Addressing Memory Wall Problem of Graph Computation in Reconfigurable System. - Xu Wang 010; Linan Huang; Yongxin Zhu 001; Yipeng Zhou; Huwan Peng; Haifei Xiong (HPCC/CSS/ICESS, 2015)

OCEAN: An on-chip incremental-learning enhanced processor with gated recurrent neural network accelerators. - Chixiao Chen; Hongwei Ding; Huwan Peng; Haozhe Zhu; Rui Ma; Peiyong Zhang; Xiaolang Yan; Yu Wang 046; Mingyu Wang 001; Hao Min; Chuanjin Richard Shi (ESSCIRC, 2017)

Exploring the programmability for deep learning processors: from architecture to tensorization. - Chixiao Chen; Huwan Peng; Xindi Liu; Hongwei Ding; Chuanjin Richard Shi (DAC, 2018)

iFPNA: A Flexible and Efficient Deep Neural Network Accelerator with a Programmable Data Flow Engine in 28nm CMOS. - Chixiao Chen; Xindi Liu; Huwan Peng; Hongwei Ding; Chuanjin Richard Shi (ESSCIRC, 2018)

OCEAN: An On-Chip Incremental-Learning Enhanced Artificial Neural Network Processor With Multiple Gated-Recurrent-Unit Accelerators. - Chixiao Chen; Hongwei Ding; Huwan Peng; Haozhe Zhu; Yu Wang 046; Chuanjin Richard Shi (IEEE J. Emerg. Sel. Topics Circuits Syst., 2018)

iFPNA: A Flexible and Efficient Deep Learning Processor in 28-nm CMOS Using a Domain-Specific Instruction Set and Reconfigurable Fabric. - Chixiao Chen; Xindi Liu; Huwan Peng; Hongwei Ding; Chuanjin Richard Shi (IEEE J. Emerg. Sel. Topics Circuits Syst., 2019)

Q-VR: system-level design for future mobile collaborative virtual reality. - Chenhao Xie 001; Xie Li; Yang Hu 001; Huwan Peng; Michael B. Taylor; Shuaiwen Leon Song (ASPLOS, 2021)

Chiplet Cloud: Building AI Supercomputers for Serving Large Generative Language Models. - Huwan Peng; Scott Davidson 004; Richard Shi; Shuaiwen Leon Song; Michael B. Taylor (CoRR, 2023)

ReaLLM: A Trace-Driven Framework for Rapid Simulation of Large-Scale LLM Inference. - Huwan Peng; Scott Davidson 004; C.-J. Richard Shi; Michael B. Taylor (ASAP, 2025)