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2020 – today
- 2025
[c103]Antian Wang
, Weihang Tan, Zhenyu Xu, Tao Wei, Caiwen Ding, Keshab K. Parhi, Yingjie Lao:
HEDWIG: Homomorphic Encryption Accelerator Design Using BFV-HPS With HiGh-Speed Fixed-Point Approximation. FPGA 2025: 184- [i89]Yi Zhang, Bin Lei, Mohamadamin Rajabinezhad, Caiwen Ding, Shan Zuo:
Observer-Based Data-Driven Consensus Control for Nonlinear Multi-Agent Systems against DoS and FDI attacks. CoRR abs/2501.00872 (2025) - [i88]Can Jin, Hongwu Peng, Anxiang Zhang, Nuo Chen, Jiahui Zhao, Xi Xie, Kuangzheng Li, Shuya Feng, Kai Zhong, Caiwen Ding, Dimitris N. Metaxas:
RankFlow: A Multi-Role Collaborative Reranking Workflow Utilizing Large Language Models. CoRR abs/2502.00709 (2025) - 2024
- [j13]Deniz Gurevin, Caiwen Ding, Omer Khan:
Exploiting Intrinsic Redundancies in Dynamic Graph Neural Networks for Processing Efficiency. IEEE Comput. Archit. Lett. 23(2): 170-174 (2024) - [j12]Sanbao Su, Songyang Han, Yiming Li, Zhili Zhang, Chen Feng, Caiwen Ding, Fei Miao:
Collaborative Multi-Object Tracking With Conformal Uncertainty Propagation. IEEE Robotics Autom. Lett. 9(4): 3323-3330 (2024) - [j11]Songyang Han, Shanglin Zhou, Jiangwei Wang, Lynn Pepin, Caiwen Ding, Jie Fu, Fei Miao:
A Multi-Agent Reinforcement Learning Approach for Safe and Efficient Behavior Planning of Connected Autonomous Vehicles. IEEE Trans. Intell. Transp. Syst. 25(5): 3654-3670 (2024) - [c102]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: 683-698 - [c101]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:
SuperFlow: A Fully-Customized RTL-to-GDS Design Automation Flow for Adiabatic Quantum- Flux - Parametron Superconducting Circuits. DATE 2024: 1-6 - [c100]Shengkun Tang, Yaqing Wang, Caiwen Ding, Yi Liang, Yao Li, Dongkuan Xu:
AdaDiff: Accelerating Diffusion Models Through Step-Wise Adaptive Computation. ECCV (79) 2024: 73-90 - [c99]Deniz Gurevin, Mohsin Shan, Shaoyi Huang, Md Amit Hasan, Caiwen Ding, Omer Khan:
PruneGNN: Algorithm-Architecture Pruning Framework for Graph Neural Network Acceleration. HPCA 2024: 108-123 - [c98]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:
Quasar-ViT: Hardware-Oriented Quantization-Aware Architecture Search for Vision Transformers. ICS 2024: 324-337 - [c97]Bin Lei, Yi Zhang, Shan Zuo, Ali Payani, Caiwen Ding:
MACM: Utilizing a Multi-Agent System for Condition Mining in Solving Complex Mathematical Problems. NeurIPS 2024 - [c96]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: 14-20 - [d2]Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding:
ASPLOS 2024 Artifact for "MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training". Version 1. Zenodo, 2024 [all versions]
- [d1]Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding:
ASPLOS 2024 Artifact for "MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training". Version 2. Zenodo, 2024 [all versions] - [i87]Bin Lei, Le Chen, Caiwen Ding:
FlashVideo: A Framework for Swift Inference in Text-to-Video Generation. CoRR abs/2401.00869 (2024) - [i86]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 abs/2401.11664 (2024) - [i85]Jiahui Zhao, Ziyi Meng, Stepan Gordeev, Zijie Pan, Dongjin Song, Sandro Steinbach, Caiwen Ding:
Key Information Retrieval to Classify the Unstructured Data Content of Preferential Trade Agreements. CoRR abs/2401.12520 (2024) - [i84]Binghao Lu, Caiwen Ding, Jinbo Bi, Dongjin Song:
Weakly Supervised Change Detection via Knowledge Distillation and Multiscale Sigmoid Inference. CoRR abs/2403.05796 (2024) - [i83]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 abs/2406.02629 (2024) - [i82]Tong Zhou, Jiahui Zhao, Yukui Luo, Xi Xie, Wujie Wen, Caiwen Ding, Xiaolin Xu:
AdaPI: Facilitating DNN Model Adaptivity for Efficient Private Inference in Edge Computing. CoRR abs/2407.05633 (2024) - [i81]Zijie Pan, Stepan Gordeev, Jiahui Zhao, Ziyi Meng, Caiwen Ding, Sandro Steinbach, Dongjin Song:
International Trade Flow Prediction with Bilateral Trade Provisions. CoRR abs/2407.13698 (2024) - [i80]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:
Quasar-ViT: Hardware-Oriented Quantization-Aware Architecture Search for Vision Transformers. CoRR abs/2407.18175 (2024) - [i79]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:
SuperFlow: A Fully-Customized RTL-to-GDS Design Automation Flow for Adiabatic Quantum-Flux-Parametron Superconducting Circuits. CoRR abs/2407.18209 (2024) - [i78]Nicole Meng, Caleb Manicke, David Chen, Yingjie Lao, Caiwen Ding, Pengyu Hong, Kaleel Mahmood:
Theoretical Corrections and the Leveraging of Reinforcement Learning to Enhance Triangle Attack. CoRR abs/2411.12071 (2024) - [i77]Jinwei Tang, Jiayin Qin, Kiran Thorat, Chen Tian, Yu Cao, Yang Zhao, Caiwen Ding:
