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

Feb 12, 2021
Yuhong Song, Weiwen Jiang, Bingbing Li, Panjie Qi, Qingfeng Zhuge, Edwin Hsing-Mean Sha, Sakyasingha Dasgupta, Yiyu Shi, Caiwen Ding

* 7 pages, 5 figures 

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

Dec 18, 2020
Deniz Gurevin, Shanglin Zhou, Lynn Pepin, Bingbing Li, Mikhail Bragin, Caiwen Ding, Fei Miao


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

Oct 08, 2020
Bingbing Li, Zhenglun Kong, Tianyun Zhang, Ji Li, Zhengang Li, Hang Liu, Caiwen Ding

* Accepted to Findings of EMNLP 2020 

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

Sep 15, 2020
Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang


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SAPAG: A Self-Adaptive Privacy Attack From Gradients

Sep 14, 2020
Yijue Wang, Jieren Deng, Dan Guo, Chenghong Wang, Xianrui Meng, Hang Liu, Caiwen Ding, Sanguthevar Rajasekaran


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ESMFL: Efficient and Secure Models for Federated Learning

Sep 03, 2020
Sheng Lin, Chenghong Wang, Hongjia Li, Jieren Deng, Yanzhi Wang, Caiwen Ding

* 7 pages, 3 figures 

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

Aug 28, 2020
Yijue Wang, Chenghong Wang, Zigeng Wang, Shanglin Zhou, Hang Liu, Jinbo Bi, Caiwen Ding, Sanguthevar Rajasekaran

* Machine Learning (cs.LG); Cryptography and Security (cs.CR); Machine Learning (stat.ML) 

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FTRANS: Energy-Efficient Acceleration of Transformers using FPGA

Jul 16, 2020
Bingbing Li, Santosh Pandey, Haowen Fang, Yanjun Lyv, Ji Li, Jieyang Chen, Mimi Xie, Lipeng Wan, Hang Liu, Caiwen Ding

* 7 pages, 7 figures 

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A Unified DNN Weight Compression Framework Using Reweighted Optimization Methods

Apr 12, 2020
Tianyun Zhang, Xiaolong Ma, Zheng Zhan, Shanglin Zhou, Minghai Qin, Fei Sun, Yen-Kuang Chen, Caiwen Ding, Makan Fardad, Yanzhi Wang


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

Feb 25, 2020
Kaidi Xu, Sijia Liu, Pin-Yu Chen, Mengshu Sun, Caiwen Ding, Bhavya Kailkhura, Xue Lin

* Accepted by ICASSP 2020 

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

Nov 24, 2019
Geng Yuan, Xiaolong Ma, Sheng Lin, Zhengang Li, Caiwen Ding


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Deep Compressed Pneumonia Detection for Low-Power Embedded Devices

Nov 04, 2019
Hongjia Li, Sheng Lin, Ning Liu, Caiwen Ding, Yanzhi Wang


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

Sep 29, 2019
Caiwen Ding, Shuo Wang, Ning Liu, Kaidi Xu, Yanzhi Wang, Yun Liang


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

Aug 29, 2019
Geng Yuan, Xiaolong Ma, Caiwen Ding, Sheng Lin, Tianyun Zhang, Zeinab S. Jalali, Yilong Zhao, Li Jiang, Sucheta Soundarajan, Yanzhi Wang


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

Aug 27, 2019
Xiaolong Ma, Geng Yuan, Sheng Lin, Caiwen Ding, Fuxun Yu, Tao Liu, Wujie Wen, Xiang Chen, Yanzhi Wang


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

Jul 22, 2019
Ruizhe Cai, Ao Ren, Olivia Chen, Ning Liu, Caiwen Ding, Xuehai Qian, Jie Han, Wenhui Luo, Nobuyuki Yoshikawa, Yanzhi Wang


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

Dec 12, 2018
Zhe Li, Caiwen Ding, Siyue Wang, Wujie Wen, Youwei Zhuo, Chang Liu, Qinru Qiu, Wenyao Xu, Xue Lin, Xuehai Qian, Yanzhi Wang

* In The 25th International Symposium on High-Performance Computer Architecture (HPCA 2019) 

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

May 10, 2018
Zhe Li, Ji Li, Ao Ren, Caiwen Ding, Jeffrey Draper, Qinru Qiu, Bo Yuan, Yanzhi Wang

* Accepted by IEEE Computer Society Annual Symposium on VLSI 2018 

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Learning Topics using Semantic Locality

Apr 11, 2018
Ziyi Zhao, Krittaphat Pugdeethosapol, Sheng Lin, Zhe Li, Caiwen Ding, Yanzhi Wang, Qinru Qiu

* International Conference of Pattern Recognition (ICPR) in 2018 

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

Mar 28, 2018
Caiwen Ding, Ao Ren, Geng Yuan, Xiaolong Ma, Jiayu Li, Ning Liu, Bo Yuan, Yanzhi Wang

* 6 pages, 7 figures, GLSVLSI2018 

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Efficient Recurrent Neural Networks using Structured Matrices in FPGAs

Mar 22, 2018
Zhe Li, Shuo Wang, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Yun Liang

* To appear in International Conference on Learning Representations 2018 Workshop Track 

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

Mar 14, 2018
Shuo Wang, Zhe Li, Caiwen Ding, Bo Yuan, Yanzhi Wang, Qinru Qiu, Yun Liang

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

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

Feb 18, 2018
Yanzhi Wang, Caiwen Ding, Zhe Li, Geng Yuan, Siyu Liao, Xiaolong Ma, Bo Yuan, Xuehai Qian, Jian Tang, Qinru Qiu, Xue Lin

* 6 figures, AAAI Conference on Artificial Intelligence, 2018 

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VIBNN: Hardware Acceleration of Bayesian Neural Networks

Feb 02, 2018
Ruizhe Cai, Ao Ren, Ning Liu, Caiwen Ding, Luhao Wang, Xuehai Qian, Massoud Pedram, Yanzhi Wang


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FFT-Based Deep Learning Deployment in Embedded Systems

Dec 13, 2017
Sheng Lin, Ning Liu, Mahdi Nazemi, Hongjia Li, Caiwen Ding, Yanzhi Wang, Massoud Pedram

* Design, Automation, and Test in Europe (DATE) For source code, please contact Mahdi Nazemi at  

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

Aug 29, 2017
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

* 14 pages, 15 Figures, conference 

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Hardware-Driven Nonlinear Activation for Stochastic Computing Based Deep Convolutional Neural Networks

Mar 12, 2017
Ji Li, Zihao Yuan, Zhe Li, Caiwen Ding, Ao Ren, Qinru Qiu, Jeffrey Draper, Yanzhi Wang

* This paper is accepted by 2017 International Joint Conference on Neural Networks (IJCNN) 

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

Jan 31, 2017
Ao Ren, Ji Li, Zhe Li, Caiwen Ding, Xuehai Qian, Qinru Qiu, Bo Yuan, Yanzhi Wang

* This paper is accepted by 22nd ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2017 

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