Hongwu Peng

According to our database, Hongwu Peng authored at least 33 papers between 2021 and 2024.

Collaborative distances:

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

2024

ASPLOS 2024 Artifact for "MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training".

Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding

Dataset, February, 2024

ASPLOS 2024 Artifact for "MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training".

Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding

Dataset, February, 2024

APEER: Automatic Prompt Engineering Enhances Large Language Model Reranking.

Can Jin, Hongwu Peng, Shiyu Zhao, Zhenting Wang, Wujiang Xu, Ligong Han, Jiahui Zhao, Kai Zhong, Sanguthevar Rajasekaran, Dimitris N. Metaxas

CoRR, 2024

SSNet: A Lightweight Multi-Party Computation Scheme for Practical Privacy-Preserving Machine Learning Service in the Cloud.

Shijin Duan, Chenghong Wang, Hongwu Peng, Yukui Luo, Wujie Wen, Caiwen Ding, Xiaolin Xu

CoRR, 2024

Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate.

Can Jin, Tong Che, Hongwu Peng, Yiyuan Li, Marco Pavone

CoRR, 2024

Zero-Space Cost Fault Tolerance for Transformer-based Language Models on ReRAM.

Bingbing Li, Geng Yuan, Zigeng Wang, Shaoyi Huang, Hongwu Peng, Payman Behnam, Wujie Wen, Hang Liu, Caiwen Ding

CoRR, 2024

Evaluating Emerging AI/ML Accelerators: IPU, RDU, and NVIDIA/AMD GPUs.

Hongwu Peng, Caiwen Ding, Tong Geng, Sutanay Choudhury, Kevin J. Barker, Ang Li

Proceedings of the Companion of the 15th ACM/SPEC International Conference on Performance Engineering, 2024

Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads.

Tianle Cai, Yuhong Li, Zhengyang Geng, Hongwu Peng, Jason D. Lee, Deming Chen, Tri Dao

Proceedings of the Forty-first International Conference on Machine Learning, 2024

MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training.

Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Md Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding

Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2024

2023

MaxK-GNN: Towards Theoretical Speed Limits for Accelerating Graph Neural Networks Training.

Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Md Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding

CoRR, 2023

Advanced Large Language Model (LLM)-Driven Verilog Development: Enhancing Power, Performance, and Area Optimization in Code Synthesis.

Kiran Thorat, Jiahui Zhao, Yaotian Liu, Hongwu Peng, Xi Xie, Bin Lei, Jeff Zhang, Caiwen Ding

CoRR, 2023

RRNet: Towards ReLU-Reduced Neural Network for Two-party Computation Based Private Inference.

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

CoRR, 2023

LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference.

Hongwu Peng, Ran Ran, Yukui Luo, Jiahui Zhao, Shaoyi Huang, Kiran Thorat, Tong Geng, Chenghong Wang, Xiaolin Xu, Wujie Wen, Caiwen Ding

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

AQ2PNN: Enabling Two-party Privacy-Preserving Deep Neural Network Inference with Adaptive Quantization.

Yukui Luo, Nuo Xu, Hongwu Peng, Chenghong Wang, Shijin Duan, Kaleel Mahmood, Wujie Wen, Caiwen Ding, Xiaolin Xu

Proceedings of the 56th Annual IEEE/ACM International Symposium on Microarchitecture, 2023

AutoReP: Automatic ReLU Replacement for Fast Private Network Inference.

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

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks.

Xi Xie, Hongwu Peng, Amit Hasan, Shaoyi Huang, Jiahui Zhao, Haowen Fang, Wei Zhang, Tong Geng, Omer Khan, Caiwen Ding

Proceedings of the IEEE/ACM International Conference on Computer Aided Design, 2023

PASNet: Polynomial Architecture Search Framework for Two-party Computation-based Secure Neural Network Deployment.

Hongwu Peng, Shanglin Zhou, Yukui Luo, Nuo Xu, Shijin Duan, Ran Ran, Jiahui Zhao, Chenghong Wang, Tong Geng, Wujie Wen, Xiaolin Xu, Caiwen Ding

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off.

Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

2022

Aerial Manipulation Using a Novel Unmanned Aerial Vehicle Cyber-Physical System.

Caiwu Ding, Hongwu Peng, Lu Lu, Caiwen Ding

CoRR, 2022

An Automatic and Efficient BERT Pruning for Edge AI Systems.

Shaoyi Huang, Ning Liu, Yueying Liang, Hongwu Peng, Hongjia Li, Dongkuan Xu, Mimi Xie, Caiwen Ding

Proceedings of the 23rd International Symposium on Quality Electronic Design, 2022

Towards Sparsification of Graph Neural Networks.

Hongwu Peng, Deniz Gurevin, Shaoyi Huang, Tong Geng, Weiwen Jiang, Omer Khan, Caiwen Ding

Proceedings of the IEEE 40th International Conference on Computer Design, 2022

CoDG-ReRAM: An Algorithm-Hardware Co-design to Accelerate Semi-Structured GNNs on ReRAM.

Yixuan Luo, Payman Behnam, Kiran Thorat, Zhuo Liu, Hongwu Peng, Shaoyi Huang, Shu Zhou, Omer Khan, Alexey Tumanov, Caiwen Ding, Tong Geng

Proceedings of the IEEE 40th International Conference on Computer Design, 2022

A length adaptive algorithm-hardware co-design of transformer on FPGA through sparse attention and dynamic pipelining.

Hongwu Peng, Shaoyi Huang, Shiyang Chen, Bingbing Li, Tong Geng, Ang Li, Weiwen Jiang, Wujie Wen, Jinbo Bi, Hang Liu, Caiwen Ding

Proceedings of the DAC '22: 59th ACM/IEEE Design Automation Conference, San Francisco, California, USA, July 10, 2022

2021

Detecting Gender Bias in Transformer-based Models: A Case Study on BERT.

Bingbing Li, Hongwu Peng, Rajat Sainju, Junhuan Yang, Lei Yang, Yueying Liang, Weiwen Jiang, Binghui Wang, Hang Liu, Caiwen Ding

CoRR, 2021

Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search.

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

CoRR, 2021

Binary Complex Neural Network Acceleration on FPGA.

Hongwu Peng, Shanglin Zhou, Scott Weitze, Jiaxin Li, Sahidul Islam, Tong Geng, Ang Li, Wei Zhang, Minghu Song, Mimi Xie, Hang Liu, Caiwen Ding

CoRR, 2021

Improving DNN Fault Tolerance using Weight Pruning and Differential Crossbar Mapping for ReRAM-based Edge AI.

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

Proceedings of the 22nd International Symposium on Quality Electronic Design, 2021

Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block Pruning.

Hongwu Peng, Shaoyi Huang, Tong Geng, Ang Li, Weiwen Jiang, Hang Liu, Shusen Wang, Caiwen Ding

Proceedings of the 22nd International Symposium on Quality Electronic Design, 2021

Accelerating Framework of Transformer by Hardware Design and Model Compression Co-Optimization.

Panjie Qi, Edwin Hsing-Mean Sha, Qingfeng Zhuge, Hongwu Peng, Shaoyi Huang, Zhenglun Kong, Yuhong Song, Bingbing Li

Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2021

Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search (Special Session Paper).

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

Proceedings of the IEEE/ACM International Conference On Computer Aided Design, 2021

Accommodating Transformer onto FPGA: Coupling the Balanced Model Compression and FPGA-Implementation Optimization.

Panjie Qi, Yuhong Song, Hongwu Peng, Shaoyi Huang, Qingfeng Zhuge, Edwin Hsing-Mean Sha

Proceedings of the GLSVLSI '21: Great Lakes Symposium on VLSI 2021, 2021

HMC-TRAN: A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU.

Shaoyi Huang, Shiyang Chen, Hongwu Peng, Daniel Manu, Zhenglun Kong, Geng Yuan, Lei Yang, Shusen Wang, Hang Liu, Caiwen Ding

Proceedings of the GLSVLSI '21: Great Lakes Symposium on VLSI 2021, 2021

Binary Complex Neural Network Acceleration on FPGA : (Invited Paper).

Hongwu Peng, Shanglin Zhou, Scott Weitze, Jiaxin Li, Sahidul Islam, Tong Geng, Ang Li, Wei Zhang, Minghu Song, Mimi Xie, Hang Liu, Caiwen Ding

Proceedings of the 32nd IEEE International Conference on Application-specific Systems, 2021