Characterizing On-Chip Traffic Patterns in General-Purpose GPUs: A Deep Learning Approach. - Yunfan Li 002; Drew Penney; Abhishek Ramamurthy; Lizhong Chen (ICCD, 2019)

Optimizing Routerless Network-on-Chip Designs: An Innovative Learning-Based Framework. - Ting-Ru Lin; Drew Penney; Massoud Pedram; Lizhong Chen (CoRR, 2019)

A Survey of Machine Learning Applied to Computer Architecture Design. - Drew D. Penney; Lizhong Chen (CoRR, 2019)

A Deep Reinforcement Learning Framework for Architectural Exploration: A Routerless NoC Case Study. - Ting-Ru Lin; Drew Penney; Massoud Pedram; Lizhong Chen (HPCA, 2020)

AI for Computer Architecture: Principles, Practice, and Prospects - Lizhong Chen; Drew Penney; Daniel Jiménez (AI for Computer Architecture, 2020)

PROMPT: Learning Dynamic Resource Allocation Policies for Edge-Network Applications. - Drew Penney; Bin Li 018; Jaroslaw Sydir; Charlie Tai; Eoin Walsh; Thomas Long; Stefan Lee; Lizhong Chen (CoRR, 2022)

Shiftable Context: Addressing Training-Inference Context Mismatch in Simultaneous Speech Translation. - Matthew Raffel; Drew Penney; Lizhong Chen (ICML, 2023)

PROMPT: Learning dynamic resource allocation policies for network applications. - Drew Penney; Bin Li 018; Jaroslaw J. Sydir; Lizhong Chen; Charlie Tai; Stefan Lee; Eoin Walsh; Thomas Long (Future Gener. Comput. Syst., 2023)

RAPID: Enabling fast online policy learning in dynamic public cloud environments. - Drew Penney; Bin Li 018; Lizhong Chen; Jaroslaw J. Sydir; Anna Drewek-Ossowicka; Ramesh Illikkal; Charlie Tai; Ravi R. Iyer 001; Andrew Herdrich (Neurocomputing, 2023)