Caiwen Ding

According to our database, Caiwen Ding authored at least 152 papers between 2015 and 2024.

Collaborative distances:

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

2024

A Multi-Agent Reinforcement Learning Approach for Safe and Efficient Behavior Planning of Connected Autonomous Vehicles.

Songyang Han, Shanglin Zhou, Jiangwei Wang, Lynn Pepin, Caiwen Ding, Jie Fu, Fei Miao

IEEE Trans. Intell. Transp. Syst., May, 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

Collaborative Multi-Object Tracking With Conformal Uncertainty Propagation.

Sanbao Su, Songyang Han, Yiming Li, Zhili Zhang, Chen Feng, Caiwen Ding, Fei Miao

IEEE Robotics Autom. Lett., 2024

International Trade Flow Prediction with Bilateral Trade Provisions.

Zijie Pan, Stepan Gordeev, Jiahui Zhao, Ziyi Meng, Caiwen Ding, Sandro Steinbach, Dongjin Song

CoRR, 2024

AdaPI: Facilitating DNN Model Adaptivity for Efficient Private Inference in Edge Computing.

Tong Zhou, Jiahui Zhao, Yukui Luo, Xi Xie, Wujie Wen, Caiwen Ding, Xiaolin Xu

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

Weakly Supervised Change Detection via Knowledge Distillation and Multiscale Sigmoid Inference.

Binghao Lu, Caiwen Ding, Jinbo Bi, Dongjin Song

CoRR, 2024

Key Information Retrieval to Classify the Unstructured Data Content of Preferential Trade Agreements.

Jiahui Zhao, Ziyi Meng, Stepan Gordeev, Zijie Pan, Dongjin Song, Sandro Steinbach, Caiwen Ding

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

FlashVideo: A Framework for Swift Inference in Text-to-Video Generation.

Bin Lei, Le Chen, 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

Quasar-ViT: Hardware-Oriented Quantization-Aware Architecture Search for Vision Transformers.

Zhengang Li, Alec Lu, Yanyue Xie, Zhenglun Kong, Mengshu Sun, Hao Tang, Zhong Jia Xue, Peiyan Dong, Caiwen Ding, Yanzhi Wang, Xue Lin, Zhenman Fang

Proceedings of the 38th ACM International Conference on Supercomputing, 2024

PruneGNN: Algorithm-Architecture Pruning Framework for Graph Neural Network Acceleration.

Deniz Gurevin, Mohsin Shan, Shaoyi Huang, Md Amit Hasan, Caiwen Ding, Omer Khan

Proceedings of the IEEE International Symposium on High-Performance Computer Architecture, 2024

AdaDiff: Accelerating Diffusion Models Through Step-Wise Adaptive Computation.

Shengkun Tang, Yaqing Wang, Caiwen Ding, Yi Liang, Yao Li, Dongkuan Xu

Proceedings of the Computer Vision - ECCV 2024, 2024

SuperFlow: A Fully-Customized RTL-to-GDS Design Automation Flow for Adiabatic Quantum- Flux - Parametron Superconducting Circuits.

Yanyue Xie, Peiyan Dong, Geng Yuan, Zhengang Li, Masoud Zabihi, Chao Wu, Sung-En Chang, Xufeng Zhang, Xue Lin, Caiwen Ding, Nobuyuki Yoshikawa, Olivia Chen, Yanzhi Wang

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 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

Surrogate Lagrangian Relaxation: A Path to Retrain-Free Deep Neural Network Pruning.

Shanglin Zhou, Mikhail A. Bragin, Deniz Gurevin, Lynn Pepin, Fei Miao, Caiwen Ding

ACM Trans. Design Autom. Electr. Syst., November, 2023

Memristor-Based Spectral Decomposition of Matrices and Its Applications.

Zeinab S. Jalali, Chenghong Wang, Griffin Kearney, Geng Yuan, Caiwen Ding, Yinan Zhou, Yanzhi Wang, Sucheta Soundarajan

IEEE Trans. Computers, May, 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

DeeDiff: Dynamic Uncertainty-Aware Early Exiting for Accelerating Diffusion Model Generation.

Shengkun Tang, Yaqing Wang, Caiwen Ding, Yi Liang, Yao Li, Dongkuan Xu

CoRR, 2023

Towards Zero Memory Footprint Spiking Neural Network Training.

Bin Lei, Sheng Lin, Pei-Hung Lin, Chunhua Liao, Caiwen Ding

CoRR, 2023

Boosting Logical Reasoning in Large Language Models through a New Framework: The Graph of Thought.

