Hongwu Peng

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 43

Top Topics

Avoid Overfitting

Top Venues

Publications

Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Md Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding
MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training. ASPLOS (2) (2024)
Shijin Duan, Chenghong Wang, Hongwu Peng, Yukui Luo, Wujie Wen, Caiwen Ding, Xiaolin Xu
SSNet: A Lightweight Multi-Party Computation Scheme for Practical Privacy-Preserving Machine Learning Service in the Cloud. CoRR (2024)
Can Jin, Hongwu Peng, Shiyu Zhao, Zhenting Wang, Wujiang Xu, Ligong Han, Jiahui Zhao, Kai Zhong, Sanguthevar Rajasekaran, Dimitris N. Metaxas
APEER: Automatic Prompt Engineering Enhances Large Language Model Reranking. CoRR (2024)
Hongwu Peng, Caiwen Ding, Tong Geng, Sutanay Choudhury, Kevin J. Barker, Ang Li
Evaluating Emerging AI/ML Accelerators: IPU, RDU, and NVIDIA/AMD GPUs. ICPE (Companion) (2024)
Tianle Cai, Yuhong Li, Zhengyang Geng, Hongwu Peng, Jason D. Lee, Deming Chen, Tri Dao
Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads. CoRR (2024)
Bingbing Li, Geng Yuan, Zigeng Wang, Shaoyi Huang, Hongwu Peng, Payman Behnam, Wujie Wen, Hang Liu, Caiwen Ding
Zero-Space Cost Fault Tolerance for Transformer-based Language Models on ReRAM. CoRR (2024)
Can Jin, Tong Che, Hongwu Peng, Yiyuan Li, Marco Pavone
Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate. CoRR (2024)
Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding
Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off. DAC (2023)
Xi Xie, Hongwu Peng, Amit Hasan, Shaoyi Huang, Jiahui Zhao, Haowen Fang, Wei Zhang, Tong Geng, Omer Khan, Caiwen Ding
Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks. ICCAD (2023)
Hongwu Peng, Shanglin Zhou, Yukui Luo, Nuo Xu, Shijin Duan, Ran Ran, Jiahui Zhao, Shaoyi Huang, Xi Xie, Chenghong Wang, Tong Geng, Wujie Wen, Xiaolin Xu, Caiwen Ding
RRNet: Towards ReLU-Reduced Neural Network for Two-party Computation Based Private Inference. CoRR (2023)
Hongwu Peng, Ran Ran, Yukui Luo, Jiahui Zhao, Shaoyi Huang, Kiran Thorat, Tong Geng, Chenghong Wang, Xiaolin Xu, Wujie Wen, Caiwen Ding
LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference. CoRR (2023)
Hongwu Peng, Shanglin Zhou, Yukui Luo, Nuo Xu, Shijin Duan, Ran Ran, Jiahui Zhao, Chenghong Wang, Tong Geng, Wujie Wen, Xiaolin Xu, Caiwen Ding
PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment. DAC (2023)
Hongwu Peng, Shaoyi Huang, Tong Zhou, Yukui Luo, Chenghong Wang, Zigeng Wang, Jiahui Zhao, Xi Xie, Ang Li, Tony Geng, Kaleel Mahmood, Wujie Wen, Xiaolin Xu, Caiwen Ding
AutoReP: Automatic ReLU Replacement for Fast Private Network Inference. CoRR (2023)
Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Md Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David Kaeli, Caiwen Ding
MaxK-GNN: Towards Theoretical Speed Limits for Accelerating Graph Neural Networks Training. CoRR (2023)
Kiran Thorat, Jiahui Zhao, Yaotian Liu, Hongwu Peng, Xi Xie, Bin Lei, Jeff Zhang, Caiwen Ding
Advanced Language Model-Driven Verilog Development: Enhancing Power, Performance, and Area Optimization in Code Synthesis. CoRR (2023)
Hongwu Peng, Shanglin Zhou, Yukui Luo, Nuo Xu, Shijin Duan, Ran Ran, Jiahui Zhao, Chenghong Wang, Tong Geng, Wujie Wen, Xiaolin Xu, Caiwen Ding
PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment. CoRR (2023)
Yukui Luo, Nuo Xu, Hongwu Peng, Chenghong Wang, Shijin Duan, Kaleel Mahmood, Wujie Wen, Caiwen Ding, Xiaolin Xu
AQ2PNN: Enabling Two-party Privacy-Preserving Deep Neural Network Inference with Adaptive Quantization. MICRO (2023)
Hongwu Peng, Ran Ran, Yukui Luo, Jiahui Zhao, Shaoyi Huang, Kiran Thorat, Tong Geng, Chenghong Wang, Xiaolin Xu, Wujie Wen, Caiwen Ding
LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference. NeurIPS (2023)
Hongwu Peng, Caiwen Ding, Tong Geng, Sutanay Choudhury, Kevin J. Barker, Ang Li
Evaluating Emerging AI/ML Accelerators: IPU, RDU, and NVIDIA/AMD GPUs. CoRR (2023)
Xi Xie, Hongwu Peng, Amit Hasan, Shaoyi Huang, Jiahui Zhao, Haowen Fang, Wei Zhang, Tong Geng, Omer Khan, Caiwen Ding
Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks. CoRR (2023)
Hongwu Peng, Shaoyi Huang, Tong Zhou, Yukui Luo, Chenghong Wang, Zigeng Wang, Jiahui Zhao, Xi Xie, Ang Li, Tony Geng, Kaleel Mahmood, Wujie Wen, Xiaolin Xu, Caiwen Ding
AutoReP: Automatic ReLU Replacement for Fast Private Network Inference. ICCV (2023)
Hongwu Peng, Shaoyi Huang, Shiyang Chen, Bingbing Li, Tong Geng, Ang Li, Weiwen Jiang, Wujie Wen, Jinbo Bi, Hang Liu, Caiwen Ding
A length adaptive algorithm-hardware co-design of transformer on FPGA through sparse attention and dynamic pipelining. DAC (2022)
Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding
Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off. CoRR (2022)
Hongwu Peng, Deniz Gurevin, Shaoyi Huang, Tong Geng, Weiwen Jiang, Omer Khan, Caiwen Ding
Towards Sparsification of Graph Neural Networks. CoRR (2022)
Hongwu Peng, Shanglin Zhou, Yukui Luo, Shijin Duan, Nuo Xu, Ran Ran, Shaoyi Huang, Chenghong Wang, Tong Geng, Ang Li, Wujie Wen, Xiaolin Xu, Caiwen Ding
PolyMPCNet: Towards ReLU-free Neural Architecture Search in Two-party Computation Based Private Inference. CoRR (2022)
Yixuan Luo, Payman Behnam, Kiran Thorat, Zhuo Liu, Hongwu Peng, Shaoyi Huang, Shu Zhou, Omer Khan, Alexey Tumanov, Caiwen Ding, Tong Geng
CoDG-ReRAM: An Algorithm-Hardware Co-design to Accelerate Semi-Structured GNNs on ReRAM. ICCD (2022)
Shaoyi Huang, Ning Liu, Yueying Liang, Hongwu Peng, Hongjia Li, Dongkuan Xu, Mimi Xie, Caiwen Ding
An Automatic and Efficient BERT Pruning for Edge AI Systems. ISQED (2022)
Hongwu Peng, Deniz Gurevin, Shaoyi Huang, Tong Geng, Weiwen Jiang, Orner Khan, Caiwen Ding
Towards Sparsification of Graph Neural Networks. ICCD (2022)
Caiwu Ding, Hongwu Peng, Lu Lu, Caiwen Ding
Aerial Manipulation Using a Novel Unmanned Aerial Vehicle Cyber-Physical System. CoRR (2022)
Shaoyi Huang, Ning Liu, Yueying Liang, Hongwu Peng, Hongjia Li, Dongkuan Xu, Mimi Xie, Caiwen Ding
An Automatic and Efficient BERT Pruning for Edge AI Systems. CoRR (2022)
Hongwu Peng, Shaoyi Huang, Shiyang Chen, Bingbing Li, Tong Geng, Ang Li, Weiwen Jiang, Wujie Wen, Jinbo Bi, Hang Liu, Caiwen Ding
A Length Adaptive Algorithm-Hardware Co-design of Transformer on FPGA Through Sparse Attention and Dynamic Pipelining. CoRR (2022)
Geng Yuan, Zhiheng Liao, Xiaolong Ma, Yuxuan Cai, Zhenglun Kong, Xuan Shen, Jingyan Fu, Zhengang Li, Chengming Zhang, Hongwu Peng, Ning Liu, Ao Ren, Jinhui Wang, Yanzhi Wang
Improving DNN Fault Tolerance using Weight Pruning and Differential Crossbar Mapping for ReRAM-based Edge AI. ISQED (2021)
Hongwu Peng, Shanglin Zhou, Scott Weitze, Jiaxin Li, Sahidul Islam, Tong Geng, Ang Li, Wei Zhang, Minghu Song, Mimi Xie, Hang Liu, Caiwen Ding
Binary Complex Neural Network Acceleration on FPGA. CoRR (2021)
Hongwu Peng, Shiyang Chen, Zhepeng Wang, Junhuan Yang, Scott A. Weitze, Tong Geng, Ang Li, Jinbo Bi, Minghu Song, Weiwen Jiang, Hang Liu, Caiwen Ding
Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search (Special Session Paper). ICCAD (2021)
Geng Yuan, Zhiheng Liao, Xiaolong Ma, Yuxuan Cai, Zhenglun Kong, Xuan Shen, Jingyan Fu, Zhengang Li, Chengming Zhang, Hongwu Peng, Ning Liu, Ao Ren, Jinhui Wang, Yanzhi Wang
Improving DNN Fault Tolerance using Weight Pruning and Differential Crossbar Mapping for ReRAM-based Edge AI. CoRR (2021)
Bingbing Li, Hongwu Peng, Rajat Sainju, Junhuan Yang, Lei Yang, Yueying Liang, Weiwen Jiang, Binghui Wang, Hang Liu, Caiwen Ding
Detecting Gender Bias in Transformer-based Models: A Case Study on BERT. CoRR (2021)
Hongwu Peng, Shiyang Chen, Zhepeng Wang, Junhuan Yang, Scott A. Weitze, Tong Geng, Ang Li, Jinbo Bi, Minghu Song, Weiwen Jiang, Hang Liu, Caiwen Ding
Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search. CoRR (2021)
Panjie Qi, Yuhong Song, Hongwu Peng, Shaoyi Huang, Qingfeng Zhuge, Edwin Hsing-Mean Sha
Accommodating Transformer onto FPGA: Coupling the Balanced Model Compression and FPGA-Implementation Optimization. ACM Great Lakes Symposium on VLSI (2021)
Shaoyi Huang, Shiyang Chen, Hongwu Peng, Daniel Manu, Zhenglun Kong, Geng Yuan, Lei Yang, Shusen Wang, Hang Liu, Caiwen Ding
HMC-TRAN: A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU. ACM Great Lakes Symposium on VLSI (2021)
Hongwu Peng, Shaoyi Huang, Tong Geng, Ang Li, Weiwen Jiang, Hang Liu, Shusen Wang, Caiwen Ding
Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block Pruning. ISQED (2021)
Panjie Qi, Edwin Hsing-Mean Sha, Qingfeng Zhuge, Hongwu Peng, Shaoyi Huang, Zhenglun Kong, Yuhong Song, Bingbing Li
Accelerating Framework of Transformer by Hardware Design and Model Compression Co-Optimization. ICCAD (2021)
Panjie Qi, Edwin Hsing-Mean Sha, Qingfeng Zhuge, Hongwu Peng, Shaoyi Huang, Zhenglun Kong, Yuhong Song, Bingbing Li
Accelerating Framework of Transformer by Hardware Design and Model Compression Co-Optimization. CoRR (2021)
Hongwu Peng, Shanglin Zhou, Scott Weitze, Jiaxin Li, Sahidul Islam, Tong Geng, Ang Li, Wei Zhang, Minghu Song, Mimi Xie, Hang Liu, Caiwen Ding
Binary Complex Neural Network Acceleration on FPGA : (Invited Paper). ASAP (2021)