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2020 – today
- 2024
[j3]Dongsheng Li
, Shengwei Li, Zhiquan Lai, