Publications

Journals

  1. [21’CADJ] Jiangce Chen, Horea T. Ilies, Caiwen Ding (2021). Graph-Based Shape Analysis for Heterogeneous Geometric Datasets: Similarity, Retrieval and Substructure Matching, Computer Aided Design.
  2. [21’TCCPS-LETTER] Caiwu Ding, Hongwu Peng, Lu Lu, and Caiwen Ding,  Aerial  Manipulation  Using  a Novel Unmanned AerialVehicle Cyber-Physical System, IEEE Technical Committee on Cyber-Physical Systems letter (TCCPSletter),
  3. [21’TPDS] Santosh Pandey, Zhibin Wang, Sheng Zhong, Chen Tian, Bolong Zheng, Xiaoye Li, Lingda Li, Adolfy Hoisie, Caiwen Ding, Dong Li, Hang Liu. TRUST: Triangle Counting Reloaded on GPUs. IEEE Transactions on Parallel and Distributed Systems. IEEE Transactions on Parallel and Distributed Systems (TPDS) (2021).
  4. [21’IEEE RA-L] Caiwu Ding, Lu Lu, Cong Wang, Caiwen Ding. Design, Sensing, and Control of a Novel UAV Platform for AerialDrilling and In Robotics and Automation Letters (RA-L) (2021).
  5. [19’INTEGRATION] Ji Li, Zihao Yuan, Zhe Li, Ao Ren, Caiwen Ding, Jeffrey Draper, Shahin Nazarian, Qinru Qiu, Bo Yuan, and Yanzhi Wang. Normalization and dropout for stochastic computing-based deep convolutional neural In Integration, theVLSI Journal, 2019.
  6. [18’TVLSI] Jaemin Kim, Donkyu Baek, Caiwen Ding, Sheng Lin, Donghwa Shin, Xue Lin, et al. Dynamic reconfiguration of thermoelectric generators for vehicle radiators energy harvesting under location-dependent temperature In IEEETransactions on Very Large Scale Integration (VLSI) Systems (TVLSI).
  7. [18’TCAD] Zhe Li, Ji Li, Ao Ren, Ruizhe Cai, Caiwen Ding, Xuehai Qian, Jeffrey Draper, Bo Yuan,  Jian Tang,  Qinru Qiu,  et al.   HEIF: Highly Efficient Stochastic Computing based Inference Framework for Deep Neural In IEEE Transactions onComputer Aided Design of Integrated Circuits & Systems (TCAD).
  8. [18’D&T] Caiwen Ding, Hongjia Li, Weiwei Zheng, Xue Lin, and Yanzhi Wang. Reconfigurable Photovoltaic Systems for Electric In IEEE Design & Test, 2018, IEEE.
  9. [17’D&T] Caiwen Ding, Ning Liu, Yanzhi Wang, Ji Li, Soroush Heidari, Jingtong Hu, and Yongpan Liu. Multisource indoor energyharvesting for nonvolatile In IEEE Design & Test, 34(3):42–49, 2017.
  10. [16’IJERI] Yuqiu You and Caiwen Ding. Design and analysis of a labview and arduino-based automatic solar tracking International Journal of Engineering Research & Innovation, page 31, 2016.
  11. [16’TIIJ] Caiwen Ding and Yuqiu You. A temperature alarming system based on an hcs12 microcontroller. in TechnologyInterface International Journal, page 35, 2016.
  12. [16’TCCPS-LETTER] Yanzhi Wang, Caiwen Ding, Luminescent Solar Concentrator-Based Reconfigurable Photovoltaic System for EV/HEV, IEEE Technical Committee on Cyber-Physical Systems letter (TCCPS- letter), 2016.

Conferences (* equal contribution)

  1. [21’EMNLP] Jieren Deng*, Yijue Wang*, Ji Li, Chenghong Wang, Chao Shang, Hang Liu, Sanguthevar Rajasekaran and Caiwen Ding, TAG: Transformer Attack from Gradient, In Findings of ACL Empirical Methods in Natural Language Processing (EMNLP), 2021.
