| DAPPLE: a pipelined data parallel approach for training large models S Fan, Y Rong, C Meng, Z Cao, S Wang, Z Zheng, C Wu, G Long, J Yang, ... Proceedings of the 26th ACM SIGPLAN Symposium on Principles and Practice of …, 2021 | 146 | 2021 |
| Training deeper models by GPU memory optimization on TensorFlow C Meng, M Sun, J Yang, M Qiu, Y Gu Proc. of ML Systems Workshop in NIPS, 2017 | 98 | 2017 |
| Dl2: A deep learning-driven scheduler for deep learning clusters Y Peng, Y Bao, Y Chen, C Wu, C Meng, W Lin IEEE Transactions on Parallel and Distributed Systems 32 (8), 1947-1960, 2021 | 78 | 2021 |
| Characterizing deep learning training workloads on alibaba-pai M Wang, C Meng, G Long, C Wu, J Yang, W Lin, Y Jia 2019 IEEE International Symposium on Workload Characterization (IISWC), 189-202, 2019 | 48 | 2019 |
| Fast Training of Deep Learning Models over Multiple GPUs X Yi, Z Luo, C Meng, M Wang, G Long, C Wu, J Yang, W Lin Proceedings of the 21st International Middleware Conference, 105-118, 2020 | 16 | 2020 |
| Efficient Deep Learning Inference Based on Model Compression Q Zhang, M Zhang, M Wang, W Sui, C Meng, J Yang, W Kong, X Cui, ... Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 14 | 2018 |
| PHoToNs–A parallel heterogeneous and threads oriented code for cosmological N-body simulation Q Wang, ZY Cao, L Gao, XB Chi, C Meng, J Wang, L Wang Research in Astronomy and Astrophysics 18 (6), 062, 2018 | 11 | 2018 |
| Large-Scale Parallelization Based on CPU and GPU Cluster for Cosmological Fluid Simulations C Meng, L Wang, Z Cao, L Feng, W Zhu Computers & Fluids, 2014 | 8 | 2014 |
| Acceleration of a High Order Finite-Difference WENO Scheme for Large-Scale Cosmological Simulations on GPU C Meng, L Wang, Z Cao, X Ye, LL Feng Proceedings of the 2013 IEEE 27th International Symposium on Parallel and …, 2013 | 7 | 2013 |
| The ultramarine simulation: properties of dark matter haloes before redshift 5.5 Q Wang, L Gao, C Meng Monthly Notices of the Royal Astronomical Society 517 (4), 6004-6012, 2022 | 6 | 2022 |
| PhotoNs-GPU:A GPU accelerated cosmological simulation code Q Wang, C Meng Research in Astronomy and Astrophysics, 2021 | 4 | 2021 |
| 基于 Charm++ 运行时环境的异构计算应用容错研究 孟晨， 曹宗雁， 王龙， 迟学斌 计算机工程与应用, 1-7, 2016 | | 2016 |
