2 citations · 2 across the 3 of their papers we have counts for
5 papers
A Composable AI-Accelerated Iterative Solver for 3D-IC Thermal Modeling
Yixing Li, Jiahang Zhou, Zhiyu Zeng +1
Accurate thermal analysis of heterogeneous 2.5D/3D-IC packages is essential yet computationally prohibitive. A single full-package FEM simulation can take hours, while AI-based sur…
AI-driven Thermal-aware Data Center Capacity Planning
Yixing Li, Mark Fenton, Matthew Kaufeler +3
The emerging of large language models (LLMs) has posed significant challenges to the thermal management of data center. Intense GPU computation for LLMs results in localized hotspo…
DeepOHeat-v2: Self-Improving Operator Learning for Fast and Trustworthy Thermal Optimization in 3D-IC Design
Xinling Yu, Yixing Li, Ziyue Liu +4
Thermal-aware optimization of multi-die 3D integrated circuits evaluates many designs, each a costly heat-equation solve. Operator-learning surrogates replace this solve with a fas…
DeepOHeat-v1: Efficient Operator Learning for Fast and Trustworthy Thermal Simulation and Optimization in 3D-IC Design
Xinling Yu, Ziyue Liu, Hai Li +5
Thermal analysis is crucial in 3D-IC design due to increased power density and complex heat dissipation paths. Although operator learning frameworks such as DeepOHeat~\cite{liu2023…
DeepOHeat: Operator Learning-based Ultra-fast Thermal Simulation in 3D-IC Design
Ziyue Liu, Yixing Li, Jing Hu +5
Thermal issue is a major concern in 3D integrated circuit (IC) design. Thermal optimization of 3D IC often requires massive expensive PDE simulations. Neural network-based thermal…