A Parallel Simulation Framework Incorporating Machine Learning-Based Hotspot Detection for Accelerated Power Grid Analysis-Reference-Cited by-同舟云学术

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A Parallel Simulation Framework Incorporating Machine Learning-Based Hotspot Detection for Accelerated Power Grid Analysis

Published:2024-09-09 Issue: Volume:41 Page:1-7
ISSN:
Container-title:Proceedings of the 2024 ACM/IEEE International Symposium on Machine Learning for CAD
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Author:

Jiang Yangfan¹^ORCID,Song Jianfei¹^ORCID,Yin Xunzhao¹^ORCID,Dong Xiao¹^ORCID,Sun Songyu¹^ORCID,Lin Yibo²^ORCID,Jin Zhou³^ORCID,Yang Xiaoyu³^ORCID,Zhuo Cheng¹^ORCID

Affiliation:

1. Zhejiang University, Hangzhou, China

2. Peking University, Beijing, China

3. China University of Petroleum-Beijing, Beijing, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3670474.3685947

Reference22 articles.

1. Power Supply Noise in SoCs: Metrics, Management, and Measurement

2. Y. Bai X. Yang et al. 2024. Efficient spectral-aware power supply noise analysis for low-power design verification. In DATE. IEEE 1--6.

3. R. Barrett M. Berry et al. 1994. Templates for the solution of linear systems: building blocks for iterative methods. SIAM.

4. Faster region-based hotspot detection;Chen R.;IEEE TCAD,2020

5. Xiaoming Chen. 2022. Numerically-stable and highly-scalable parallel LU factorization for circuit simulation. In ICCAD. 1--9.

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