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2020 – today
- 2023
[i57]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)- [i56]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) - 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) - [c69]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 - [c68]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. Big Data 2022: 5823-5832 - [c67]Bingyu Liu, Rujia Wang, Zhongjie Ba, Shanglin Zhou, Caiwen Ding, Yuan Hong:
Poster: Cryptographic Inferences for Video Deep Neural Networks. CCS 2022: 3395-3397 - [c66]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 - [c65]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 - [c64]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 - [c63]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 - [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]