  2. [21’EMNLP] Jieren Deng*, Chenghong Wang*, Xianrui Meng, Yijue Wang, Ji Li, Sheng Lin, Shuo Han, Fei Miao, Sanguthevar Rajasekaran and Caiwen Ding, A Secure and Efficient Federated Learning Framework for NLP, In Proceedings of ACL Empirical Methods in Natural Language Processing (EMNLP), 2021. (Oral)
  3. [21’SC] Shiyang Chen*, Shaoyi Huang*, Santosh Pandey, Bingbing Li, Guang Gao, Long Zheng, Caiwen Ding, Hang Liu, E.T.: Re-Thinking Self-Attention for Transformer Models on GPUs, In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC), 2021.
  4. [21’SC] 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 Computation on GPUs, In Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis (SC), 2021.
  5. [21’ICCAD] Daniel Manu, Yi Sheng, Junhuan Yang, Jieren Deng, Tong Geng, Ang Li, Caiwen Ding, Weiwen Jiang, Lei Yang,  BFL-DISCO: Federated Generative Adversarial Network for Graph-based Molecule Drug Discovery, 2021 the 40th International Conference On Computer Aided Design (ICCAD), to appear
  6. [21’ICCAD] Hongwu Peng, Shiyang Chen, Zhepeng Wang, Junhuan Yang, Scott Weitze, Tong Geng, Ang Li, Jinbo Bi, Minghu Song, Weiwen Jiang, Hang Liu, and Caiwen DingOptimizing FPGA-based Accelerator Design for Large-Scale Molecular Similarity Search, 2021 the 40th International Conference On Computer-Aided Design (ICCAD), to appear
  7. [21’ICCAD] Zhepeng Wang, Zhiding Liang, Shanglin Zhou, Caiwen Ding, Jinjun Xiong, Yiyu Shi, WeiwenJiang, Exploration of Quantum Neural Architecture by Mixing Quantum Neuron Designs, 2021 the 40th Inter-national Conference On Computer-Aided Design (ICCAD), to appear
  8. [21’ASAP] Hongwu Peng, Shanglin Zhou, Scott Weitze, Jiaxin Li, Sahidul Islam, Wei Zhang, Minghu Song, Mimi Xie, Hang Liu, and Caiwen Ding,  Binary Complex Neural Network Acceleration on FPGA, IEEE 31st International Conference on Application-specific Systems, Architectures and Processors (ASAP), 2021
  9. [21’IJCAI] Deniz Gurevin*, Mikhail Bragin*, Caiwen Ding*, Shanglin  Zhou,  Lynn  Pepin,  Bingbing  Li,  Fei Miao, Enabling Retrain-free Deep Neural Network Pruning using Surrogate Lagrangian Relaxation. In Proceedings of the 30th International Joint Conference on Artificial  Intelligence (IJCAI), 2021.  Acceptance  rate:  13.9% (587/4204)
  10. [21’IJCAI] 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. In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI), 2021. Acceptance rate: 13.9% (587/4204)
  11. [21’IJCAI] 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”, in Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI), 2021. (Demonstration Track)
  12. [21’GLSVLSI] Shaoyi Huang, Shiyang Chen, Hongwu Peng, Daniel Manu, Zhenglun Kong, Geng Yuan, Lei Yang, Shusen Wang, Hang Liu, and Caiwen Ding, HMC-TRAN: A Tensor-core Inspired Hierarchical Model Compression for Transformer-based DNNs on GPU. In Proceedings of the 30th ACM Great Lakes Symposium on VLSI (GLSVLSI), 2021.
  13. [21’GLSVLSI] Daniel Manu, Shaoyi Huang, Caiwen  Ding,  Lei Yang,  Co-Exploration of Graph Neural Network and Network-on-Chip Design using AutoML. In Proceedings of the 30th ACM Great Lakes Symposium on VLSI (GLSVLSI), 2021.
