An Event-Driven Multithreaded Dynamic Optimization Framework. - Weifeng Zhang 003; Brad Calder; Dean M. Tullsen (IEEE PACT, 2005)

A Self-Repairing Prefetcher in an Event-Driven Dynamic Optimization Framework. - Weifeng Zhang 003; Brad Calder; Dean M. Tullsen (CGO, 2006)

Speculative Code Value Specialization Using the Trace Cache Fill Unit. - Weifeng Zhang 003; Brad Calder; Dean M. Tullsen; Steve Checkoway (ICCD, 2006)

Accelerating and Adapting Precomputation Threads for Effcient Prefetching. - Weifeng Zhang 003; Dean M. Tullsen; Brad Calder (HPCA, 2007)

Parallel Training via Computation Graph Transformation. - Fei Wang 046; Guoyang Chen; Weifeng Zhang 003; Tiark Rompf (IEEE BigData, 2019)

Hardware-Guided Symbiotic Training for Compact, Accurate, yet Execution-Efficient LSTM. - Hongxu Yin; Guoyang Chen; Yingmin Li; Shuai Che; Weifeng Zhang 003; Niraj K. Jha (CoRR, 2019)

Software-Defined Design Space Exploration for an Efficient AI Accelerator Architecture. - Ye Yu 003; Yingmin Li; Shuai Che; Niraj K. Jha; Weifeng Zhang 003 (CoRR, 2019)

Sionnx: Automatic Unit Test Generator for ONNX Conformance. - Xinli Cai; Peng Zhou; Shuhan Ding; Guoyang Chen; Weifeng Zhang 003 (CoRR, 2019)

Energy-Efficient and Quality-Assured Approximate Computing Framework Using a Co-Training Method. - Li Jiang 002; Zhuoran Song; Haiyue Song; Chengwen Xu; Qiang Xu 001; Naifeng Jing; Weifeng Zhang 003; Xiaoyao Liang (ACM Trans. Design Autom. Electr. Syst., 2019)

Regularized Training and Tight Certification for Randomized Smoothed Classifier with Provable Robustness. - Huijie Feng; Chunpeng Wu; Guoyang Chen; Weifeng Zhang 003; Yang Ning (AAAI, 2020)

iPIM: Programmable In-Memory Image Processing Accelerator Using Near-Bank Architecture. - Peng Gu; Xinfeng Xie; Yufei Ding 001; Guoyang Chen; Weifeng Zhang 003; Dimin Niu; Yuan Xie 001 (ISCA, 2020)

PIM-DL: Boosting DNN Inference on Digital Processing In-Memory Architectures via Data Layout Optimizations. - Minxuan Zhou; Guoyang Chen; Mohsen Imani; Saransh Gupta; Weifeng Zhang 003; Tajana Rosing (PACT, 2021)

Simple Augmentation Goes a Long Way: ADRL for DNN Quantization. - Lin Ning 001; Guoyang Chen; Weifeng Zhang 003; Xipeng Shen (ICLR, 2021)

Enabling energy-efficient DNN training on hybrid GPU-FPGA accelerators. - Xin He; Jiawen Liu; Zhen Xie; Hao Chen 002; Guoyang Chen; Weifeng Zhang 003; Dong Li 001 (ICS, 2021)

EGEMM-TC: accelerating scientific computing on tensor cores with extended precision. - Boyuan Feng; Yuke Wang; Guoyang Chen; Weifeng Zhang 003; Yuan Xie 001; Yufei Ding 001 (PPoPP, 2021)

Software-Defined Design Space Exploration for an Efficient DNN Accelerator Architecture. - Ye Yu 003; Yingmin Li; Shuai Che; Niraj K. Jha; Weifeng Zhang 003 (IEEE Trans. Computers, 2021)

N3H-Core: Neuron-designed Neural Network Accelerator via FPGA-based Heterogeneous Computing Cores. - Yu Gong; Zhihan Xu; Zhezhi He; Weifeng Zhang 003; Xiaobing Tu; Xiaoyao Liang; Li Jiang 002 (FPGA, 2022)

Towards Execution-Efficient LSTMs via Hardware-Guided Grow-and-Prune Paradigm. - Hongxu Yin; Guoyang Chen; Yingmin Li; Shuai Che; Weifeng Zhang 003; Niraj K. Jha (IEEE Trans. Emerg. Top. Comput., 2022)

GIM: Versatile GNN Acceleration with Reconfigurable Processing-in-Memory. - Chen Nie; Guoyang Chen; Weifeng Zhang 003; Zhezhi He (ICCD, 2023)

A Classical Architecture For Digital Quantum Computers. - Fang Zhang; Xing Zhu; Rui Chao; Cupjin Huang; Linghang Kong; Guoyang Chen; Dawei Ding 002; Haishan Feng; Yihuai Gao; Xiaotong Ni; Liwei Qiu; Zhe Wei; et al. (CoRR, 2023)

VSPIM: SRAM Processing-in-Memory DNN Acceleration via Vector-Scalar Operations. - Chen Nie; Chenyu Tang; Jie Lin 004; Huan Hu; Chenyang Lv; Ting Cao; Weifeng Zhang 003; Li Jiang 002; Xiaoyao Liang; Weikang Qian; Yanan Sun 003; Zhezhi He (IEEE Trans. Computers, 2024)