HiVeGen - Hierarchical LLM-based Verilog Generation for Scalable Chip Design. CoRR abs/2412.05393 (2024) - [i76]Le Chen, Bin Lei, Dunzhi Zhou, Pei-Hung Lin, Chunhua Liao, Caiwen Ding, Ali Jannesari:
Fortran2CPP: Automating Fortran-to-C++ Migration using LLMs via Multi-Turn Dialogue and Dual-Agent Integration. CoRR abs/2412.19770 (2024) - 2023
- [j10]Zeinab S. Jalali, Chenghong Wang, Griffin Kearney, Geng Yuan, Caiwen Ding, Yinan Zhou, Yanzhi Wang, Sucheta Soundarajan:
Memristor-Based Spectral Decomposition of Matrices and Its Applications. IEEE Trans. Computers 72(5): 1460-1472 (2023) - [j9]Shanglin Zhou, Mikhail A. Bragin, Deniz Gurevin, Lynn Pepin, Fei Miao, Caiwen Ding:
Surrogate Lagrangian Relaxation: A Path to Retrain-Free Deep Neural Network Pruning. ACM Trans. Design Autom. Electr. Syst. 28(6): 102:1-102:19 (2023) - [c95]Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu:
You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model. CVPR 2023: 10781-10791 - [c94]Lei Zhang, Jie Zhang, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, Dongkuan Xu:
Accelerating Dataset Distillation via Model Augmentation. CVPR 2023: 11950-11959 - [c93]Yifan Gong, Pu Zhao, Zheng Zhan, Yushu Wu, Chao Wu, Zhenglun Kong, Minghai Qin, Caiwen Ding, Yanzhi Wang:
Condense: A Framework for Device and Frequency Adaptive Neural Network Models on the Edge. DAC 2023: 1-6 - [c92]Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding:
Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration. DAC 2023: 1-6 - [c91]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: 1-6 - [c90]Zhuo Liu, Yunan Yang, Zhenyu Pan, Anshujit Sharma, Amit Hasan, Caiwen Ding, Ang Li, Michael C. Huang, Tong Geng:
Ising-CF: A Pathbreaking Collaborative Filtering Method Through Efficient Ising Machine Learning. DAC 2023: 1-6 - [c89]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: 1-6 - [c88]Shanglin Zhou, Yingjie Li, Minhan Lou, Weilu Gao, Zhijie Shi, Cunxi Yu, Caiwen Ding:
Physics-aware Roughness Optimization for Diffractive Optical Neural Networks. DAC 2023: 1-6 - [c87]Andy Trinh, Shivam Sheth, Anil Gaihre, Caiwen Ding, Jieyang Chen, Feiyi Wang, David Pugmire, Scott Klasky, Hang Liu, Lipeng Wan:
Understanding Node Allocation on Leadership-Class Supercomputers with Graph Analytics. HPCC/DSS/SmartCity/DependSys 2023: 780-787 - [c86]Bin Lei, Caiwen Ding, Le Chen, Pei-Hung Lin, Chunhua Liao:
Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C++. HPEC 2023: 1-7 - [c85]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: 1-9 - [c84]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: 5155-5165 - [c83]Ran Ran, Xinwei Luo, Wei Wang, Tao Liu, Gang Quan, Xiaolin Xu, Caiwen Ding, Wujie Wen:
SpENCNN: Orchestrating Encoding and Sparsity for Fast Homomorphically Encrypted Neural Network Inference. ICML 2023: 28718-28728 - [c82]Sanbao Su, Yiming Li, Sihong He, Songyang Han, Chen Feng, Caiwen Ding, Fei Miao:
Uncertainty Quantification of Collaborative Detection for Self-Driving. ICRA 2023: 5588-5594 - [c81]Bingbing Li, Zigeng Wang, Shaoyi Huang, Mikhail A. Bragin, Ji Li, Caiwen Ding:
Towards Lossless Head Pruning through Automatic Peer Distillation for Language Models. IJCAI 2023: 5113-5121 - [c80]Mohsin Shan, Deniz Gurevin, Jared Nye, Caiwen Ding, Omer Khan:
MergePath-SpMM: Parallel Sparse Matrix-Matrix Algorithm for Graph Neural Network Acceleration. ISPASS 2023: 145-156 - [c79]Ya-sine Agrignan, Shanglin Zhou, Jun Bai, Sahidul Islam, Sheida Nabavi, Mimi Xie, Caiwen Ding:
A Deep Learning Approach for Ventricular Arrhythmias Classification using Microcontroller. ISQED 2023: 1-5 - [c78]Zigeng Wang, Bingbing Li, Xia Xiao, Tianyun Zhang, Mikhail A. Bragin, Bing Yan, Caiwen Ding, Sanguthevar Rajasekaran:
Automatic Subnetwork Search Through Dynamic Differentiable Neuron Pruning. ISQED 2023: 1-6 - [c77]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: 628-640 - [c76]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 - [c75]Shiyang Chen, Da Zheng, Caiwen Ding, Chengying Huan, Yuede Ji, Hang Liu:
TANGO: re-thinking quantization for graph neural network training on GPUs. SC 2023: 38:1-38:14 - [c74]Ce Feng, Nuo Xu, Wujie Wen, Parv Venkitasubramaniam, Caiwen Ding:
Spectral-DP: Differentially Private Deep Learning through Spectral Perturbation and Filtering. SP 2023: 1944-1960 - [i75]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 abs/2302.02292 (2023) - [i74]Songyang Han, Shanglin Zhou, Lynn Pepin, Jiangwei Wang, Caiwen Ding, Fei Miao:
Shared Information-Based Safe And Efficient Behavior Planning For Connected Autonomous Vehicles. CoRR abs/2302.04321 (2023) - [i73]Sanbao Su, Songyang Han, Yiming Li, Zhili Zhang, Chen Feng, Caiwen Ding, Fei Miao:
Collaborative Multi-Object Tracking with Conformal Uncertainty Propagation. CoRR abs/2303.14346 (2023) - [i72]Shanglin Zhou, Yingjie Li, Minhan Lou, Weilu Gao, Zhijie Shi, Cunxi Yu, Caiwen Ding:
