Timing macro modeling with graph neural networks-Reference-Cited by-同舟云学术

Timing macro modeling with graph neural networks

Published:2022-07-10 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 59th ACM/IEEE Design Automation Conference
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Author:

Chang Kevin Kai-Chun¹,Chiang Chun-Yao¹,Lee Pei-Yu²,Jiang Iris Hui-Ru¹

Affiliation:

1. National Taiwan University, Taipei, Taiwan

2. Cadence Design Systems, Inc., Hsinchu, Taiwan

Funder

Taiwan Ministry of Science and Technology

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3489517.3530599

Reference17 articles.

1. Jin Hu , Song Chen , Xin Zhao , and Xi Chen. TAU 2016 timing contest on macro modeling. In International Workshop on Timing Issues in the Specification and Synthesis of Digital Systems (TAU) , 2016 . Jin Hu, Song Chen, Xin Zhao, and Xi Chen. TAU 2016 timing contest on macro modeling. In International Workshop on Timing Issues in the Specification and Synthesis of Digital Systems (TAU), 2016.

2. Automated timing model generation

3. LibAbs

4. A highly compressed timing macro-modeling algorithm for hierarchical and incremental timing analysis

5. Pei-Yu Lee and Iris Hui-Ru Jiang . iTimerM: A compact and accurate timing macro model for efficient hierarchical timing analysis. ACM Transactions on Design Automation of Electronic Systems (TODAES), 23(4):48:1--48:21 , 2018 . Pei-Yu Lee and Iris Hui-Ru Jiang. iTimerM: A compact and accurate timing macro model for efficient hierarchical timing analysis. ACM Transactions on Design Automation of Electronic Systems (TODAES), 23(4):48:1--48:21, 2018.

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