3 papers
cs.AR2026
FETTA: Flexible and Efficient Hardware Accelerator for Tensorized Neural Network Training
Jinming Lu, Jiayi Tian, Hai Li +2
The increasing demand for on-device training of deep neural networks (DNNs) aims to leverage personal data for high-performance applications while addressing privacy concerns and r…
cs.LG2025
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…
cs.LG2025
Ultra Memory-Efficient On-FPGA Training of Transformers via Tensor-Compressed Optimization
Jiayi Tian, Jinming Lu, Hai Li +4
Transformer models have achieved state-of-the-art performance across a wide range of machine learning tasks. There is growing interest in training transformers on resource-constrai…