Bin Lei, Pei-Hung Lin, Chunhua Liao, Caiwen Ding

CoRR, 2023

Tango: rethinking quantization for graph neural network training on GPUs.

Shiyang Chen, Da Zheng, Caiwen Ding, Chengying Huan, Yuede Ji, Hang Liu

CoRR, 2023

Creating a Dataset for High-Performance Computing Code Translation: A Bridge Between HPC Fortran and C++.

Bin Lei, Caiwen Ding, Le Chen, Pei-Hung Lin, Chunhua Liao

CoRR, 2023

Dynamic Gradient Balancing for Enhanced Adversarial Attacks on Multi-Task Models.

Lijun Zhang, Xiao Liu, Kaleel Mahmood, Caiwen Ding, Hui Guan

CoRR, 2023

Shared Information-Based Safe And Efficient Behavior Planning For Connected Autonomous Vehicles.

Songyang Han, Shanglin Zhou, Lynn Pepin, Jiangwei Wang, Caiwen Ding, Fei Miao

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

Spectral-DP: Differentially Private Deep Learning through Spectral Perturbation and Filtering.

Ce Feng, Nuo Xu, Wujie Wen, Parv Venkitasubramaniam, Caiwen Ding

Proceedings of the 44th IEEE Symposium on Security and Privacy, 2023

TANGO: re-thinking quantization for graph neural network training on GPUs.

Shiyang Chen, Da Zheng, Caiwen Ding, Chengying Huan, Yuede Ji, Hang Liu

Proceedings of the International Conference for High Performance Computing, 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

Automatic Subnetwork Search Through Dynamic Differentiable Neuron Pruning.

Zigeng Wang, Bingbing Li, Xia Xiao, Tianyun Zhang, Mikhail A. Bragin, Bing Yan, Caiwen Ding, Sanguthevar Rajasekaran

Proceedings of the 24th International Symposium on Quality Electronic Design, 2023

A Deep Learning Approach for Ventricular Arrhythmias Classification using Microcontroller.

Ya-sine Agrignan, Shanglin Zhou, Jun Bai, Sahidul Islam, Sheida Nabavi, Mimi Xie, Caiwen Ding

Proceedings of the 24th International Symposium on Quality Electronic Design, 2023

MergePath-SpMM: Parallel Sparse Matrix-Matrix Algorithm for Graph Neural Network Acceleration.

Mohsin Shan, Deniz Gurevin, Jared Nye, Caiwen Ding, Omer Khan

Proceedings of the IEEE International Symposium on Performance Analysis of Systems and Software, 2023

Towards Lossless Head Pruning through Automatic Peer Distillation for Language Models.

Bingbing Li, Zigeng Wang, Shaoyi Huang, Mikhail A. Bragin, Ji Li, Caiwen Ding

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Uncertainty Quantification of Collaborative Detection for Self-Driving.

Sanbao Su, Yiming Li, Sihong He, Songyang Han, Chen Feng, Caiwen Ding, Fei Miao

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

SpENCNN: Orchestrating Encoding and Sparsity for Fast Homomorphically Encrypted Neural Network Inference.

Ran Ran, Xinwei Luo, Wei Wang, Tao Liu, Gang Quan, Xiaolin Xu, Caiwen Ding, Wujie Wen

Proceedings of the International Conference on Machine Learning, 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

Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C++.

Bin Lei, Caiwen Ding, Le Chen, Pei-Hung Lin, Chunhua Liao

Proceedings of the IEEE High Performance Extreme Computing Conference, 2023

Understanding Node Allocation on Leadership-Class Supercomputers with Graph Analytics.

Andy Trinh, Shivam Sheth, Anil Gaihre, Caiwen Ding, Jieyang Chen, Feiyi Wang, David Pugmire, Scott Klasky, Hang Liu, Lipeng Wan

Proceedings of the IEEE International Conference on High Performance Computing & Communications, 2023

Physics-aware Roughness Optimization for Diffractive Optical Neural Networks.

Shanglin Zhou, Yingjie Li, Minhan Lou, Weilu Gao, Zhijie Shi, Cunxi Yu, Caiwen Ding

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

Ising-CF: A Pathbreaking Collaborative Filtering Method Through Efficient Ising Machine Learning.

Zhuo Liu, Yunan Yang, Zhenyu Pan, Anshujit Sharma, Amit Hasan, Caiwen Ding, Ang Li, Michael C. Huang, Tong Geng

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

Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration.

Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding

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

Condense: A Framework for Device and Frequency Adaptive Neural Network Models on the Edge.

Yifan Gong, Pu Zhao, Zheng Zhan, Yushu Wu, Chao Wu, Zhenglun Kong, Minghai Qin, Caiwen Ding, Yanzhi Wang

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

Accelerating Dataset Distillation via Model Augmentation.

Lei Zhang, Jie Zhang, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, Dongkuan Xu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model.

Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Game Theoretic Mixed Experts for Combinational Adversarial Machine Learning.

Ethan Rathbun, Kaleel Mahmood, Sohaib Ahmad, Caiwen Ding, Marten van Dijk

CoRR, 2022

Efficient Traffic State Forecasting using Spatio-Temporal Network Dependencies: A Sparse Graph Neural Network Approach.

Bin Lei, Shaoyi Huang, Caiwen Ding, Monika Filipovska

CoRR, 2022

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

Caiwu Ding, Hongwu Peng, Lu Lu, Caiwen Ding

CoRR, 2022

Securing the Spike: On the Transferabilty and Security of Spiking Neural Networks to Adversarial Examples.

Nuo Xu, Kaleel Mahmood, Haowen Fang, Ethan Rathbun, Caiwen Ding, Wujie Wen

CoRR, 2022

Graph-Based Shape Analysis for Heterogeneous Geometric Datasets: Similarity, Retrieval and Substructure Matching.

Jiangce Chen, Horea T. Ilies, Caiwen Ding

Comput. Aided Des., 2022

QuClassi: A Hybrid Deep Neural Network Architecture based on Quantum State Fidelity.

Samuel Alexander Stein, Betis Baheri, Daniel Chen, Ying Mao, Qiang Guan, Ang Li, Shuai Xu, Caiwen Ding

Proceedings of the Fifth Conference on Machine Learning and Systems, 2022

An Intermittent OTA Approach to Update the DL Weights on Energy Harvesting Devices.

Wei Wei, Sahidul Islam, Jishnu Banerjee, Shanglin Zhou, Chen Pan, Caiwen Ding, Mimi Xie

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

Reliability Improvement in RRAM-based DNN for Edge Computing.

Md. Oli-Uz-Zaman, Saleh Ahmad Khan, Geng Yuan, Yanzhi Wang, Zhiheng Liao, Jingyan Fu, Caiwen Ding, Jinhui Wang

Proceedings of the IEEE International Symposium on Circuits and Systems, 2022

Variance of the Gradient Also Matters: Privacy Leakage from Gradients.

Yijue Wang, Jieren Deng, Dan Guo, Chenghong Wang, Xianrui Meng, Hang Liu, Chao Shang, Binghui Wang, Qin Cao, Caiwen Ding, Sanguthevar Rajasekaran

Proceedings of the International Joint Conference on Neural Networks, 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

On the Design of Quantum Graph Convolutional Neural Network in the NISQ-Era and Beyond.

Zhirui Hu, Jinyang Li, Zhenyu Pan, Shanglin Zhou, Lei Yang, Caiwen Ding, Omer Khan, Tong Geng, Weiwen Jiang

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

Towards Real-Time Temporal Graph Learning.

Deniz Gurevin, Mohsin Shan, Tong Geng, Weiwen Jiang, Caiwen Ding, Omer Khan

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

EVE: Environmental Adaptive Neural Network Models for Low-Power Energy Harvesting System.

Sahidul Islam, Shanglin Zhou, Ran Ran, Yufang Jin, Wujie Wen, Caiwen Ding, Mimi Xie

Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design, 2022

All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management.

Yifan Gong, Zheng Zhan, Pu Zhao, Yushu Wu, Chao Wu, Caiwen Ding, Weiwen Jiang, Minghai Qin, Yanzhi Wang

Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided Design, 2022

Enabling Fast Deep Learning on Tiny Energy-Harvesting IoT Devices.

Sahidul Islam, Jieren Deng, Shanglin Zhou, Chen Pan, Caiwen Ding, Mimi Xie

Proceedings of the 2022 Design, Automation & Test in Europe Conference & Exhibition, 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

Poster: Cryptographic Inferences for Video Deep Neural Networks.

Bingyu Liu, Rujia Wang, Zhongjie Ba, Shanglin Zhou, Caiwen Ding, Yuan Hong

Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security, 2022

Analyzing and Defending against Membership Inference Attacks in Natural Language Processing Classification.

