| Evaluating fast algorithms for convolutional neural networks on FPGAs L Lu, Y Liang, Q Xiao, S Yan 2017 IEEE 25th annual international symposium on field-programmable custom …, 2017 | 280 | 2017 |
| Exploring heterogeneous algorithms for accelerating deep convolutional neural networks on FPGAs Q Xiao, Y Liang, L Lu, S Yan, YW Tai Proceedings of the 54th Annual Design Automation Conference 2017, 1-6, 2017 | 225 | 2017 |
| An efficient hardware accelerator for sparse convolutional neural networks on FPGAs L Lu, J Xie, R Huang, J Zhang, W Lin, Y Liang 2019 IEEE 27th Annual International Symposium on Field-Programmable Custom …, 2019 | 157 | 2019 |
| Evaluating fast algorithms for convolutional neural networks on FPGAs Y Liang, L Lu, Q Xiao, S Yan IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2019 | 148 | 2019 |
| SpWA: An efficient sparse winograd convolutional neural networks accelerator on FPGAs L Lu, Y Liang Proceedings of the 55th Annual Design Automation Conference, 1-6, 2018 | 117 | 2018 |
| Optimize transfer learning for lung diseases in bronchoscopy using a new concept: sequential fine-tuning T Tan, Z Li, H Liu, FG Zanjani, Q Ouyang, Y Tang, Z Hu, Q Li IEEE journal of translational engineering in health and medicine 6, 1-8, 2018 | 73 | 2018 |
| Sanger: A co-design framework for enabling sparse attention using reconfigurable architecture L Lu, Y Jin, H Bi, Z Luo, P Li, T Wang, Y Liang MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture …, 2021 | 60 | 2021 |
| Tenet: A framework for modeling tensor dataflow based on relation-centric notation L Lu, N Guan, Y Wang, L Jia, Z Luo, J Yin, J Cong, Y Liang 2021 ACM/IEEE 48th Annual International Symposium on Computer Architecture …, 2021 | 56 | 2021 |
| AMOS: enabling automatic mapping for tensor computations on spatial accelerators with hardware abstraction S Zheng, R Chen, A Wei, Y Jin, Q Han, L Lu, B Wu, X Li, S Yan, Y Liang Proceedings of the 49th Annual International Symposium on Computer …, 2022 | 41 | 2022 |
| Hangrui Bi, Zizhang Luo, Peng Li, Tao Wang, and Yun Liang. 2021. Sanger: A co-design framework for enabling sparse attention using reconfigurable architecture L Lu, Y Jin MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture …, 2021 | 30 | 2021 |
| OMNI: A framework for integrating hardware and software optimizations for sparse CNNs Y Liang, L Lu, J Xie IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2020 | 30 | 2020 |
| An efficient hardware design for accelerating sparse CNNs with NAS-based models Y Liang, L Lu, Y Jin, J Xie, R Huang, J Zhang, W Lin IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2021 | 27 | 2021 |
| Exploiting sparsity to accelerate fully connected layers of cnn-based applications on mobile socs X Xie, D Du, Q Li, Y Liang, WT Tang, ZL Ong, M Lu, HP Huynh, RSM Goh ACM Transactions on Embedded Computing Systems (TECS) 17 (2), 1-25, 2017 | 25 | 2017 |
| Tensorlib: A spatial accelerator generation framework for tensor algebra L Jia, Z Luo, L Lu, Y Liang 2021 58th ACM/IEEE Design Automation Conference (DAC), 865-870, 2021 | 24 | 2021 |
| Generating systolic array accelerators with reusable blocks L Jia, L Lu, X Wei, Y Liang IEEE Micro 40 (4), 85-92, 2020 | 21 | 2020 |
| Enabling efficient fast convolution algorithms on GPUs via MegaKernels L Jia, Y Liang, X Li, L Lu, S Yan IEEE Transactions on Computers 69 (7), 986-997, 2020 | 20 | 2020 |
| FCNNLib: An efficient and flexible convolution algorithm library on FPGAs Q Xiao, L Lu, J Xie, Y Liang 2020 57th ACM/IEEE Design Automation Conference (DAC), 1-6, 2020 | 10 | 2020 |
| Accelerating convolutional neural networks on FPGAs LQ Lu, S Zheng, QC Xiao, DM Chen, Y Liang Scientia Sinica Informationis 49 (3), 277-294, 2019 | 8 | 2019 |
| Convolution acceleration and computing processing method and apparatus, electronic device, and storage medium LU Liqiang, Y Liang, X Qingcheng, YAN Shengen US Patent 11,429,852, 2022 | 7 | 2022 |
| FCNNLib: A flexible convolution algorithm library for deep learning on FPGAs Y Liang, Q Xiao, L Lu, J Xie IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2021 | 7 | 2021 |
Yun (Eric) LiangProfessor of EECS, Peking University, ACM Distinguished Scientist在 pku.edu.cn 的电子邮件经过验证
Yun (Eric) LiangProfessor of EECS, Peking University, ACM Distinguished Scientist在 pku.edu.cn 的电子邮件经过验证
Shengen YanThe Chinese University of HongKong在 ie.cuhk.edu.hk 的电子邮件经过验证