Physics-aware Roughness Optimization for Diffractive Optical Neural Networks. CoRR abs/2304.01500 (2023) - [i71]Shanglin Zhou, Mikhail A. Bragin, Lynn Pepin, Deniz Gurevin, Fei Miao, Caiwen Ding:
Surrogate Lagrangian Relaxation: A Path To Retrain-free Deep Neural Network Pruning. CoRR abs/2304.04120 (2023) - [i70]Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding:
Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration. CoRR abs/2304.12214 (2023) - [i69]Lijun Zhang, Xiao Liu, Kaleel Mahmood, Caiwen Ding, Hui Guan:
Dynamic Gradient Balancing for Enhanced Adversarial Attacks on Multi-Task Models. CoRR abs/2305.12066 (2023) - [i68]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 abs/2306.15513 (2023) - [i67]Bin Lei, Caiwen Ding, Le Chen, Pei-Hung Lin, Chunhua Liao:
Creating a Dataset for High-Performance Computing Code Translation: A Bridge Between HPC Fortran and C++. CoRR abs/2307.07686 (2023) - [i66]Ce Feng, Nuo Xu, Wujie Wen, Parv Venkitasubramaniam, Caiwen Ding:
Spectral-DP: Differentially Private Deep Learning through Spectral Perturbation and Filtering. CoRR abs/2307.13231 (2023) - [i65]Shiyang Chen, Da Zheng, Caiwen Ding, Chengying Huan, Yuede Ji, Hang Liu:
Tango: rethinking quantization for graph neural network training on GPUs. CoRR abs/2308.00890 (2023) - [i64]Bin Lei, Pei-Hung Lin, Chunhua Liao, Caiwen Ding:
Boosting Logical Reasoning in Large Language Models through a New Framework: The Graph of Thought. CoRR abs/2308.08614 (2023) - [i63]Bin Lei, Sheng Lin, Pei-Hung Lin, Chunhua Liao, Caiwen Ding:
Towards Zero Memory Footprint Spiking Neural Network Training. CoRR abs/2308.08649 (2023) - [i62]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 abs/2308.10134 (2023) - [i61]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 abs/2308.11825 (2023) - [i60]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 abs/2309.14331 (2023) - [i59]Shengkun Tang, Yaqing Wang, Caiwen Ding, Yi Liang, Yao Li, Dongkuan Xu:
DeeDiff: Dynamic Uncertainty-Aware Early Exiting for Accelerating Diffusion Model Generation. CoRR abs/2309.17074 (2023) - [i58]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 abs/2311.04417 (2023) - [i57]Kiran Thorat, Jiahui Zhao, Yaotian Liu, Hongwu Peng, Xi Xie, Bin Lei, Jeff Zhang, Caiwen Ding:
Advanced Large Language Model (LLM)-Driven Verilog Development: Enhancing Power, Performance, and Area Optimization in Code Synthesis. CoRR abs/2312.01022 (2023) - [i56]Hongwu Peng, Xi Xie, Kaustubh Shivdikar, Md Amit Hasan, Jiahui Zhao, Shaoyi Huang, Omer Khan, David R. Kaeli, Caiwen Ding:
MaxK-GNN: Towards Theoretical Speed Limits for Accelerating Graph Neural Networks Training. CoRR abs/2312.08656 (2023) - 2022
- [j8]Jiangce Chen, Horea T. Ilies, Caiwen Ding:
Graph-Based Shape Analysis for Heterogeneous Geometric Datasets: Similarity, Retrieval and Substructure Matching. Comput. Aided Des. 143: 103125 (2022) - [c73]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:
Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm. ACL (1) 2022: 190-200 - [c72]Yijue Wang, Nuo Xu, Shaoyi Huang, Kaleel Mahmood, Dan Guo, Caiwen Ding, Wujie Wen, Sanguthevar Rajasekaran:
Analyzing and Defending against Membership Inference Attacks in Natural Language Processing Classification. IEEE Big Data 2022: 5823-5832 - [c71]Bingyu Liu, Rujia Wang, Zhongjie Ba, Shanglin Zhou, Caiwen Ding, Yuan Hong:
Poster: Cryptographic Inferences for Video Deep Neural Networks. CCS 2022: 3395-3397 - [c70]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: 1135-1140 - [c69]Sahidul Islam, Jieren Deng, Shanglin Zhou, Chen Pan, Caiwen Ding, Mimi Xie:
Enabling Fast Deep Learning on Tiny Energy-Harvesting IoT Devices. DATE 2022: 921-926 - [c68]Sahidul Islam, Shanglin Zhou, Ran Ran, Yufang Jin, Wujie Wen, Caiwen Ding, Mimi Xie:
EVE: Environmental Adaptive Neural Network Models for Low-Power Energy Harvesting System. ICCAD 2022: 35:1-35:9 - [c67]Yifan Gong, Zheng Zhan, Pu Zhao, Yushu Wu, Chao Wu, Caiwen Ding, Weiwen Jiang, Minghai Qin, Yanzhi Wang:
All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management. ICCAD 2022: 133:1-133:9 - [c66]Deniz Gurevin, Mohsin Shan, Tong Geng, Weiwen Jiang, Caiwen Ding, Omer Khan:
Towards Real-Time Temporal Graph Learning. ICCD 2022: 263-271 - [c65]Hongwu Peng, Deniz Gurevin, Shaoyi Huang, Tong Geng, Weiwen Jiang, Omer Khan, Caiwen Ding:
Towards Sparsification of Graph Neural Networks. ICCD 2022: 272-279 - [c64]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: 280-289 - [c63]Zhirui Hu, Jinyang Li, Zhenyu Pan, Shanglin Zhou, Lei Yang, Caiwen Ding, Omer Khan, Tong Geng, Weiwen Jiang:
On the Design of Quantum Graph Convolutional Neural Network in the NISQ-Era and Beyond. ICCD 2022: 290-297 - [c62]Yijue Wang, Jieren Deng, Dan Guo, Chenghong Wang, Xianrui Meng, Hang Liu, Chao Shang, Binghui Wang, Qin Cao, Caiwen Ding, Sanguthevar Rajasekaran:
Variance of the Gradient Also Matters: Privacy Leakage from Gradients. IJCNN 2022: 1-8 - [c61]Md. Oli-Uz-Zaman, Saleh Ahmad Khan, Geng Yuan, Yanzhi Wang, Zhiheng Liao, Jingyan Fu, Caiwen Ding, Jinhui Wang:
Reliability Improvement in RRAM-based DNN for Edge Computing. ISCAS 2022: 581-585 - [c60]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: 1-6 - [c59]Wei Wei, Sahidul Islam, Jishnu Banerjee, Shanglin Zhou, Chen Pan, Caiwen Ding, Mimi Xie:
An Intermittent OTA Approach to Update the DL Weights on Energy Harvesting Devices. ISQED 2022: 1-6 - [c58]Samuel Alexander Stein, Betis Baheri, Daniel Chen, Ying Mao, Qiang Guan, Ang Li, Shuai Xu, Caiwen Ding:
QuClassi: A Hybrid Deep Neural Network Architecture based on Quantum State Fidelity. MLSys 2022 - [i55]Jieren Deng, Chenghong Wang, Xianrui Meng, Yijue Wang, Ji Li, Sheng Lin, Shuo Han, Fei Miao, Sanguthevar Rajasekaran, Caiwen Ding:
A Secure and Efficient Federated Learning Framework for NLP. CoRR abs/2201.11934 (2022) - [i54]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 abs/2206.10461 (2022) - [i53]Sahidul Islam, Shanglin Zhou, Ran Ran, Yufang Jin, Wujie Wen, Caiwen Ding, Mimi Xie:
EVE: Environmental Adaptive Neural Network Models for Low-power Energy Harvesting System. CoRR abs/2207.09258 (2022) - [i52]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 abs/2208.03646 (2022) - [i51]Nuo Xu, Kaleel Mahmood, Haowen Fang, Ethan Rathbun, Caiwen Ding, Wujie Wen:
Securing the Spike: On the Transferabilty and Security of Spiking Neural Networks to Adversarial Examples. CoRR abs/2209.03358 (2022) - [i50]Hongwu Peng, Deniz Gurevin, Shaoyi Huang, Tong Geng, Weiwen Jiang, Omer Khan, Caiwen Ding:
Towards Sparsification of Graph Neural Networks. CoRR abs/2209.04766 (2022) - [i49]Sanbao Su, Yiming Li, Sihong He, Songyang Han, Chen Feng, Caiwen Ding, Fei Miao:
Uncertainty Quantification of Collaborative Detection for Self-Driving. CoRR abs/2209.08162 (2022) - [i48]Deniz Gurevin, Mohsin Shan, Tong Geng, Weiwen Jiang, Caiwen Ding, Omer Khan:
Towards Real-Time Temporal Graph Learning. CoRR abs/2210.04114 (2022) - [i47]Caiwu Ding, Hongwu Peng, Lu Lu, Caiwen Ding:
Aerial Manipulation Using a Novel Unmanned Aerial Vehicle Cyber-Physical System. CoRR abs/2210.15632 (2022) - [i46]Bin Lei, Shaoyi Huang, Caiwen Ding, Monika Filipovska:
Efficient Traffic State Forecasting using Spatio-Temporal Network Dependencies: A Sparse Graph Neural Network Approach. CoRR abs/2211.03033 (2022) - [i45]Shengkun Tang, Yaqing Wang, Zhenglun Kong, Tianchi Zhang, Yao Li, Caiwen Ding, Yanzhi Wang, Yi Liang, Dongkuan Xu:
You Need Multiple Exiting: Dynamic Early Exiting for Accelerating Unified Vision Language Model. CoRR abs/2211.11152 (2022) - [i44]Ethan Rathbun, Kaleel Mahmood, Sohaib Ahmad, Caiwen Ding, Marten van Dijk:
Game Theoretic Mixed Experts for Combinational Adversarial Machine Learning. CoRR abs/2211.14669 (2022) - [i43]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 abs/2211.16667 (2022) - [i42]Yifan Gong, Zheng Zhan, Pu Zhao, Yushu Wu, Chao Wu, Caiwen Ding, Weiwen Jiang, Minghai Qin, Yanzhi Wang:
All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management. CoRR abs/2212.05122 (2022) - [i41]Lei Zhang, Jie Zhang, Bowen Lei, Subhabrata Mukherjee, Xiang Pan, Bo Zhao, Caiwen Ding, Yao Li, Dongkuan Xu:
Accelerating Dataset Distillation via Model Augmentation. CoRR abs/2212.06152 (2022) - 2021
- [j7]Caiwu Ding, Lu Lu, Cong Wang, Caiwen Ding:
Design, Sensing, and Control of a Novel UAV Platform for Aerial Drilling and Screwing. IEEE Robotics Autom. Lett. 6(2): 3176-3183 (2021) - [j6]Santosh Pandey, Zhibin Wang, Sheng Zhong, Chen Tian, Bolong Zheng, Xiaoye S. Li, Lingda Li, Adolfy Hoisie, Caiwen Ding, Dong Li, Hang Liu:
Trust: Triangle Counting Reloaded on GPUs. IEEE Trans. Parallel Distributed Syst. 32(11): 2646-2660 (2021) - [c57]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: 85-92 - [c56]Tianyun Zhang, Xiaolong Ma, Zheng Zhan, Shanglin Zhou, Caiwen Ding, Makan Fardad, Yanzhi Wang:
A Unified DNN Weight Pruning Framework Using Reweighted Optimization Methods. DAC 2021: 493-498 - [c55]Yuhong Song, Weiwen Jiang, Bingbing Li, Panjie Qi, Qingfeng Zhuge, Edwin Hsing-Mean Sha, Sakyasingha Dasgupta, Yiyu Shi, Caiwen Ding:
Dancing along Battery: Enabling Transformer with Run-time Reconfigurability on Mobile Devices. DAC 2021: 1003-1008 - [c54]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:
TinyADC: Peripheral Circuit-aware Weight Pruning Framework for Mixed-signal DNN Accelerators. DATE 2021: 926-931 - [c53]Jieren Deng, Yijue Wang, Ji Li, Chenghong Wang, Chao Shang, Hang Liu, Sanguthevar Rajasekaran, Caiwen Ding:
TAG: Gradient Attack on Transformer-based Language Models. EMNLP (Findings) 2021: 3600-3610 - [c52]Chenghong Wang, Jieren Deng, Xianrui Meng, Yijue Wang, Ji Li, Sheng Lin, Shuo Han, Fei Miao, Sanguthevar Rajasekaran, Caiwen Ding:
