Binary Complex Neural Network Acceleration on FPGA : (Invited Paper). - Hongwu Peng; Shanglin Zhou; Scott Weitze; Jiaxin Li; Sahidul Islam; Tong Geng; Ang Li 006; Wei Zhang; Minghu Song; Mimi Xie; Hang Liu 001; Caiwen Ding (ASAP, 2021)

HMC-TRAN: A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU. - Shaoyi Huang; Shiyang Chen 004; Hongwu Peng; Daniel Manu; Zhenglun Kong; Geng Yuan; Lei Yang 018; Shusen Wang; Hang Liu 001; Caiwen Ding (ACM Great Lakes Symposium on VLSI, 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 (ACM Great Lakes Symposium on VLSI, 2021)

Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search (Special Session Paper). - Hongwu Peng; Shiyang Chen 004; Zhepeng Wang 001; Junhuan Yang; Scott A. Weitze; Tong Geng; Ang Li 006; Jinbo Bi; Minghu Song; Weiwen Jiang; Hang Liu 001; Caiwen Ding (ICCAD, 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 (ICCAD, 2021)

Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block Pruning. - Hongwu Peng; Shaoyi Huang; Tong Geng; Ang Li 006; Weiwen Jiang; Hang Liu 001; Shusen Wang; Caiwen Ding (ISQED, 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 001; Zhenglun Kong; Xuan Shen; Jingyan Fu; Zhengang Li; Chengming Zhang 006; Hongwu Peng; Ning Liu 007; Ao Ren; et al. (ISQED, 2021)

Binary Complex Neural Network Acceleration on FPGA. - Hongwu Peng; Shanglin Zhou; Scott Weitze; Jiaxin Li; Sahidul Islam; Tong Geng; Ang Li 006; Wei Zhang; Minghu Song; Mimi Xie; Hang Liu 001; Caiwen Ding (CoRR, 2021)

Optimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search. - Hongwu Peng; Shiyang Chen 004; Zhepeng Wang 001; Junhuan Yang; Scott A. Weitze; Tong Geng; Ang Li 006; Jinbo Bi; Minghu Song; Weiwen Jiang; Hang Liu 001; Caiwen Ding (CoRR, 2021)

Detecting Gender Bias in Transformer-based Models: A Case Study on BERT. - Bingbing Li; Hongwu Peng; Rajat Sainju; Junhuan Yang; Lei Yang 018; Yueying Liang; Weiwen Jiang; Binghui Wang; Hang Liu 001; Caiwen Ding (CoRR, 2021)

A length adaptive algorithm-hardware co-design of transformer on FPGA through sparse attention and dynamic pipelining. - Hongwu Peng; Shaoyi Huang; Shiyang Chen 004; Bingbing Li; Tong Geng; Ang Li 006; Weiwen Jiang; Wujie Wen; Jinbo Bi; Hang Liu 001; Caiwen Ding (DAC, 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 (ICCD, 2022)

Towards Sparsification of Graph Neural Networks. - Hongwu Peng; Deniz Gurevin; Shaoyi Huang; Tong Geng; Weiwen Jiang; Omer Khan; Caiwen Ding (ICCD, 2022)

An Automatic and Efficient BERT Pruning for Edge AI Systems. - Shaoyi Huang; Ning Liu 007; Yueying Liang; Hongwu Peng; Hongjia Li; Dongkuan Xu; Mimi Xie; Caiwen Ding (ISQED, 2022)

Aerial Manipulation Using a Novel Unmanned Aerial Vehicle Cyber-Physical System. - Caiwu Ding; Hongwu Peng; Lu Lu 003; Caiwen Ding (CoRR, 2022)

Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off. - Shaoyi Huang; Bowen Lei; Dongkuan Xu; Hongwu Peng; Yue Sun; Mimi Xie; Caiwen Ding (DAC, 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 001; Caiwen Ding (DAC, 2023)

Accel-GCN: High-Performance GPU Accelerator Design for Graph Convolution Networks. - Xi Xie; Hongwu Peng; Amit Hasan 001; Shaoyi Huang; Jiahui Zhao; Haowen Fang; Wei Zhang; Tong Geng; Omer Khan; Caiwen Ding (ICCAD, 2023)

AutoReP: Automatic ReLU Replacement for Fast Private Network Inference. - Hongwu Peng; Shaoyi Huang; Tong Zhou 002; Yukui Luo; Chenghong Wang; Zigeng Wang; Jiahui Zhao; Xi Xie; Ang Li 006; Tony Geng; Kaleel Mahmood; Wujie Wen; et al. (ICCV, 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 001 (MICRO, 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 001; Wujie Wen; Caiwen Ding (NeurIPS, 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; et al. (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 001; Caiwen Ding (CoRR, 2023)

MaxK-GNN: Towards Theoretical Speed Limits for Accelerating Graph Neural Networks Training. - Hongwu Peng; Xi Xie; Kaustubh Shivdikar; Md Amit Hasan 001; Jiahui Zhao; Shaoyi Huang; Omer Khan; David R. Kaeli; Caiwen Ding (CoRR, 2023)

MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training. - Hongwu Peng; Xi Xie; Kaustubh Shivdikar; Md Amit Hasan 001; Jiahui Zhao; Shaoyi Huang; Omer Khan; David R. Kaeli; Caiwen Ding (ASPLOS (2), 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 (ICML, 2024)

Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate. - Can Jin; Tong Che; Hongwu Peng; Yiyuan Li; Dimitris N. Metaxas; Marco Pavone 001 (NeurIPS, 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 006 (ICPE (Companion), 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 001; Caiwen Ding (CoRR, 2024)

Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate. - Can Jin; Tong Che; Hongwu Peng; Yiyuan Li; Marco Pavone 001 (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 001 (CoRR, 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 001; Jiahui Zhao; Shaoyi Huang; Omer Khan; David R. Kaeli; Caiwen Ding (Zenodo, 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 001; Jiahui Zhao; Shaoyi Huang; Omer Khan; David R. Kaeli; Caiwen Ding (Zenodo, 2024)

RTop-K: Ultra-Fast Row-Wise Top-K Selection for Neural Network Acceleration on GPUs. - Xi Xie; Yuebo Luo; Hongwu Peng; Caiwen Ding (ICLR, 2025)

RankFlow: A Multi-Role Collaborative Reranking Workflow Utilizing Large Language Models. - Can Jin; Hongwu Peng; Anxiang Zhang; Nuo Chen 004; Jiahui Zhao; Xi Xie; Kuangzheng Li; Shuya Feng; Kai Zhong; Caiwen Ding; Dimitris N. Metaxas (WWW (Companion Volume), 2025)

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 (WWW (Companion Volume), 2025)

Two Heads are Better Than One: Test-time Scaling of Multi-agent Collaborative Reasoning. - Can Jin; Hongwu Peng; Qixin Zhang 001; Yujin Tang; Dimitris N. Metaxas; Tong Che (CoRR, 2025)

Your Reward Function for RL is Your Best PRM for Search: Unifying RL and Search-Based TTS. - Can Jin; Yang Zhou 019; Qixin Zhang 001; Hongwu Peng; Di Zhang; Marco Pavone 001; Ligong Han; Zhang-Wei Hong; Tong Che; Dimitris N. Metaxas (CoRR, 2025)