Yijue Wang, Nuo Xu, Shaoyi Huang, Kaleel Mahmood, Dan Guo, Caiwen Ding, Wujie Wen, Sanguthevar Rajasekaran

Proceedings of the IEEE International Conference on Big Data, 2022

Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm.

Shaoyi Huang, Dongkuan Xu, Ian En-Hsu Yen, Yijue Wang, Sung-En Chang, Bingbing Li, Shiyang Chen, Mimi Xie, Sanguthevar Rajasekaran, Hang Liu, Caiwen Ding

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

Trust: Triangle Counting Reloaded on GPUs.

Santosh Pandey, Zhibin Wang, Sheng Zhong, Chen Tian, Bolong Zheng, Xiaoye S. Li, Lingda Li, Adolfy Hoisie, Caiwen Ding, Dong Li, Hang Liu

IEEE Trans. Parallel Distributed Syst., 2021

Design, Sensing, and Control of a Novel UAV Platform for Aerial Drilling and Screwing.

Caiwu Ding, Lu Lu, Cong Wang, Caiwen Ding

IEEE Robotics Autom. Lett., 2021

Enabling Super-Fast Deep Learning on Tiny Energy-Harvesting IoT Devices.

Sahidul Islam, Jieren Deng, Shanglin Zhou, Chen Pan, Caiwen Ding, Mimi Xie

CoRR, 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

Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm.

Shaoyi Huang, Dongkuan Xu, Ian En-Hsu Yen, Sung-En Chang, Bingbing Li, Shiyang Chen, Mimi Xie, 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

Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs.

Zhepeng Wang, Zhiding Liang, Shanglin Zhou, Caiwen Ding, Jinjun Xiong, Yiyu Shi, Weiwen Jiang

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

TAG: Transformer Attack from Gradient.

Jieren Deng, Yijue Wang, Ji Li, Chao Shang, Hang Liu, Sanguthevar Rajasekaran, Caiwen Ding

CoRR, 2021

Dr. Top-k: delegate-centric Top-k on GPUs.

Anil Gaihre, Da Zheng, Scott Weitze, Lingda Li, Shuaiwen Leon Song, Caiwen Ding, Xiaoye S. Li, Hang Liu

Proceedings of the International Conference for High Performance Computing, 2021

E.T.: re-thinking self-attention for transformer models on GPUs.

Shiyang Chen, Shaoyi Huang, Santosh Pandey, Bingbing Li, Guang R. Gao, Long Zheng, Caiwen Ding, Hang Liu

Proceedings of the International Conference for High Performance Computing, 2021

An End-to-end Multi-task Object Detection using Embedded GPU in Autonomous Driving.

Shanglin Zhou, Mimi Xie, Yufang Jin, Fei Miao, Caiwen Ding

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

FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator.

Geng Yuan, Payman Behnam, Zhengang Li, Ali Shafiee, Sheng Lin, Xiaolong Ma, Hang Liu, Xuehai Qian, Mahdi Nazm Bojnordi, Yanzhi Wang, Caiwen Ding

Proceedings of the 48th ACM/IEEE Annual International Symposium on Computer Architecture, 2021

Against Membership Inference Attack: Pruning is All You Need.

Yijue Wang, Chenghong Wang, Zigeng Wang, Shanglin Zhou, Hang Liu, Jinbo Bi, Caiwen Ding, Sanguthevar Rajasekaran

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

A Compression-Compilation Framework for On-mobile Real-time BERT Applications.

Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Enabling Retrain-free Deep Neural Network Pruning Using Surrogate Lagrangian Relaxation.

Deniz Gurevin, Mikhail A. Bragin, Caiwen Ding, Shanglin Zhou, Lynn Pepin, Bingbing Li, Fei Miao

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs: (Invited Paper).

Zhepeng Wang, Zhiding Liang, Shanglin Zhou, Caiwen Ding, Yiyu Shi, Weiwen Jiang

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

FL-DISCO: Federated Generative Adversarial Network for Graph-based Molecule Drug Discovery: Special Session Paper.

Daniel Manu, Yi Sheng, Junhuan Yang, Jieren Deng, Tong Geng, Ang Li, Caiwen Ding, Weiwen Jiang, Lei Yang

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

Co-Exploration of Graph Neural Network and Network-on-Chip Design Using AutoML.

Daniel Manu, Shaoyi Huang, Caiwen Ding, Lei Yang

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

A Secure and Efficient Federated Learning Framework for NLP.