  14. [21’TranSET] Eugenia Cadete, Caiwen Ding, Mimi  Xie,  Sara  Ahmed  and  Yu-Fang  Jin,  Prediction  of  Elec- tric Vehicles Charging Load Using Long Short-Term Memory Model. In Proceedings of the Transportation Consortium of South-Central States (TranSET),
  15. [21’ISCA] Geng Yuan*, Payman Behnam*, Ali Shafiee, Zhengang Li, Xiaolong Ma, Hang Liu, Xuehai Qian, Mahdi Bojnordi, Yanzhi Wang, Caiwen  Ding,  FORMS:  Fine-grained  Polarized  ReRAM-based  In-situ  Computation for Mixed-signal DNN Accelerator, In Proceedings of the 46th International Symposium on Computer Architecture (ISCA), 2021.
  16. [21’DAC] 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, In Proceedings of ACM/EDAC/IEEE Design Automation Conference (DAC), (To appear).
  17. [21’DAC] Tianyun Zhang, Xiaolong Ma, Zheng Zhan, Shanglin Zhou, Caiwen Ding, Makan Fardad, Yanzhi Wang, A unified DNN weight compression framework using reweighted optimization methods, In Proceedings of ACM/EDAC/IEEE Design Automation Conference (DAC), 2021. (To appear).
  18. [21’ISQED] Hongwu Peng, Shaoyi Huang, Tong Geng, Ang Li, Weiwen Jiang, Hang Liu, Shusen Wang, and Caiwen Ding. Accelerating Transformer-based Deep Learning Models on FPGAs using Column Balanced Block In proceedings of IEEE International Society for Quality Electronic Design (ISQED), 2021.
  19. [21’ISQED] Shanglin Zhou, Mimi Xie, Yu-Fang Jin,  Fei Miao,  Caiwen Ding.  An End-to-end Multi-task Object Detection using Embedded GPU in Autonomous Driving. In proceedings of IEEE International Society for Quality Electronic Design (ISQED), 2021.
  20. [21’DATE] Geng Yuan*, Payman Behnam*, Yuxuan Cai, Ali Shafiee, Jingyan Fu, Zhiheng Liao, Zhengang Li, Xiaolong Ma, Jieren Deng, Jinhui Wang, Mahdi Bojnordi, Yanzhi Wang, Caiwen Ding, TinyADC: Peripheral Circuit-aware Weight Pruning Framework for Mixed-signal DNN Accelerators, In Proc. of Design Automation & Test in Europe Conference & Exhibition (DATE), 2021. (Best Paper Award Nomination)
  21. [20’EMNLP]Bingbing Li*, Zhenglun Kong*, Tianyun Zhang, Ji Li, Zhengang Li, Hang Liu, and Caiwen Ding, Efficient Transformer-based Large Scale Language Representations using Hardware-friendly Block Structured Pruning, In Findings of ACL Empirical Methods in Natural Language Processing (EMNLP), 2020.
  22. [20’SOCC] Geng Yuan, Xiaolong Ma, Sheng Lin, Zhengang Li, Jieren Deng, and Caiwen Ding, A DNN Compression Framework for SOT-MRAM-Based Processing-In-Memory Engine, In Proceedings of the 2020 IEEE 33rd International System-on-Chip Conference (SOCC), 2020.
  23. [20’GLSVLSI] Yifan Gong, Zheng Zhan, Zhengang Li, Wei Niu, Bin Ren, Xiaolong Ma, Xiaolin Xu, Caiwen Ding, and Xue Lin, A Privacy-Preserving-Oriented DNN Pruning and Mobile Acceleration Framework, In Proceedings of the 29th ACM Great Lakes Symposium on VLSI (GLSVLSI), 2020.
  24. [20’ISLPED] Bingbing Li, Santosh Pandey, Haowen Fang, Yanjun Lyv, Ji Li, Jieyang Chen, Mimi Xie, Lipeng Wan, Hang Liu and Caiwen Ding. FTRANS: Energy-Efficient Acceleration of Transformers using FPGA. In Proceedings of ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED),
  25. [20’ICASSP] 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. In proceeding of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020.
  26. [20’DAC] Runbin Shi, Yuhao Ding, Xuechao Wei, He Li, Hang Liu, Hayden So, Caiwen Ding. Ftdl: A tailored FPGA-overlay for deep learning with high scalability. In Proceedings of ACM/EDAC/IEEE Design Automation Conference (DAC), 2020. (full paper)
  27. [20’ISQED] Shanglin Zhou, Bingbing Li, Caiwu Ding, Lu Lu, Caiwen Ding. An Efficient Deep Reinforcement Learning Framework for UAVs. In IEEE International Society for Quality Electronic Design (ISQED), 2020.