A Secure and Efficient Federated Learning Framework for NLP. EMNLP (1) 2021: 7676-7682 - [c51]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: 169-174 - [c50]Daniel Manu, Shaoyi Huang, Caiwen Ding, Lei Yang:
Co-Exploration of Graph Neural Network and Network-on-Chip Design Using AutoML. ACM Great Lakes Symposium on VLSI 2021: 175-180 - [c49]Daniel Manu, Yi Sheng, Junhuan Yang, Jieren Deng, Tong Geng, Ang Li, Caiwen Ding, Weiwen Jiang, Lei Yang:
FL-DISCO: Federated Generative Adversarial Network for Graph-based Molecule Drug Discovery: Special Session Paper. ICCAD 2021: 1-7 - [c48]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: 1-7 - [c47]Zhepeng Wang, Zhiding Liang, Shanglin Zhou, Caiwen Ding, Yiyu Shi, Weiwen Jiang:
Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs: (Invited Paper). ICCAD 2021: 1-7 - [c46]Deniz Gurevin, Mikhail A. Bragin, Caiwen Ding, Shanglin Zhou, Lynn Pepin, Bingbing Li, Fei Miao:
Enabling Retrain-free Deep Neural Network Pruning Using Surrogate Lagrangian Relaxation. IJCAI 2021: 2497-2504 - [c45]Yijue Wang, Chenghong Wang, Zigeng Wang, Shanglin Zhou, Hang Liu, Jinbo Bi, Caiwen Ding, Sanguthevar Rajasekaran:
Against Membership Inference Attack: Pruning is All You Need. IJCAI 2021: 3141-3147 - [c44]Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang:
A Compression-Compilation Framework for On-mobile Real-time BERT Applications. IJCAI 2021: 5000-5003 - [c43]Geng Yuan, Payman Behnam, Zhengang Li, Ali Shafiee, Sheng Lin, Xiaolong Ma, Hang Liu, Xuehai Qian, Mahdi Nazm Bojnordi, Yanzhi Wang, Caiwen Ding:
FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator. ISCA 2021: 265-278 - [c42]Shanglin Zhou, Mimi Xie, Yufang Jin, Fei Miao, Caiwen Ding:
An End-to-end Multi-task Object Detection using Embedded GPU in Autonomous Driving. ISQED 2021: 122-128 - [c41]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: 142-148 - [c40]Shiyang Chen, Shaoyi Huang, Santosh Pandey, Bingbing Li, Guang R. Gao, Long Zheng, Caiwen Ding, Hang Liu:
E.T.: re-thinking self-attention for transformer models on GPUs. SC 2021: 25 - [c39]Anil Gaihre, Da Zheng, Scott Weitze, Lingda Li, Shuaiwen Leon Song, Caiwen Ding, Xiaoye S. Li, Hang Liu:
Dr. Top-k: delegate-centric Top-k on GPUs. SC 2021: 39 - [i40]Yuhong Song, Weiwen Jiang, Bingbing Li, Panjie Qi, Qingfeng Zhuge, Edwin Hsing-Mean Sha, Sakyasingha Dasgupta, Yiyu Shi, Caiwen Ding:
Dancing along Battery: Enabling Transformer with Run-time Reconfigurability on Mobile Devices. CoRR abs/2102.06336 (2021) - [i39]Jieren Deng, Yijue Wang, Ji Li, Chao Shang, Hang Liu, Sanguthevar Rajasekaran, Caiwen Ding:
TAG: Transformer Attack from Gradient. CoRR abs/2103.06819 (2021) - [i38]Santosh Pandey, Zhibin Wang, Sheng Zhong, Chen Tian, Bolong Zheng, Xiaoye S. Li, Lingda Li, Adolfy Hoisie, Caiwen Ding, Dong Li, Hang Liu:
TRUST: Triangle Counting Reloaded on GPUs. CoRR abs/2103.08053 (2021) - [i37]Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang:
A Compression-Compilation Framework for On-mobile Real-time BERT Applications. CoRR abs/2106.00526 (2021) - [i36]Geng Yuan, Payman Behnam, Zhengang Li, Ali Shafiee, Sheng Lin, Xiaolong Ma, Hang Liu, Xuehai Qian, Mahdi Nazm Bojnordi, Yanzhi Wang, Caiwen Ding:
FORMS: Fine-grained Polarized ReRAM-based In-situ Computation for Mixed-signal DNN Accelerator. CoRR abs/2106.09144 (2021) - [i35]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 abs/2108.04811 (2021) - [i34]Zhepeng Wang, Zhiding Liang, Shanglin Zhou, Caiwen Ding, Jinjun Xiong, Yiyu Shi, Weiwen Jiang:
Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs. CoRR abs/2109.03806 (2021) - [i33]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 abs/2109.06355 (2021) - [i32]Anil Gaihre, Da Zheng, Scott Weitze, Lingda Li, Shuaiwen Leon Song, Caiwen Ding, Xiaoye S. Li, Hang Liu:
Dr. Top-k: Delegate-Centric Top-k on GPUs. CoRR abs/2109.08219 (2021) - [i31]Shaoyi Huang, Dongkuan Xu, Ian En-Hsu Yen, Sung-En Chang, Bingbing Li, Shiyang Chen, Mimi Xie, Hang Liu, Caiwen Ding:
Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm. CoRR abs/2110.08190 (2021) - [i30]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 abs/2110.15733 (2021) - [i29]Sahidul Islam, Jieren Deng, Shanglin Zhou, Chen Pan, Caiwen Ding, Mimi Xie:
Enabling Super-Fast Deep Learning on Tiny Energy-Harvesting IoT Devices. CoRR abs/2111.14051 (2021) - 2020
- [c38]Xiaolong Ma, Geng Yuan, Sheng Lin, Caiwen Ding, Fuxun Yu, Tao Liu, Wujie Wen, Xiang Chen, Yanzhi Wang:
Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation. ASP-DAC 2020: 301-306 - [c37]Runbin Shi, Yuhao Ding, Xuechao Wei, He Li, Hang Liu, Hayden Kwok-Hay So, Caiwen Ding:
FTDL: A Tailored FPGA-Overlay for Deep Learning with High Scalability. DAC 2020: 1-6 - [c36]Bingbing Li, Zhenglun Kong, Tianyun Zhang, Ji Li, Zhengang Li, Hang Liu, Caiwen Ding:
Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning. EMNLP (Findings) 2020: 3187-3199 - [c35]Runbin Shi, Yuhao Ding, Xuechao Wei, Hang Liu, Hayden Kwok-Hay So, Caiwen Ding:
FTDL: An FPGA-tailored Architecture for Deep Learning Systems. FPGA 2020: 320 - [c34]Yifan Gong, Zheng Zhan, Zhengang Li, Wei Niu, Xiaolong Ma, Wenhao Wang, Bin Ren, Caiwen Ding, Xue Lin, Xiaolin Xu, Yanzhi Wang:
A Privacy-Preserving-Oriented DNN Pruning and Mobile Acceleration Framework. ACM Great Lakes Symposium on VLSI 2020: 119-124 - [c33]Kaidi Xu, Sijia Liu, Pin-Yu Chen, Mengshu Sun, Caiwen Ding, Bhavya Kailkhura, Xue Lin:
Towards an Efficient and General Framework of Robust Training for Graph Neural Networks. ICASSP 2020: 8479-8483 - [c32]Bingbing Li, Santosh Pandey, Haowen Fang, Yanjun Lyv, Ji Li, Jieyang Chen, Mimi Xie, Lipeng Wan, Hang Liu, Caiwen Ding:
FTRANS: energy-efficient acceleration of transformers using FPGA. ISLPED 2020: 175-180 - [c31]Shanglin Zhou, Bingbing Li, Caiwu Ding, Lu Lu, Caiwen Ding:
An Efficient Deep Reinforcement Learning Framework for UAVs. ISQED 2020: 323-328 - [c30]Geng Yuan, Xiaolong Ma, Sheng Lin, Zhengang Li, Jieren Deng, Caiwen Ding:
A DNN Compression Framework for SOT-MRAM-based Processing-In-Memory Engine. SoCC 2020: 37-42 - [i28]Kaidi Xu, Sijia Liu, Pin-Yu Chen, Mengshu Sun, Caiwen Ding, Bhavya Kailkhura, Xue Lin:
Towards an Efficient and General Framework of Robust Training for Graph Neural Networks. CoRR abs/2002.10947 (2020) - [i27]Tianyun Zhang, Xiaolong Ma, Zheng Zhan, Shanglin Zhou, Minghai Qin, Fei Sun, Yen-Kuang Chen, Caiwen Ding, Makan Fardad, Yanzhi Wang:
A Unified DNN Weight Compression Framework Using Reweighted Optimization Methods. CoRR abs/2004.05531 (2020) - [i26]Bingbing Li, Santosh Pandey, Haowen Fang, Yanjun Lyv, Ji Li, Jieyang Chen, Mimi Xie, Lipeng Wan, Hang Liu, Caiwen Ding:
FTRANS: Energy-Efficient Acceleration of Transformers using FPGA. CoRR abs/2007.08563 (2020) - [i25]Yijue Wang, Chenghong Wang, Zigeng Wang, Shanglin Zhou, Hang Liu, Jinbo Bi, Caiwen Ding, Sanguthevar Rajasekaran:
MCMIA: Model Compression Against Membership Inference Attack in Deep Neural Networks. CoRR abs/2008.13578 (2020) - [i24]Sheng Lin, Chenghong Wang, Hongjia Li, Jieren Deng, Yanzhi Wang, Caiwen Ding:
ESMFL: Efficient and Secure Models for Federated Learning. CoRR abs/2009.01867 (2020) - [i23]Yijue Wang, Jieren Deng, Dan Guo, Chenghong Wang, Xianrui Meng, Hang Liu, Caiwen Ding, Sanguthevar Rajasekaran:
SAPAG: A Self-Adaptive Privacy Attack From Gradients. CoRR abs/2009.06228 (2020) - [i22]Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang:
Achieving Real-Time Execution of Transformer-based Large-scale Models on Mobile with Compiler-aware Neural Architecture Optimization. CoRR abs/2009.06823 (2020) - [i21]Bingbing Li, Zhenglun Kong, Tianyun Zhang, Ji Li, Zhengang Li, Hang Liu, Caiwen Ding:
Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning. CoRR abs/2009.08065 (2020) - [i20]Deniz Gurevin, Shanglin Zhou, Lynn Pepin, Bingbing Li, Mikhail A. Bragin, Caiwen Ding, Fei Miao:
A Surrogate Lagrangian Relaxation-based Model Compression for Deep Neural Networks. CoRR abs/2012.10079 (2020)
2010 – 2019
- 2019
- [j5]Ji Li, Zihao Yuan, Zhe Li, Ao Ren, Caiwen Ding, Jeffrey Draper, Shahin Nazarian, Qinru Qiu, Bo Yuan, Yanzhi Wang:
Normalization and dropout for stochastic computing-based deep convolutional neural networks. Integr. 65: 395-403 (2019) - [j4]Zhe Li, Ji Li, Ao Ren, Ruizhe Cai, Caiwen Ding, Xuehai Qian, Jeffrey Draper, Bo Yuan, Jian Tang, Qinru Qiu, Yanzhi Wang:
HEIF: Highly Efficient Stochastic Computing-Based Inference Framework for Deep Neural Networks. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 38(8): 1543-1556 (2019) - [c29]Caiwen Ding, Shuo Wang, Ning Liu, Kaidi Xu, Yanzhi Wang, Yun Liang:
REQ-YOLO: A Resource-Aware, Efficient Quantization Framework for Object Detection on FPGAs. FPGA 2019: 33-42 - [c28]Ruizhe Cai, Olivia Chen, Ao Ren, Ning Liu, Caiwen Ding, Nobuyuki Yoshikawa, Yanzhi Wang:
A Majority Logic Synthesis Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits. ACM Great Lakes Symposium on VLSI 2019: 189-194 - [c27]Zhe Li, Caiwen Ding, Siyue Wang, Wujie Wen, Youwei Zhuo, Chang Liu, Qinru Qiu, Wenyao Xu, Xue Lin, Xuehai Qian, Yanzhi Wang:
E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs. HPCA 2019: 69-80 - [c26]Ruizhe Cai, Ao Ren, Olivia Chen, Ning Liu, Caiwen Ding, Xuehai Qian, Jie Han, Wenhui Luo, Nobuyuki Yoshikawa, Yanzhi Wang:
A stochastic-computing based deep learning framework using adiabatic quantum-flux-parametron superconducting technology. ISCA 2019: 567-578 - [c25]Geng Yuan, Xiaolong Ma, Caiwen Ding, Sheng Lin, Tianyun Zhang, Zeinab S. Jalali, Yilong Zhao, Li Jiang, Sucheta Soundarajan, Yanzhi Wang:
An Ultra-Efficient Memristor-Based DNN Framework with Structured Weight Pruning and Quantization Using ADMM. ISLPED 2019: 1-6 - [c24]Hongjia Li, Sheng Lin, Ning Liu, Caiwen Ding, Yanzhi Wang:
Deep Compressed Pneumonia Detection for Low-Power Embedded Devices. LABELS/HAL-MICCAI/CuRIOUS@MICCAI 2019: 89-97 - [i19]Ruizhe Cai, Ao Ren, Olivia Chen, Ning Liu, Caiwen Ding, Xuehai Qian, Jie Han, Wenhui Luo, Nobuyuki Yoshikawa, Yanzhi Wang:
A Stochastic-Computing based Deep Learning Framework using Adiabatic Quantum-Flux-Parametron SuperconductingTechnology. CoRR abs/1907.09077 (2019) - [i18]Xiaolong Ma, Geng Yuan, Sheng Lin, Caiwen Ding, Fuxun Yu, Tao Liu, Wujie Wen, Xiang Chen, Yanzhi Wang:
Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation. CoRR abs/1908.10017 (2019) - [i17]Geng Yuan, Xiaolong Ma, Caiwen Ding, Sheng Lin, Tianyun Zhang, Zeinab S. Jalali, Yilong Zhao, Li Jiang, Sucheta Soundarajan, Yanzhi Wang:
An Ultra-Efficient Memristor-Based DNN Framework with Structured Weight Pruning and Quantization Using ADMM. CoRR abs/1908.11691 (2019) - [i16]Caiwen Ding, Shuo Wang, Ning Liu, Kaidi Xu, Yanzhi Wang, Yun Liang:
REQ-YOLO: A Resource-Aware, Efficient Quantization Framework for Object Detection on FPGAs. CoRR abs/1909.13396 (2019) - [i15]Hongjia Li, Sheng Lin, Ning Liu, Caiwen Ding, Yanzhi Wang:
Deep Compressed Pneumonia Detection for Low-Power Embedded Devices. CoRR abs/1911.02007 (2019) - [i14]Geng Yuan, Xiaolong Ma, Sheng Lin, Zhengang Li, Caiwen Ding:
A SOT-MRAM-based Processing-In-Memory Engine for Highly Compressed DNN Implementation. CoRR abs/1912.05416 (2019) - 2018
- [j3]Caiwen Ding, Hongjia Li, Weiwei Zheng, Yanzhi Wang, Xue Lin:
Reconfigurable Photovoltaic Systems for Electric Vehicles. IEEE Des. Test 35(6): 37-43 (2018) - [j2]Jaemin Kim, Donkyu Baek, Caiwen Ding, Sheng Lin, Donghwa Shin, Xue Lin, Yanzhi Wang, Youngjin Cho, Sang Hyun Park, Naehyuck Chang:
Dynamic Reconfiguration of Thermoelectric Generators for Vehicle Radiators Energy Harvesting Under Location-Dependent Temperature Variations. IEEE Trans. Very Large Scale Integr. Syst. 26(7): 1241-1253 (2018) - [c23]Yanzhi Wang, Caiwen Ding, Zhe Li, Geng Yuan, Siyu Liao, Xiaolong Ma, Bo Yuan, Xuehai Qian, Jian Tang, Qinru Qiu, Xue Lin:
Towards Ultra-High Performance and Energy Efficiency of Deep Learning Systems: An Algorithm-Hardware Co-Optimization Framework. AAAI 2018: 4235-4243 - [c22]Ruizhe Cai, Ao Ren, Ning Liu, Caiwen Ding, Luhao Wang, Xuehai Qian, Massoud Pedram, Yanzhi Wang:
VIBNN: Hardware Acceleration of Bayesian Neural Networks. ASPLOS 2018: 476-488 - [c21]Hanchen Yang, Feiyang Kang, Caiwen Ding, Ji Li, Jaemin Kim, Donkyu Baek, Shahin Nazarian, Xue Lin, Paul Bogdan, Naehyuck Chang:
Prediction-based fast thermoelectric generator reconfiguration for energy harvesting from vehicle radiators. DATE 2018: 877-880 - [c20]Sheng Lin, Ning Liu, Mahdi Nazemi, Hongjia Li, Caiwen Ding, Yanzhi Wang, Massoud Pedram:
FFT-based deep learning deployment in embedded systems. DATE 2018: 1045-1050 - [c19]Shuo Wang, Zhe Li, Caiwen Ding, Bo Yuan, Qinru Qiu, Yanzhi Wang, Yun Liang:
C-LSTM: Enabling Efficient LSTM using Structured Compression Techniques on FPGAs. FPGA 2018: 11-20 - [c18]Caiwen Ding, Ao Ren, Geng Yuan, Xiaolong Ma, Jiayu Li, Ning Liu, Bo Yuan, Yanzhi Wang:
Structured Weight Matrices-Based Hardware Accelerators in Deep Neural Networks: FPGAs and ASICs. ACM Great Lakes Symposium on VLSI 2018: 353-358 - [c17]Zhe Li, Shuo Wang, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Yun Liang:
Efficient Recurrent Neural Networks using Structured Matrices in FPGAs. ICLR (Workshop) 2018 - [c16]Ziyi Zhao, Krittaphat Pugdeethosapol, Sheng Lin, Zhe Li, Caiwen Ding, Yanzhi Wang, Qinru Qiu:
Learning Topics Using Semantic Locality. ICPR 2018: 3710-3715 - [c15]Zhe Li, Ji Li, Ao Ren, Caiwen Ding, Jeffrey Draper, Qinru Qiu, Bo Yuan, Yanzhi Wang:
Towards Budget-Driven Hardware Optimization for Deep Convolutional Neural Networks Using Stochastic Computing. ISVLSI 2018: 28-33 - [c14]Chenghong Wang, Zeinab S. Jalali, Caiwen Ding, Yanzhi Wang, Sucheta Soundarajan:
A Fast and Effective Memristor-Based Method for Finding Approximate Eigenvalues and Eigenvectors of Non-negative Matrices. ISVLSI 2018: 563-568 - [i13]Ruizhe Cai, Ao Ren, Ning Liu, Caiwen Ding, Luhao Wang, Xuehai Qian, Massoud Pedram, Yanzhi Wang:
VIBNN: Hardware Acceleration of Bayesian Neural Networks. CoRR abs/1802.00822 (2018) - [i12]Yanzhi Wang, Caiwen Ding, Zhe Li, Geng Yuan, Siyu Liao, Xiaolong Ma, Bo Yuan, Xuehai Qian, Jian Tang, Qinru Qiu, Xue Lin:
Towards Ultra-High Performance and Energy Efficiency of Deep Learning Systems: An Algorithm-Hardware Co-Optimization Framework. CoRR abs/1802.06402 (2018) - [i11]Shuo Wang, Zhe Li, Caiwen Ding, Bo Yuan, Yanzhi Wang, Qinru Qiu, Yun Liang:
C-LSTM: Enabling Efficient LSTM using Structured Compression Techniques on FPGAs. CoRR abs/1803.06305 (2018) - [i10]Zhe Li, Shuo Wang, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Yun Liang:
