Weifeng Zhang

According to our database, Weifeng Zhang authored at least 20 papers between 2005 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

A Classical Architecture For Digital Quantum Computers.

Fang Zhang, Xing Zhu, Rui Chao, Cupjin Huang, Linghang Kong, Guoyang Chen, Dawei Ding, Haishan Feng, Yihuai Gao, Xiaotong Ni, Liwei Qiu, Zhe Wei, Yueming Yang, Yang Zhao, Yaoyun Shi, Weifeng Zhang, Peng Zhou, Jianxin Chen

CoRR, 2023

GIM: Versatile GNN Acceleration with Reconfigurable Processing-in-Memory.

Chen Nie, Guoyang Chen, Weifeng Zhang, Zhezhi He

Proceedings of the 41st IEEE International Conference on Computer Design, 2023

2022

Towards Execution-Efficient LSTMs via Hardware-Guided Grow-and-Prune Paradigm.

Hongxu Yin, Guoyang Chen, Yingmin Li, Shuai Che, Weifeng Zhang, Niraj K. Jha

IEEE Trans. Emerg. Top. Comput., 2022

N3H-Core: Neuron-designed Neural Network Accelerator via FPGA-based Heterogeneous Computing Cores.

Yu Gong, Zhihan Xu, Zhezhi He, Weifeng Zhang, Xiaobing Tu, Xiaoyao Liang, Li Jiang

Proceedings of the FPGA '22: The 2022 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, Virtual Event, USA, 27 February 2022, 2022

2021

Software-Defined Design Space Exploration for an Efficient DNN Accelerator Architecture.

Ye Yu, Yingmin Li, Shuai Che, Niraj K. Jha, Weifeng Zhang

IEEE Trans. Computers, 2021

EGEMM-TC: accelerating scientific computing on tensor cores with extended precision.

Boyuan Feng, Yuke Wang, Guoyang Chen, Weifeng Zhang, Yuan Xie, Yufei Ding

Proceedings of the PPoPP '21: 26th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 2021

Enabling energy-efficient DNN training on hybrid GPU-FPGA accelerators.

Xin He, Jiawen Liu, Zhen Xie, Hao Chen, Guoyang Chen, Weifeng Zhang, Dong Li

Proceedings of the ICS '21: 2021 International Conference on Supercomputing, 2021

Simple Augmentation Goes a Long Way: ADRL for DNN Quantization.

Lin Ning, Guoyang Chen, Weifeng Zhang, Xipeng Shen

Proceedings of the 9th International Conference on Learning Representations, 2021

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, Tajana Rosing

Proceedings of the 30th International Conference on Parallel Architectures and Compilation Techniques, 2021

2020

iPIM: Programmable In-Memory Image Processing Accelerator Using Near-Bank Architecture.

Peng Gu, Xinfeng Xie, Yufei Ding, Guoyang Chen, Weifeng Zhang, Dimin Niu, Yuan Xie

Proceedings of the 47th ACM/IEEE Annual International Symposium on Computer Architecture, 2020

Regularized Training and Tight Certification for Randomized Smoothed Classifier with Provable Robustness.

Huijie Feng, Chunpeng Wu, Guoyang Chen, Weifeng Zhang, Yang Ning

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Energy-Efficient and Quality-Assured Approximate Computing Framework Using a Co-Training Method.

Li Jiang, Zhuoran Song, Haiyue Song, Chengwen Xu, Qiang Xu, Naifeng Jing, Weifeng Zhang, Xiaoyao Liang

ACM Trans. Design Autom. Electr. Syst., 2019

Sionnx: Automatic Unit Test Generator for ONNX Conformance.

Xinli Cai, Peng Zhou, Shuhan Ding, Guoyang Chen, Weifeng Zhang

CoRR, 2019

Software-Defined Design Space Exploration for an Efficient AI Accelerator Architecture.

Ye Yu, Yingmin Li, Shuai Che, Niraj K. Jha, Weifeng Zhang

CoRR, 2019

Hardware-Guided Symbiotic Training for Compact, Accurate, yet Execution-Efficient LSTM.

Hongxu Yin, Guoyang Chen, Yingmin Li, Shuai Che, Weifeng Zhang, Niraj K. Jha

CoRR, 2019

Parallel Training via Computation Graph Transformation.

Fei Wang, Guoyang Chen, Weifeng Zhang, Tiark Rompf

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2007

Accelerating and Adapting Precomputation Threads for Effcient Prefetching.

Weifeng Zhang, Dean M. Tullsen, Brad Calder

Proceedings of the 13st International Conference on High-Performance Computer Architecture (HPCA-13 2007), 2007

2006

Speculative Code Value Specialization Using the Trace Cache Fill Unit.

Weifeng Zhang, Brad Calder, Dean M. Tullsen, Steve Checkoway

Proceedings of the 24th International Conference on Computer Design (ICCD 2006), 2006

A Self-Repairing Prefetcher in an Event-Driven Dynamic Optimization Framework.

Weifeng Zhang, Brad Calder, Dean M. Tullsen

Proceedings of the Fourth IEEE/ACM International Symposium on Code Generation and Optimization (CGO 2006), 2006

2005

An Event-Driven Multithreaded Dynamic Optimization Framework.

Weifeng Zhang, Brad Calder, Dean M. Tullsen

Proceedings of the 14th International Conference on Parallel Architectures and Compilation Techniques (PACT 2005), 2005