  28. [20’ASP-DAC] 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”,  In  Proceedings of 25th Asia and South Pacific Design Automation Conference (ASP-DAC), 2020.
  29. [19’ISCA] Ruizhe Cai, Ao Ren, Olivia Chen, Ning Liu, Caiwen Ding, Xuehai Qian, Jie Han, Wenhui Luo, Yoshikawa Nobuyuki, Yanzhi Wang, A stochastic-computing based deep learning framework using adiabatic quantum-flux-parametron superconducting technology, In Proceedings of the 46th International Symposium on Computer Architecture (ISCA), 2019. (Acceptance Rate: 17%)
  30. [19’ISLPED] Geng Yuan*, Xiaolong Ma*, Caiwen Ding, Sheng Lin, Tianyun Zhang, Zeinab S. Jalali, Yilong Zhao, Li Jiang, Sucheta Soundarajan and Yanzhi Wang, An Ultra-Efficient Memristor-Based DNN Framework with Structured Pruning and Quantization Using ADMM, In Proceedings of ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED), 2019.
  31. [19’FPGA] Caiwen Ding*, Shuo Wang*, Ning Liu, Kaidi Xu, Yanzhi Wang and Yun Liang, REQ-YOLO: A Resource-Aware, Efficient Quantization Framework for Object Detection on FPGAs, In Proceedings of the ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA), 2019 (Full paper)
  32. [19’GLSVLSI] Ruizhe Cai, Olivia Chen, Ao Ren, Ning Liu, Caiwen Ding, Nobuyuki Yoshikawa and Yanzhi Wang, A Majority Logic Synthesis Framework for Adiabatic Quantum-Flux-Parametron Superconducting Circuits, In Proceedings of the 29th ACM Great Lakes Symposium on VLSI (GLSVLSI), 2019. (Full Paper Acceptance Rate: 29%)
  33. [19’HPCA] Zhe Li*, Caiwen Ding*, Siyue Wang, Wujie Wen, Youwei Zhuo, Chang Liu, Qinru Qiu, Wenyao Xu, Xue Lin, Yanzhi Wang. E-RNN: Design Optimization for Efficient Recurrent Neural Networks in FPGAs, In Proc. of IEEE International Symposium on High-Performance Computer Architecture (HPCA), 2019
  34. [18’FPGA] Shuo Wang*, Zhe Li*, Caiwen Ding*, Bo Yuan, Qinru Qiu, Yanzhi Wang, and Yun Liang. C-LSTM: Enabling Efficient LSTM using Structured Compression Techniques on FPGAs. In Proceedings of the ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA). ACM, 2018. (Full paper)
  35. [18’AAAI] Yanzhi Wang, Caiwen Ding, Gen Yuan, Siyu Liao, Zhe Li, Xiaolong Ma, Bo Yuan, Xuehai Qian, Jian Tang, Qinru Qiu, and Xue Lin. Towards ultra-high performance and energy efficiency of deep learning systems: an algorithm-hardware co-optimization framework. In Proc. of the 32nd AAAI Conference on Artificial Intelligence (AAAI), Feb. 2018.
  36. [18’ASPLOS] Ruizhe Cai, Ao Ren, Ning Liu, Caiwen Ding, Luhao Wang, Xuehai Qian, Massoud Pedram, Yanzhi Wang. VIBNN: Hardware Acceleration of Bayesian Neural Networks. In Proceedings of ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2018. (Acceptance Rate: 17.4%)
  37. [18’DATE] Sheng Lin, Ning Liu, Mahdi Nazemi, Hongjia Li, Caiwen Ding, Yanzhi Wang, and Massoud Pedram. FFT-Based Deep Learning Deployment in Embedded Systems. In Proc. of Design Automation & Testing Europe Conference & Exhibition (DATE), Mar. 2018.  (Best Paper Award Nomination)
  38. [18’DATE] Hanchen Yang, Feiyang Kang, Caiwen Ding, Ji Li, Jaemin Kim, et al. Prediction-Based Fast Thermoelectric Generator Reconfiguration for Energy Harvesting from Vehicle Radiators. In Proc. of Design Automation & Test in Europe Conference & Exhibition (DATE), Mar. 2018. (Acceptance Rate: 23%)
  39. [18’ICPR] Ziyi Zhao, Krittaphat Pugdeethosapol, Sheng Lin, Zhe Li, Caiwen Ding, Yanzhi Wang, Qinru Qiu. Learning Topics using Semantic Locality. In International Conference on Pattern Recognition (ICPR), Aug. 2018.
