GridNetOpt: Fast Full-Chip EM-Aware Power Grid Optimization Accelerated by Deep Neural Networks
Author:
Affiliation:
1. Department of Electrical and Computer Engineering, University of California at Riverside, Riverside, CA, USA
Funder
NSF
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Graphics and Computer-Aided Design,Software
Link
https://ieeexplore.ieee.org/ielam/43/10106059/9888769-aam.pdf
Reference45 articles.
1. Microstructure Effect on EM-Induced Degradations in Dual Inlaid Copper Interconnects
2. PowerNet: Transferable Dynamic IR Drop Estimation via Maximum Convolutional Neural Network
3. Experimental characterization and modeling of the reliability of interconnect trees
4. IncPIRD: Fast Learning-Based Prediction of Incremental IR Drop
5. Power Grid Electromigration Checking Using Physics-Based Models
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1. OhmNet: General Static IR Drop Estimation Neural Network Architecture;2024 2nd International Symposium of Electronics Design Automation (ISEDA);2024-05-10
2. GridVAE: Fast Power Grid EM-Aware IR Drop Prediction and Fixing Accelerated by Variational AutoEncoder;2024 25th International Symposium on Quality Electronic Design (ISQED);2024-04-03
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