Chenghong Wang, Jieren Deng, Xianrui Meng, Yijue Wang, Ji Li, Sheng Lin, Shuo Han, Fei Miao, Sanguthevar Rajasekaran, Caiwen Ding

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

TAG: Gradient Attack on Transformer-based Language Models.

Jieren Deng, Yijue Wang, Ji Li, Chenghong Wang, Chao Shang, Hang Liu, Sanguthevar Rajasekaran, Caiwen Ding

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

TinyADC: Peripheral Circuit-aware Weight Pruning Framework for Mixed-signal DNN Accelerators.

Geng Yuan, Payman Behnam, Yuxuan Cai, Ali Shafiee, Jingyan Fu, Zhiheng Liao, Zhengang Li, Xiaolong Ma, Jieren Deng, Jinhui Wang, Mahdi Nazm Bojnordi, Yanzhi Wang, Caiwen Ding

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2021

A Unified DNN Weight Pruning Framework Using Reweighted Optimization Methods.

Tianyun Zhang, Xiaolong Ma, Zheng Zhan, Shanglin Zhou, Caiwen Ding, Makan Fardad, Yanzhi Wang

Proceedings of the 58th ACM/IEEE Design Automation Conference, 2021

Dancing along Battery: Enabling Transformer with Run-time Reconfigurability on Mobile Devices.

Yuhong Song, Weiwen Jiang, Bingbing Li, Panjie Qi, Qingfeng Zhuge, Edwin Hsing-Mean Sha, Sakyasingha Dasgupta, Yiyu Shi, Caiwen Ding

Proceedings of the 58th ACM/IEEE Design Automation Conference, 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

2020

A Surrogate Lagrangian Relaxation-based Model Compression for Deep Neural Networks.

Deniz Gurevin, Shanglin Zhou, Lynn Pepin, Bingbing Li, Mikhail A. Bragin, Caiwen Ding, Fei Miao

CoRR, 2020

Achieving Real-Time Execution of Transformer-based Large-scale Models on Mobile with Compiler-aware Neural Architecture Optimization.

Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang

CoRR, 2020

SAPAG: A Self-Adaptive Privacy Attack From Gradients.

Yijue Wang, Jieren Deng, Dan Guo, Chenghong Wang, Xianrui Meng, Hang Liu, Caiwen Ding, Sanguthevar Rajasekaran

CoRR, 2020

ESMFL: Efficient and Secure Models for Federated Learning.

Sheng Lin, Chenghong Wang, Hongjia Li, Jieren Deng, Yanzhi Wang, Caiwen Ding

CoRR, 2020

MCMIA: Model Compression Against Membership Inference Attack in Deep Neural Networks.

Yijue Wang, Chenghong Wang, Zigeng Wang, Shanglin Zhou, Hang Liu, Jinbo Bi, Caiwen Ding, Sanguthevar Rajasekaran

CoRR, 2020

A Unified DNN Weight Compression Framework Using Reweighted Optimization Methods.

Tianyun Zhang, Xiaolong Ma, Zheng Zhan, Shanglin Zhou, Minghai Qin, Fei Sun, Yen-Kuang Chen, Caiwen Ding, Makan Fardad, Yanzhi Wang

CoRR, 2020

A DNN Compression Framework for SOT-MRAM-based Processing-In-Memory Engine.

Geng Yuan, Xiaolong Ma, Sheng Lin, Zhengang Li, Jieren Deng, Caiwen Ding

Proceedings of the 33rd IEEE International System-on-Chip Conference, 2020

An Efficient Deep Reinforcement Learning Framework for UAVs.

Shanglin Zhou, Bingbing Li, Caiwu Ding, Lu Lu, Caiwen Ding

Proceedings of the 21st International Symposium on Quality Electronic Design, 2020

FTRANS: energy-efficient acceleration of transformers using FPGA.

Bingbing Li, Santosh Pandey, Haowen Fang, Yanjun Lyv, Ji Li, Jieyang Chen, Mimi Xie, Lipeng Wan, Hang Liu, Caiwen Ding

Proceedings of the ISLPED '20: ACM/IEEE International Symposium on Low Power Electronics and Design, 2020

Towards an Efficient and General Framework of Robust Training for Graph Neural Networks.

Kaidi Xu, Sijia Liu, Pin-Yu Chen, Mengshu Sun, Caiwen Ding, Bhavya Kailkhura, Xue Lin

Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

A Privacy-Preserving-Oriented DNN Pruning and Mobile Acceleration Framework.

