| Graph processing on GPUs: A survey X Shi, Z Zheng, Y Zhou, H Jin, L He, B Liu, QS Hua ACM Computing Surveys (CSUR) 50 (6), 1-35, 2018 | 167 | 2018 |
| Layer-centric memory reuse and data migration for extreme-scale deep learning on many-core architectures H Jin, B Liu, W Jiang, Y Ma, X Shi, B He, S Zhao ACM Transactions on Architecture and Code Optimization (TACO) 15 (3), 1-26, 2018 | 48 | 2018 |
| Layup: Layer-adaptive and multi-type intermediate-oriented memory optimization for GPU-based CNNs W Jiang, Y Ma, B Liu, H Liu, BB Zhou, J Zhu, S Wu, H Jin ACM Transactions on Architecture and Code Optimization (TACO) 16 (4), 1-23, 2019 | 13 | 2019 |
| Layrub: layer-centric GPU memory reuse and data migration in extreme-scale deep learning systems B Liu, W Jiang, H Jin, X Shi, Y Ma Proceedings of the 23rd ACM SIGPLAN Symposium on Principles and Practice of …, 2018 | 3 | 2018 |
| GradSA: Gradient sparsification and accumulation for communication-efficient distributed deep learning B Liu, W Jiang, S Zhao, H Jin, B He Green, Pervasive, and Cloud Computing: 15th International Conference, GPC …, 2020 | 2 | 2020 |
| LayCO: Achieving Least Lossy Accuracy for Most Efficient RRAM-Based Deep Neural Network Accelerator via Layer-Centric Co-Optimization SF Zhao, F Wang, B Liu, D Feng, Y Liu Journal of Computer Science and Technology 38 (2), 328-347, 2023 | | 2023 |
| 基于忆阻器的神经网络加速器数据位宽与工作电压协同优化机制 赵少锋， 王芳， 刘博， 冯丹， 刘洋 计算机科学技术学报 38 (2), 328-347, 2023 | | 2023 |
| Bridging the Gap Between Memory and Communication Efficiency on Distributed Deep Learning Systems S Zhao, B Liu, F Wang, D Feng IEEE Access 9, 57075-57088, 2021 | | 2021 |
| Measuring Directional Semantic Similarity with Multi-features B Liu, X Shi, H Jin Web Technologies and Applications: 18th Asia-Pacific Web Conference, APWeb …, 2016 | | 2016 |
