| Optimizing FPGA-based accelerator design for deep convolutional neural networks C Zhang, P Li, G Sun, Y Guan, B Xiao, J Cong Proceedings of the 2015 ACM/SIGDA international symposium on field …, 2015 | 2336 | 2015 |
| Caffeine: Toward uniformed representation and acceleration for deep convolutional neural networks C Zhang, G Sun, Z Fang, P Zhou, P Pan, J Cong IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2018 | 641* | 2018 |
| Energy-efficient CNN implementation on a deeply pipelined FPGA cluster C Zhang, D Wu, J Sun, G Sun, G Luo, J Cong Proceedings of the 2016 International Symposium on Low Power Electronics and …, 2016 | 256 | 2016 |
| An efficient design and implementation of LSM-tree based key-value store on open-channel SSD P Wang, G Sun, S Jiang, J Ouyang, S Lin, C Zhang, J Cong Proceedings of the Ninth European Conference on Computer Systems, 1-14, 2014 | 241 | 2014 |
| Efficient and effective sparse LSTM on FPGA with bank-balanced sparsity S Cao, C Zhang, Z Yao, W Xiao, L Nie, D Zhan, Y Liu, M Wu, L Zhang Proceedings of the 2019 ACM/SIGDA International Symposium on Field …, 2019 | 180 | 2019 |
| Memory partitioning for multidimensional arrays in high-level synthesis Y Wang, P Li, P Zhang, C Zhang, J Cong Proceedings of the 50th Annual Design Automation Conference, 1-8, 2013 | 116 | 2013 |
| Balanced sparsity for efficient dnn inference on gpu Z Yao, S Cao, W Xiao, C Zhang, L Nie Proceedings of the AAAI conference on artificial intelligence 33 (01), 5676-5683, 2019 | 104 | 2019 |
| Seernet: Predicting convolutional neural network feature-map sparsity through low-bit quantization S Cao, L Ma, W Xiao, C Zhang, Y Liu, L Zhang, L Nie, Z Yang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 74 | 2019 |
| Ladabert: Lightweight adaptation of bert through hybrid model compression Y Mao, Y Wang, C Wu, C Zhang, Y Wang, Y Yang, Q Zhang, Y Tong, J Bai arXiv preprint arXiv:2004.04124, 2020 | 57 | 2020 |
| SQuant: On-the-fly data-free quantization via diagonal hessian approximation C Guo, Y Qiu, J Leng, X Gao, C Zhang, Y Liu, F Yang, Y Zhu, M Guo arXiv preprint arXiv:2202.07471, 2022 | 40 | 2022 |
| Dual-side sparse tensor core Y Wang, C Zhang, Z Xie, C Guo, Y Liu, J Leng 2021 ACM/IEEE 48th Annual International Symposium on Computer Architecture …, 2021 | 36 | 2021 |
| Best-effort FPGA programming: A few steps can go a long way J Cong, Z Fang, Y Hao, P Wei, CH Yu, C Zhang, P Zhou arXiv preprint arXiv:1807.01340, 2018 | 33 | 2018 |
| Scylla: Qoe-aware continuous mobile vision with fpga-based dynamic deep neural network reconfiguration S Jiang, Z Ma, X Zeng, C Xu, M Zhang, C Zhang, Y Liu IEEE INFOCOM 2020-IEEE Conference on Computer Communications, 1369-1378, 2020 | 24 | 2020 |
| Live video analytics with FPGA-based smart cameras S Wang, C Zhang, Y Shu, Y Liu Proceedings of the 2019 Workshop on Hot Topics in Video Analytics and …, 2019 | 20 | 2019 |
| Ant: Exploiting adaptive numerical data type for low-bit deep neural network quantization C Guo, C Zhang, J Leng, Z Liu, F Yang, Y Liu, M Guo, Y Zhu 2022 55th IEEE/ACM International Symposium on Microarchitecture (MICRO …, 2022 | 12 | 2022 |
| Boosting mobile CNN inference through semantic memory Y Li, C Zhang, S Han, LL Zhang, B Yin, Y Liu, M Xu Proceedings of the 29th ACM International Conference on Multimedia, 2362-2371, 2021 | 9 | 2021 |
| Using data compression for optimizing FPGA-based convolutional neural network accelerators Y Guan, N Xu, C Zhang, Z Yuan, J Cong International workshop on advanced parallel processing technologies, 14-26, 2017 | 9 | 2017 |
| OliVe: Accelerating Large Language Models via Hardware-friendly Outlier-Victim Pair Quantization C Guo, J Tang, W Hu, J Leng, C Zhang, F Yang, Y Liu, M Guo, Y Zhu Proceedings of the 50th Annual International Symposium on Computer …, 2023 | 5 | 2023 |
| Nesting Forward Automatic Differentiation for Memory-Efficient Deep Neural Network Training C Guo, Y Qiu, J Leng, C Zhang, Y Cao, Q Zhang, Y Liu, F Yang, M Guo 2022 IEEE 40th International Conference on Computer Design (ICCD), 738-745, 2022 | 4 | 2022 |
| Caffeine: towards uniformed representation and acceleration for deep convolutional neural networks J Zhang, Chen and Fang, Zhenman and Zhou, Peipei and Pan, Peichen and Cong Proceedings of the 35th International Conference on Computer-Aided Design, 1--8, 2016 | | 2016 |
Jingsheng Jason CongVolgenau Chair for Engineering Excellence, Computer Science and Electrical Engineering, UniversityVerified email at cs.ucla.edu