  40. [18’GLSVLSI] Caiwen Ding*, Ao Ren*, Geng Yuan, Xiaolong Ma, Jiayu Li, Ning Liu, et al. Structured Weight Matrices-Based Hardware Accelerators in Deep Neural Networks: FPGAs and ASICs. In Proceedings of the 28th edition of the ACM Great Lakes Symposium on VLSI (GLSVLSI). ACM, 2018.
  41. [18’ISVLSI] Zhe Li, Ji Li, Ao Ren, Caiwen Ding, Jeffrey Draper, Qinru Qiu, Bo Yuan, and Yanzhi Wang. Towards Budget-Driven Hardware Optimization for Deep Convolutional Neural Networks using Stochastic Computing. In IEEE Computer Society Annual Symposium on VLSI (ISVLSI), July. 2018.
  42. [18’ISVLSI] Chenghong Wang, Zeinab S. Jalali, Caiwen Ding, Yanzhi Wang and Sucheta Soundarajan. A Fast and Effective Memristor-Based Method for Finding Approximate Eigenvalues and Eigenvectors of Non-Negative Matrices. In IEEE Computer Society Annual Symposium on VLSI (ISVLSI), July. 2018.
  43. [17’MICRO] Caiwen Ding, Yanzhi Wang, Siyu Liao, Zhe Li, Yu Bai, et al., “CirCNN: accelerating and compressing deep neural networks using block-circulant weight matrices”, in IEEE/ACM International Symposium on Microarchitecture (MICRO), 2017. (Acceptance Rate: 18.6%)
  44. [17’ASPLOS] Ao Ren, Zhe Li, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Ji Li, Xuehai Qian, and Bo Yuan. 2017. SC-DCNN: Highly-Scalable Deep Convolutional Neural Network using Stochastic Computing. In Proceedings of the Twenty-Second International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS ’17). (acceptance rate: 17.4%)
  45. [17’ASP-DAC] Caiwen Ding, Ji Li, Weiwei Zheng, Naehyuck Chang, Xue Lin, and Yanzhi Wang, Algorithm accelerations for luminescent solar concentrator-enhanced reconfigurable onboard photovoltaic system, in Proc. of the 22nd Asia and South Pacific Design Automation Conference (ASP-DAC), Jan. 2017. (Acceptance Rate: 31%)
  46. [17’ASP-DAC] Ji Li, Ao Ren, Zhe Li, Caiwen Ding, Bo Yuan, Qinru Qiu, and Yanzhi Wang. Towards acceleration of deep convolutional neural networks using stochastic computing. In Proc. of Asia and South Pacific Design Automation Conference (ASP-DAC), pages 115–120. IEEE, 2017.
  47. [17’IJCNN] Ji Li, Zihao Yuan, Zhe Li, Caiwen Ding, Ao Ren, Qinru Qiu, Jeffrey Draper, and Yanzhi Wang. Hardware-driven nonlinear activation for stochastic computing based deep convolutional neural networks. In Proc. of the International Joint Conference on Neural Networks (IJCNN), 2017.
  48. [17’GLSVLSI] Zihao Yuan, Ji Li, Zhe Li, Caiwen Ding, Ao Ren, Bo Yuan, et al. Softmax regression design for stochastic computing based deep convolutional neural networks. In Proceedings of the on Great Lakes Symposium on VLSI 2017 (GLSVLSI), pages 467–470. ACM, 2017. (Acceptance Rate: 24.4%)
  49. [17’ISLPED] Donkyu Baek, Caiwen Ding, Sheng Lin, Donghwa Shin, Jaemin Kim, Xue Lin, Yanzhi Wang, and Naehyuck Chang. “Reconfigurable thermoelectric generators for vehicle radiators energy harvesting.” In 2017 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED), pp. 1-6. IEEE, 2017.