Yifan Gong, Zheng Zhan, Zhengang Li, Wei Niu, Xiaolong Ma, Wenhao Wang, Bin Ren, Caiwen Ding, Xue Lin, Xiaolin Xu, Yanzhi Wang

Proceedings of the GLSVLSI '20: Great Lakes Symposium on VLSI 2020, 2020

FTDL: An FPGA-tailored Architecture for Deep Learning Systems.

Runbin Shi, Yuhao Ding, Xuechao Wei, Hang Liu, Hayden Kwok-Hay So, Caiwen Ding

Proceedings of the FPGA '20: The 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2020

Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning.

Bingbing Li, Zhenglun Kong, Tianyun Zhang, Ji Li, Zhengang Li, Hang Liu, Caiwen Ding

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

FTDL: A Tailored FPGA-Overlay for Deep Learning with High Scalability.

Runbin Shi, Yuhao Ding, Xuechao Wei, He Li, Hang Liu, Hayden Kwok-Hay So, Caiwen Ding

Proceedings of the 57th ACM/IEEE Design Automation Conference, 2020

Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation.

Xiaolong Ma, Geng Yuan, Sheng Lin, Caiwen Ding, Fuxun Yu, Tao Liu, Wujie Wen, Xiang Chen, Yanzhi Wang

Proceedings of the 25th Asia and South Pacific Design Automation Conference, 2020

2019

HEIF: Highly Efficient Stochastic Computing-Based Inference Framework for Deep Neural Networks.

Zhe Li, Ji Li, Ao Ren, Ruizhe Cai, Caiwen Ding, Xuehai Qian, Jeffrey Draper, Bo Yuan, Jian Tang, Qinru Qiu, Yanzhi Wang

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2019

Normalization and dropout for stochastic computing-based deep convolutional neural networks.

Ji Li, Zihao Yuan, Zhe Li, Ao Ren, Caiwen Ding, Jeffrey Draper, Shahin Nazarian, Qinru Qiu, Bo Yuan, Yanzhi Wang

Integr., 2019

A SOT-MRAM-based Processing-In-Memory Engine for Highly Compressed DNN Implementation.

Geng Yuan, Xiaolong Ma, Sheng Lin, Zhengang Li, Caiwen Ding

CoRR, 2019

A Stochastic-Computing based Deep Learning Framework using Adiabatic Quantum-Flux-Parametron SuperconductingTechnology.

Ruizhe Cai, Ao Ren, Olivia Chen, Ning Liu, Caiwen Ding, Xuehai Qian, Jie Han, Wenhui Luo, Nobuyuki Yoshikawa, Yanzhi Wang

CoRR, 2019

Deep Compressed Pneumonia Detection for Low-Power Embedded Devices.

Hongjia Li, Sheng Lin, Ning Liu, Caiwen Ding, Yanzhi Wang

Proceedings of the Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention, 2019

An Ultra-Efficient Memristor-Based DNN Framework with Structured Weight Pruning and Quantization Using ADMM.

Geng Yuan, Xiaolong Ma, Caiwen Ding, Sheng Lin, Tianyun Zhang, Zeinab S. Jalali, Yilong Zhao, Li Jiang, Sucheta Soundarajan, Yanzhi Wang

Proceedings of the 2019 IEEE/ACM International Symposium on Low Power Electronics and Design, 2019

A stochastic-computing based deep learning framework using adiabatic quantum-flux-parametron superconducting technology.

Ruizhe Cai, Ao Ren, Olivia Chen, Ning Liu, Caiwen Ding, Xuehai Qian, Jie Han, Wenhui Luo, Nobuyuki Yoshikawa, Yanzhi Wang

Proceedings of the 46th International Symposium on Computer Architecture, 2019

E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs.

Zhe Li, Caiwen Ding, Siyue Wang, Wujie Wen, Youwei Zhuo, Chang Liu, Qinru Qiu, Wenyao Xu, Xue Lin, Xuehai Qian, Yanzhi Wang

Proceedings of the 25th IEEE International Symposium on High Performance Computer Architecture, 2019

A Majority Logic Synthesis Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits.

Ruizhe Cai, Olivia Chen, Ao Ren, Ning Liu, Caiwen Ding, Nobuyuki Yoshikawa, Yanzhi Wang

Proceedings of the 2019 on Great Lakes Symposium on VLSI, 2019

REQ-YOLO: A Resource-Aware, Efficient Quantization Framework for Object Detection on FPGAs.

