| Auto-tuning neural network quantization framework for collaborative inference between the cloud and edge G Li, L Liu, X Wang, X Dong, P Zhao, X Feng Artificial Neural Networks and Machine Learning–ICANN 2018: 27th …, 2018 | 91 | 2018 |
| Optimizing deep neural networks on intelligent edge accelerators via flexible-rate filter pruning G Li, X Ma, X Wang, H Yue, J Li, L Liu, X Feng, J Xue Journal of Systems Architecture 124, 102431, 2022 | 45 | 2022 |
| Fusion-Catalyzed Pruning for Optimizing Deep Learning on Intelligent Edge Devices G Li, X Ma, X Wang, L Liu, J Xue, X Feng IEEE Transactions on Computer-Aided Design of Integrated Circuits and …, 2020 | 37 | 2020 |
| LANCE: Efficient Low-Precision Quantized Winograd Convolution for Neural Networks Based on Graphics Processing Units G Li, L Liu, X Wang, X Ma, X Feng ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 25 | 2020 |
| Lowino: Towards efficient low-precision winograd convolutions on modern cpus G Li, Z Jia, X Feng, Y Wang Proceedings of the 50th International Conference on Parallel Processing, 1-11, 2021 | 22 | 2021 |
| Background Subtraction on Depth Videos with Convolutional Neural Networks X Wang, L Liu, G Li, X Dong, P Zhao, X Feng 2018 International Joint Conference on Neural Networks (IJCNN), 1-7, 2018 | 22 | 2018 |
| ProSparse: Introducing and Enhancing Intrinsic Activation Sparsity within Large Language Models C Song, X Han, Z Zhang, S Hu, X Shi, K Li, C Chen, Z Liu, G Li, T Yang, ... arXiv preprint arXiv:2402.13516, 2024 | 18 | 2024 |
| Unleashing the Low-Precision Computation Potential of Tensor Cores on GPUs G Li, J Xue, L Liu, X Wang, X Ma, X Dong, J Li, X Feng 2021 IEEE/ACM International Symposium on Code Generation and Optimization …, 2021 | 18 | 2021 |
| Accelerating deep learning inference with cross-layer data reuse on GPUs X Wang, G Li, X Dong, J Li, L Liu, X Feng European Conference on Parallel Processing, 219-233, 2020 | 16 | 2020 |
| Acorns: A Framework for Accelerating Deep Neural Networks with Input Sparsity X Dong, L Liu, P Zhao, G Li, J Li, X Wang, X Feng 2019 28th International Conference on Parallel Architectures and Compilation …, 2019 | 16 | 2019 |
| Multi-source news recommender system based on convolutional neural networks B Yu, J Shao, Q Cheng, H Yu, G Li, S Lü Proceedings of the 3rd International Conference on Intelligent Information …, 2018 | 16 | 2018 |
| G-SEPM: building an accurate and efficient soft error prediction model for GPGPUs H Yue, X Wei, G Li, J Zhao, N Jiang, J Tan Proceedings of the International Conference for High Performance Computing …, 2021 | 14 | 2021 |
| An adaptive scheduling algorithm for heterogeneous Hadoop systems J Han, Z Yuan, Y Han, C Peng, J Liu, G Li 2017 IEEE/ACIS 16th International Conference on Computer and Information …, 2017 | 12 | 2017 |
| XDN: towards efficient inference of residual neural networks on cambricon chips G Li, X Wang, X Ma, L Liu, X Feng Benchmarking, Measuring, and Optimizing: Second BenchCouncil International …, 2020 | 11 | 2020 |
| An Energy-aware Virtual Machine Placement Algorithm in Cloud Data Center M Tan, C Chi, J Zhang, S Zhao, G Li, S Lü Proceedings of the 2nd International Conference on Intelligent Information …, 2017 | 8 | 2017 |
| Accelerating deep neural network filter pruning with mask-aware convolutional computations on modern CPUs X Ma, G Li, L Liu, H Liu, X Wang Neurocomputing 505, 375-387, 2022 | 7 | 2022 |
| ApproxDup: Developing an Approximate Instruction Duplication Mechanism for Efficient SDC Detection in GPGPUs X Wei, N Jiang, H Yue, X Wang, J Zhao, G Li, M Qiu IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2023 | 6 | 2023 |
| Exploiting the input sparsity to accelerate deep neural networks: poster X Dong, L Liu, G Li, J Li, P Zhao, X Wang, X Feng Proceedings of the 24th Symposium on Principles and Practice of Parallel …, 2019 | 6 | 2019 |
| Fast CNN pruning via redundancy-aware training X Dong, L Liu, G Li, P Zhao, X Feng International Conference on Artificial Neural Networks, 3-13, 2018 | 5 | 2018 |
| CoAxNN: Optimizing on-device deep learning with conditional approximate neural networks G Li, X Ma, Q Yu, L Liu, H Liu, X Wang Journal of Systems Architecture 143, 102978, 2023 | 4 | 2023 |
Xiaobing FengProfessor of Institute of Computing Technology, Chinese Academy of SciecnesAdresse e-mail validée de ict.ac.cn