DeepOHeat: Operator Learning-based Ultra-fast Thermal Simulation in 3D-IC Design
Author:
Affiliation:
1. University of California at Santa Barbara,Santa Barbara,CA
2. Cadence Design Systems,Austin,TX
3. Cadence Design Systems,San Jose,CA
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10247654/10247655/10247998.pdf?arnumber=10247998
Reference22 articles.
1. A thermal machine learning solver for chip simulation;ranade;ACM/IEEE Workshop on Machine Learning for CAD,2022
2. Ml-based fast on-chip transient thermal simulation for heterogeneous 2.5 d/3D IC designs;kumar;International Symposium on VLSI Design Automation and Test,2022
3. NVIDIA SimNet™: An AI-Accelerated Multi-Physics Simulation Framework
4. An unsupervised learning approach to solving heat equations on chip based on auto encoder and image gradient;he,2020
5. Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
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1. Parallel Per-tile Activation with Linear Superposition of Thermal Response for Solving Arbitrary Power Pattern in 3DIC Thermal Simulation;Proceedings of the 2024 ACM/IEEE International Symposium on Machine Learning for CAD;2024-09-09
2. A fast general thermal simulation model based on Multi-Branch Physics-Informed deep operator neural network;Physics of Fluids;2024-03-01
3. Invited Paper: Solving Fine-Grained Static 3DIC Thermal with ML Thermal Solver Enhanced with Decay Curve Characterization;2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD);2023-10-28
4. Fast Full-Chip Parametric Thermal Analysis Based on Enhanced Physics Enforced Neural Networks;2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD);2023-10-28
5. Real-Time Precision Prediction of 3-D Package Thermal Maps via Image-to-Image Translation;2023 IEEE 32nd Conference on Electrical Performance of Electronic Packaging and Systems (EPEPS);2023-10-15
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