Caiwen Ding, Shuo Wang, Ning Liu, Kaidi Xu, Yanzhi Wang, Yun Liang

Proceedings of the 2019 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2019

2018

Dynamic Reconfiguration of Thermoelectric Generators for Vehicle Radiators Energy Harvesting Under Location-Dependent Temperature Variations.

Jaemin Kim, Donkyu Baek, Caiwen Ding, Sheng Lin, Donghwa Shin, Xue Lin, Yanzhi Wang, Youngjin Cho, Sang Hyun Park, Naehyuck Chang

IEEE Trans. Very Large Scale Integr. Syst., 2018

Reconfigurable Photovoltaic Systems for Electric Vehicles.

Caiwen Ding, Hongjia Li, Weiwei Zheng, Yanzhi Wang, Xue Lin

IEEE Des. Test, 2018

A Fast and Effective Memristor-Based Method for Finding Approximate Eigenvalues and Eigenvectors of Non-negative Matrices.

Chenghong Wang, Zeinab S. Jalali, Caiwen Ding, Yanzhi Wang, Sucheta Soundarajan

Proceedings of the 2018 IEEE Computer Society Annual Symposium on VLSI, 2018

Towards Budget-Driven Hardware Optimization for Deep Convolutional Neural Networks Using Stochastic Computing.

Zhe Li, Ji Li, Ao Ren, Caiwen Ding, Jeffrey Draper, Qinru Qiu, Bo Yuan, Yanzhi Wang

Proceedings of the 2018 IEEE Computer Society Annual Symposium on VLSI, 2018

Learning Topics Using Semantic Locality.

Ziyi Zhao, Krittaphat Pugdeethosapol, Sheng Lin, Zhe Li, Caiwen Ding, Yanzhi Wang, Qinru Qiu

Proceedings of the 24th International Conference on Pattern Recognition, 2018

Efficient Recurrent Neural Networks using Structured Matrices in FPGAs.

Zhe Li, Shuo Wang, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Yun Liang

Proceedings of the 6th International Conference on Learning Representations, 2018

Structured Weight Matrices-Based Hardware Accelerators in Deep Neural Networks: FPGAs and ASICs.

Caiwen Ding, Ao Ren, Geng Yuan, Xiaolong Ma, Jiayu Li, Ning Liu, Bo Yuan, Yanzhi Wang

Proceedings of the 2018 on Great Lakes Symposium on VLSI, 2018

C-LSTM: Enabling Efficient LSTM using Structured Compression Techniques on FPGAs.

Shuo Wang, Zhe Li, Caiwen Ding, Bo Yuan, Qinru Qiu, Yanzhi Wang, Yun Liang

Proceedings of the 2018 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2018

Prediction-based fast thermoelectric generator reconfiguration for energy harvesting from vehicle radiators.

Hanchen Yang, Feiyang Kang, Caiwen Ding, Ji Li, Jaemin Kim, Donkyu Baek, Shahin Nazarian, Xue Lin, Paul Bogdan, Naehyuck Chang

Proceedings of the 2018 Design, Automation & Test in Europe Conference & Exhibition, 2018

FFT-based deep learning deployment in embedded systems.

Sheng Lin, Ning Liu, Mahdi Nazemi, Hongjia Li, Caiwen Ding, Yanzhi Wang, Massoud Pedram

Proceedings of the 2018 Design, Automation & Test in Europe Conference & Exhibition, 2018

VIBNN: Hardware Acceleration of Bayesian Neural Networks.

Ruizhe Cai, Ao Ren, Ning Liu, Caiwen Ding, Luhao Wang, Xuehai Qian, Massoud Pedram, Yanzhi Wang

Proceedings of the Twenty-Third International Conference on Architectural Support for Programming Languages and Operating Systems, 2018

Towards Ultra-High Performance and Energy Efficiency of Deep Learning Systems: An Algorithm-Hardware Co-Optimization Framework.

Yanzhi Wang, Caiwen Ding, Zhe Li, Geng Yuan, Siyu Liao, Xiaolong Ma, Bo Yuan, Xuehai Qian, Jian Tang, Qinru Qiu, Xue Lin

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Multisource Indoor Energy Harvesting for Nonvolatile Processors.

Caiwen Ding, Ning Liu, Yanzhi Wang, Ji Li, Soroush Heidari, Jingtong Hu, Yongpan Liu

IEEE Des. Test, 2017

CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-CirculantWeight Matrices.