Efficient Recurrent Neural Networks using Structured Matrices in FPGAs. CoRR abs/1803.07661 (2018) - [i9]Hanchen Yang, Feiyang Kang, Caiwen Ding, Ji Li, Jaemin Kim, Donkyu Baek, Shahin Nazarian, Xue Lin, Paul Bogdan, Naehyuck Chang:
Prediction-Based Fast Thermoelectric Generator Reconfiguration for Energy Harvesting from Vehicle Radiators. CoRR abs/1804.01574 (2018) - [i8]Ziyi Zhao, Krittaphat Pugdeethosapol, Sheng Lin, Zhe Li, Caiwen Ding, Yanzhi Wang, Qinru Qiu:
Learning Topics using Semantic Locality. CoRR abs/1804.04205 (2018) - [i7]Caiwen Ding, Ao Ren, Geng Yuan, Xiaolong Ma, Jiayu Li, Ning Liu, Bo Yuan, Yanzhi Wang:
Structured Weight Matrices-Based Hardware Accelerators in Deep Neural Networks: FPGAs and ASICs. CoRR abs/1804.11239 (2018) - [i6]Zhe Li, Ji Li, Ao Ren, Caiwen Ding, Jeffrey Draper, Qinru Qiu, Bo Yuan, Yanzhi Wang:
Towards Budget-Driven Hardware Optimization for Deep Convolutional Neural Networks using Stochastic Computing. CoRR abs/1805.04142 (2018) - [i5]Zhe Li, Caiwen Ding, Siyue Wang, Wujie Wen, Youwei Zhuo, Chang Liu, Qinru Qiu, Wenyao Xu, Xue Lin, Xuehai Qian, Yanzhi Wang:
E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs. CoRR abs/1812.07106 (2018) - 2017
- [j1]Caiwen Ding, Ning Liu, Yanzhi Wang, Ji Li, Soroush Heidari, Jingtong Hu, Yongpan Liu:
Multisource Indoor Energy Harvesting for Nonvolatile Processors. IEEE Des. Test 34(3): 42-49 (2017) - [c13]Ji Li, Ao Ren, Zhe Li, Caiwen Ding, Bo Yuan, Qinru Qiu, Yanzhi Wang:
Towards acceleration of deep convolutional neural networks using stochastic computing. ASP-DAC 2017: 115-120 - [c12]Caiwen Ding, Ji Li, Weiwei Zheng, Naehyuck Chang, Xue Lin, Yanzhi Wang:
Algorithm accelerations for luminescent solar concentrator-enhanced reconfigurable onboard photovoltaic system. ASP-DAC 2017: 318-323 - [c11]Ao Ren, Zhe Li, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Ji Li, Xuehai Qian, Bo Yuan:
SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing. ASPLOS 2017: 405-418 - [c10]Zihao Yuan, Ji Li, Zhe Li, Caiwen Ding, Ao Ren, Bo Yuan, Qinru Qiu, Jeffrey Draper, Yanzhi Wang:
Softmax Regression Design for Stochastic Computing Based Deep Convolutional Neural Networks. ACM Great Lakes Symposium on VLSI 2017: 467-470 - [c9]Ji Li, Zihao Yuan, Zhe Li, Caiwen Ding, Ao Ren, Qinru Qiu, Jeffrey Draper, Yanzhi Wang:
Hardware-driven nonlinear activation for stochastic computing based deep convolutional neural networks. IJCNN 2017: 1230-1236 - [c8]Donkyu Baek, Caiwen Ding, Sheng Lin, Donghwa Shin, Jaemin Kim, Xue Lin, Yanzhi Wang, Naehyuck Chang:
Reconfigurable thermoelectric generators for vehicle radiators energy harvesting. ISLPED 2017: 1-6 - [c7]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:
CirCNN: accelerating and compressing deep neural networks using block-circulant weight matrices. MICRO 2017: 395-408 - [c6]Geng Yuan, Caiwen Ding, Ruizhe Cai, Xiaolong Ma, Ziyi Zhao, Ao Ren, Bo Yuan, Yanzhi Wang:
Memristor crossbar-based ultra-efficient next-generation baseband processors. MWSCAS 2017: 1121-1124 - [i4]Ji Li, Zihao Yuan, Zhe Li, Caiwen Ding, Ao Ren, Qinru Qiu, Jeffrey T. Draper, Yanzhi Wang:
Hardware-Driven Nonlinear Activation for Stochastic Computing Based Deep Convolutional Neural Networks. CoRR abs/1703.04135 (2017) - [i3]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:
CirCNN: Accelerating and Compressing Deep Neural Networks Using Block-CirculantWeight Matrices. CoRR abs/1708.08917 (2017) - [i2]Sheng Lin, Ning Liu, Mahdi Nazemi, Hongjia Li, Caiwen Ding, Yanzhi Wang, Massoud Pedram:
FFT-Based Deep Learning Deployment in Embedded Systems. CoRR abs/1712.04910 (2017) - 2016
- [c5]Ning Liu, Caiwen Ding, Yanzhi Wang, Jingtong Hu:
Neural Network-based Prediction Algorithms for In-Door Multi-Source Energy Harvesting System for Non-Volatile Processors. ACM Great Lakes Symposium on VLSI 2016: 275-280 - [c4]Caiwen Ding, Hongjia Li, Weiwei Zheng, Yanzhi Wang, Naehyuck Chang, Xue Lin:
Luminescent solar concentrator-based photovoltaic reconfiguration for hybrid and plug-in electric vehicles. ICCD 2016: 281-288 - [c3]Caiwen Ding, Hongjia Li, Jingtong Hu, Yongpan Liu, Yanzhi Wang:
Dynamic converter reconfiguration for near-threshold non-volatile processors using in-door energy harvesting. ICCD 2016: 289-295 - [c2]Caiwen Ding, Soroush Heidari, Yanzhi Wang, Yongpan Liu, Jingtong Hu:
Multi-source in-door energy harvesting for non-volatile processors. ISCAS 2016: 173-176 - [i1]Ao Ren, Ji Li, Zhe Li, Caiwen Ding, Xuehai Qian, Qinru Qiu, Bo Yuan, Yanzhi Wang:
SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing. CoRR abs/1611.05939 (2016) - 2015
- [c1]Soroush Heidari, Caiwen Ding, Yongpan Liu, Yanzhi Wang, Jingtong Hu:
Multi-source energy harvesting management and optimization for non-volatile processors. IGSC 2015: 1-2
Coauthor Index
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