| CirCNN: accelerating and compressing deep neural networks using block-circulant weight matrices C Ding, S Liao, Y Wang, Z Li, N Liu, Y Zhuo, C Wang, X Qian, Y Bai, ... (MICRO) Proceedings of the 50th Annual IEEE/ACM International Symposium on …, 2017 | 152 | 2017 |
| Sc-dcnn: Highly-scalable deep convolutional neural network using stochastic computing A Ren, Z Li, C Ding, Q Qiu, Y Wang, J Li, X Qian, B Yuan (ASPLOS) 2017 Intl Conf on Architectural Support for Programming Languages …, 2017 | 120 | 2017 |
| C-lstm: Enabling efficient lstm using structured compression techniques on fpgas S Wang, Z Li, C Ding, B Yuan, Q Qiu, Y Wang, Y Liang (FPGA) Proceedings of the 2018 ACM/SIGDA International Symposium on Field …, 2018 | 98 | 2018 |
| Towards acceleration of deep convolutional neural networks using stochastic computing J Li, A Ren, Z Li, C Ding, B Yuan, Q Qiu, Y Wang (ASP-DAC) 2017 22nd Asia and South Pacific Design Automation Conference, 115-120, 2017 | 43 | 2017 |
| Hardware-driven nonlinear activation for stochastic computing based deep convolutional neural networks J Li, Z Yuan, Z Li, C Ding, A Ren, Q Qiu, J Draper, Y Wang (IJCNN) 2017 International Joint Conference on Neural Networks, 1230-1236, 2017 | 36 | 2017 |
| VIBNN: Hardware acceleration of Bayesian neural networks R Cai, A Ren, N Liu, C Ding, L Wang, X Qian, M Pedram, Y Wang (ASPLOS) Proceedings of the 23rd International Conference on Architectural …, 2018 | 32 | 2018 |
| E-RNN: Design optimization for efficient recurrent neural networks in FPGAs Z Li, C Ding, S Wang, W Wen, Y Zhuo, C Liu, Q Qiu, W Xu, X Lin, X Qian, ... (HPCA) 2019 IEEE International Symposium on High Performance Computer …, 2019 | 28 | 2019 |
| Multisource indoor energy harvesting for nonvolatile processors C Ding, N Liu, Y Wang, J Li, S Heidari, J Hu, Y Liu IEEE Design & Test 34 (3), 42-49, 2017 | 23 | 2017 |
| Multi-source in-door energy harvesting for non-volatile processors C Ding, S Heidari, Y Wang, Y Liu, J Hu (ISCAS) IEEE International Symposium on Circuits and Systems, 2016 | 23 | 2016 |
| Towards ultra-high performance and energy efficiency of deep learning systems: an algorithm-hardware co-optimization framework Y Wang, C Ding, Z Li, G Yuan, S Liao, X Ma, B Yuan, X Qian, J Tang, ... (AAAI) Thirty-Second AAAI Conference on Artificial Intelligence, 2018 | 21 | 2018 |
| REQ-YOLO: A Resource-Aware, Efficient Quantization Framework for Object Detection on FPGAs C Ding, S Wang, N Liu, K Xu, Y Wang, Y Liang (FPGA) Proceedings of the 2019 ACM/SIGDA International Symposium on Field …, 2019 | 20 | 2019 |
| HEIF: Highly efficient stochastic computing-based inference framework for deep neural networks Z Li, J Li, A Ren, R Cai, C Ding, X Qian, J Draper, B Yuan, J Tang, Q Qiu, ... (TCAD) IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2018 | 20 | 2018 |
| Fft-based deep learning deployment in embedded systems S Lin, N Liu, M Nazemi, H Li, C Ding, Y Wang, M Pedram (DATE) 2018 Design, Automation & Test in Europe Conference & Exhibition …, 2018 | 20 | 2018 |
| Normalization and dropout for stochastic computing-based deep convolutional neural networks J Li, Z Yuan, Z Li, A Ren, C Ding, J Draper, S Nazarian, Q Qiu, B Yuan, ... Integration 65, 395-403, 2019 | 16 | 2019 |
| Softmax regression design for stochastic computing based deep convolutional neural networks Z Yuan, J Li, Z Li, C Ding, A Ren, B Yuan, Q Qiu, J Draper, Y Wang Proceedings of the on Great Lakes Symposium on VLSI 2017, 467-470, 2017 | 16 | 2017 |
| Efficient recurrent neural networks using structured matrices in fpgas Z Li, S Wang, C Ding, Q Qiu, Y Wang, Y Liang ICLR workshop, 2018 | 13 | 2018 |
| Structured weight matrices-based hardware accelerators in deep neural networks: Fpgas and asics C Ding, A Ren, G Yuan, X Ma, J Li, N Liu, B Yuan, Y Wang Proceedings of the 2018 on Great Lakes Symposium on VLSI, 353-358, 2018 | 11 | 2018 |
| Tiny but Accurate: A Pruned, Quantized and Optimized Memristor Crossbar Framework for Ultra Efficient DNN Implementation X Ma, G Yuan, S Lin, C Ding, F Yu, T Liu, W Wen, X Chen, Y Wang 25th Asia and South Pacific Design Automation Conference (ASP-DAC), 2020 | 10 | 2020 |
| A stochastic-computing based deep learning framework using adiabatic quantum-flux-parametron superconducting technology R Cai, A Ren, O Chen, N Liu, C Ding, X Qian, J Han, W Luo, N Yoshikawa, ... (ISCA) 2019 ACM/IEEE 46th Annual International Symposium on Computer …, 2019 | 9 | 2019 |
| Multi-source energy harvesting management and optimization for non-volatile processors S Heidari, C Ding, Y Liu, Y Wang, J Hu 2015 Sixth International Green and Sustainable Computing Conference (IGSC), 1-2, 2015 | 9 | 2015 |
Yanzhi WangNortheastern UniversityDirección de correo verificada de northeastern.edu