Caiwen Ding, Siyu Liao, Yanzhi Wang, Zhe Li, Ning Liu, Youwei Zhuo, Chao Wang, Xuehai Qian, Yu Bai, Geng Yuan, Xiaolong Ma, Yipeng Zhang, Jian Tang, Qinru Qiu, Xue Lin, Bo Yuan

CoRR, 2017

Memristor crossbar-based ultra-efficient next-generation baseband processors.

Geng Yuan, Caiwen Ding, Ruizhe Cai, Xiaolong Ma, Ziyi Zhao, Ao Ren, Bo Yuan, Yanzhi Wang

Proceedings of the IEEE 60th International Midwest Symposium on Circuits and Systems, 2017

CirCNN: accelerating and compressing deep neural networks using block-circulant weight matrices.

Caiwen Ding, Siyu Liao, Yanzhi Wang, Zhe Li, Ning Liu, Youwei Zhuo, Chao Wang, Xuehai Qian, Yu Bai, Geng Yuan, Xiaolong Ma, Yipeng Zhang, Jian Tang, Qinru Qiu, Xue Lin, Bo Yuan

Proceedings of the 50th Annual IEEE/ACM International Symposium on Microarchitecture, 2017

Reconfigurable thermoelectric generators for vehicle radiators energy harvesting.

Donkyu Baek, Caiwen Ding, Sheng Lin, Donghwa Shin, Jaemin Kim, Xue Lin, Yanzhi Wang, Naehyuck Chang

Proceedings of the 2017 IEEE/ACM International Symposium on Low Power Electronics and Design, 2017

Hardware-driven nonlinear activation for stochastic computing based deep convolutional neural networks.

Ji Li, Zihao Yuan, Zhe Li, Caiwen Ding, Ao Ren, Qinru Qiu, Jeffrey Draper, Yanzhi Wang

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

Softmax Regression Design for Stochastic Computing Based Deep Convolutional Neural Networks.

Zihao Yuan, Ji Li, Zhe Li, Caiwen Ding, Ao Ren, Bo Yuan, Qinru Qiu, Jeffrey Draper, Yanzhi Wang

Proceedings of the on Great Lakes Symposium on VLSI 2017, 2017

SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing.

Ao Ren, Zhe Li, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Ji Li, Xuehai Qian, Bo Yuan

Proceedings of the Twenty-Second International Conference on Architectural Support for Programming Languages and Operating Systems, 2017

Towards acceleration of deep convolutional neural networks using stochastic computing.

Ji Li, Ao Ren, Zhe Li, Caiwen Ding, Bo Yuan, Qinru Qiu, Yanzhi Wang

Proceedings of the 22nd Asia and South Pacific Design Automation Conference, 2017

Algorithm accelerations for luminescent solar concentrator-enhanced reconfigurable onboard photovoltaic system.

Caiwen Ding, Ji Li, Weiwei Zheng, Naehyuck Chang, Xue Lin, Yanzhi Wang

Proceedings of the 22nd Asia and South Pacific Design Automation Conference, 2017

2016

Multi-source in-door energy harvesting for non-volatile processors.

Caiwen Ding, Soroush Heidari, Yanzhi Wang, Yongpan Liu, Jingtong Hu

Proceedings of the IEEE International Symposium on Circuits and Systems, 2016

Luminescent solar concentrator-based photovoltaic reconfiguration for hybrid and plug-in electric vehicles.

Caiwen Ding, Hongjia Li, Weiwei Zheng, Yanzhi Wang, Naehyuck Chang, Xue Lin

Proceedings of the 34th IEEE International Conference on Computer Design, 2016

Dynamic converter reconfiguration for near-threshold non-volatile processors using in-door energy harvesting.

Caiwen Ding, Hongjia Li, Jingtong Hu, Yongpan Liu, Yanzhi Wang

Proceedings of the 34th IEEE International Conference on Computer Design, 2016

Neural Network-based Prediction Algorithms for In-Door Multi-Source Energy Harvesting System for Non-Volatile Processors.

Ning Liu, Caiwen Ding, Yanzhi Wang, Jingtong Hu

Proceedings of the 26th edition on Great Lakes Symposium on VLSI, 2016

2015

Multi-source energy harvesting management and optimization for non-volatile processors.

Soroush Heidari, Caiwen Ding, Yongpan Liu, Yanzhi Wang, Jingtong Hu

Proceedings of the Sixth International Green and Sustainable Computing Conference, 2015