| DeepBurning: Automatic generation of FPGA-based learning accelerators for the neural network family Y Wang, J Xu, Y Han, H Li, X Li Proceedings of the 53rd Annual Design Automation Conference, 1-6, 2016 | 256 | 2016 |
| Engn: A high-throughput and energy-efficient accelerator for large graph neural networks S Liang, Y Wang, C Liu, L He, LI Huawei, D Xu, X Li IEEE Transactions on Computers 70 (9), 1511-1525, 2020 | 157 | 2020 |
| C-Brain: A deep learning accelerator that tames the diversity of CNNs through adaptive data-level parallelization L Song, Y Wang, Y Han, X Zhao, B Liu, X Li Proceedings of the 53rd Annual Design Automation Conference, 1-6, 2016 | 130 | 2016 |
| Linear symmetric quantization of neural networks for low-precision integer hardware X Zhao, Y Wang, X Cai, C Liu, L Zhang | 71 | 2020 |
| Wear rate leveling: Lifetime enhancement of PRAM with endurance variation J Dong, L Zhang, Y Han, Y Wang, X Li Proceedings of the 48th Design Automation Conference, 972-977, 2011 | 69 | 2011 |
| Cognitive {SSD}: A deep learning engine for {In-Storage} data retrieval S Liang, Y Wang, Y Lu, Z Yang, H Li, X Li 2019 USENIX Annual Technical Conference (USENIX ATC 19), 395-410, 2019 | 54 | 2019 |
| Network-aware locality scheduling for distributed data operators in data centers L Cheng, Y Wang, Q Liu, DHJ Epema, C Liu, Y Mao, J Murphy IEEE Transactions on Parallel and Distributed Systems 32 (6), 1494-1510, 2021 | 47 | 2021 |
| PIMSim: A flexible and detailed processing-in-memory simulator S Xu, X Chen, Y Wang, Y Han, X Qian, X Li IEEE Computer Architecture Letters 18 (1), 6-9, 2018 | 46 | 2018 |
| FCN-engine: Accelerating deconvolutional layers in classic CNN processors D Xu, K Tu, Y Wang, C Liu, B He, H Li 2018 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 1-6, 2018 | 36 | 2018 |
| Real-time meets approximate computing: An elastic CNN inference accelerator with adaptive trade-off between QoS and QoR Y Wang, H Li, X Li Proceedings of the 54th Annual Design Automation Conference 2017, 1-6, 2017 | 36 | 2017 |
| Retraining-based timing error mitigation for hardware neural networks J Deng, Y Fang, Z Du, Y Wang, H Li, O Temam, P Ienne, D Novo, X Li, ... 2015 Design, Automation & Test in Europe Conference & Exhibition (DATE), 593-596, 2015 | 36 | 2015 |
| Economizing TSV resources in 3-D network-on-chip design Y Wang, YH Han, L Zhang, BZ Fu, C Liu, HW Li, X Li IEEE Transactions on Very Large Scale Integration (VLSI) Systems 23 (3), 493-506, 2014 | 34 | 2014 |
| Re-architecting the on-chip memory sub-system of machine-learning accelerator for embedded devices Y Wang, H Li, X Li 2016 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 1-6, 2016 | 33 | 2016 |
| Deepburning-gl: an automated framework for generating graph neural network accelerators S Liang, C Liu, Y Wang, H Li, X Li Proceedings of the 39th International Conference on Computer-Aided Design, 1-9, 2020 | 31 | 2020 |
| Reliability evaluation and analysis of FPGA-based neural network acceleration system D Xu, Z Zhu, C Liu, Y Wang, S Zhao, L Zhang, H Liang, H Li, KT Cheng IEEE Transactions on Very Large Scale Integration (VLSI) Systems 29 (3), 472-484, 2021 | 30 | 2021 |
| RRAMedy: Protecting ReRAM-based neural network from permanent and soft faults during its lifetime W Li, Y Wang, H Li, X Li 2019 IEEE 37th International Conference on Computer Design (ICCD), 91-99, 2019 | 30 | 2019 |
| ProPRAM: Exploiting the transparent logic resources in non-volatile memory for near data computing Y Wang, Y Han, L Zhang, H Li, X Li Proceedings of the 52nd Annual Design Automation Conference, 1-6, 2015 | 30 | 2015 |
| Dadu-p: A scalable accelerator for robot motion planning in a dynamic environment S Lian, Y Han, X Chen, Y Wang, H Xiao Proceedings of the 55th Annual Design Automation Conference, 1-6, 2018 | 27 | 2018 |
| Resilience-aware frequency tuning for neural-network-based approximate computing chips Y Wang, J Deng, Y Fang, H Li, X Li IEEE Transactions on Very Large Scale Integration (VLSI) Systems 25 (10 …, 2017 | 27 | 2017 |
| P3M: a PIM-based neural network model protection scheme for deep learning accelerator W Li, Y Wang, H Li, X Li Proceedings of the 24th Asia and South Pacific Design Automation Conference …, 2019 | 26 | 2019 |
