International Conference on Digital Signal Processing and its Applications (DSPA);2024-03-27

5. Integration of Shift-Left Updates into Logic Synthesis and Macro Placement;2024 Conference of Science and Technology for Integrated Circuits (CSTIC);2024-03-17

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