  50. [17’MWSCAS] Geng Yuan, Caiwen Ding, Ruizhe Cai, Xiaolong Ma, Ziyi Zhao, Ao Ren, Bo Yuan, and Yanzhi Wang. Memristor crossbar-based ultra-efficient next-generation baseband processors. In Proc. of International Midwest Symposium on Circuits and Systems (MWSCAS), IEEE.
  51. [16’ICCD] Caiwen Ding, Hongjia Li, Weiwei Zheng, Yanzhi Wang, Naehyuck Chang, and Xue Lin, “Luminescent solar concentrator-based photovoltaic reconfiguration for hybrid and plug-in electric vehicles,” in Proc. of the 34th IEEE International Conference on Computer Design (ICCD), Oct. 2016, pp. 281-288. (Acceptance rate 28.8%)
  52. [16’ICCD] Caiwen Ding, Li Hongjia, Jingtong Hu, Yongpan Liu, and Yanzhi Wang. “Dynamic converter reconfiguration for near-threshold non-volatile processors using in-door energy harvesting.” in Proc. of the 34th IEEE International Conference on Computer Design (ICCD), Oct. 2016, pp. 281-288. (Acceptance rate 28.8%)
  53. [16’GLSVLSI] Ning Liu*, Caiwen Ding*, Yanzhi Wang, and Jingtong Hu. Neural network-based prediction algorithms for in-door multi-source energy harvesting system for non-volatile processors. In Great Lakes Symposium on VLSI, 2016 International, pages 275–280. IEEE, 2016. (Acceptance Rate: 25%)
  54. [16’ISCAS] Caiwen Ding, Soroush Heidari, Yanzhi Wang, Yongpan Liu, and Jingtong Hu. Multi-source in-door energy harvesting for non-volatile processors. In International Symposium on Circuits and Systems (ISCAS). Page 173–176. IEEE, 2016.
  55. [15’IGSC] Soroush Heidari, Caiwen Ding, Yongpan Liu, Yanzhi Wang, and Jingtong Hu. Multi-source energy harvesting management and optimization for non-volatile processors. In Proc. of Sixth International Green Computing Conference and Sustainable Computing Conference (IGSC), pages 1–2. IEEE, 2015.

Workshop and Posters (* equal contribution)

  1. [20’NeurIPS workshop] Sheng Lin, Chenghong Wang, Hongjia Li, Jieren Deng, Yanzhi Wang, Caiwen Ding, ESMFL: Efficient and Secure Models for Federated Learning, In NeurIPS Workshop on Scalability, Privacy, and Security in Federated Learning, 2020.
  2. [20’FPGA] Runbin Shi, Yuhao Ding, Xuechao Wei, Hang Liu, So Hayden, Caiwen Ding. Ftdl: An FPGA-tailored architecture for deep learning applications. In Proceedings of the 2020 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays. ACM, 2020. (Poster)
  3. [20’BARC] Z. Zhan, Y. Gong, Z. Li, W. Niu, X. Ma, B. Ren, C. Ding, X. Lin and Y. Wang, A Privacy-Preserving-Oriented DNN Pruning and Mobile Acceleration Framework, Boston area ARChitecture Annual Workshop (BARC).
  4. [20’BARC] S. Zhou, B. Li, and C. Ding. Accelerating Transformers-based Large-Scale Language Representation using FPGA, Boston area ARChitecture Annual Workshop (BARC).
  5. [19’MICCAI Workshop] Hongjia Li, Sheng Lin, Ning Liu, Caiwen Ding, and Yanzhi Wang, Deep Compressed Pneumonia Detection for Low-Power Embedded Device. In the 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) Workshop, 2019.
  6. [18’ICLR WorkshopZhe Li, Shuo Wang, Caiwen Ding, Qinru Qiu, Yanzhi Wang, Yun Liang. EfficientRecurrent Neural Networks using Structured Matrices in FPGAs. International Conference on learning representations (ICLR) Workshop, 2018.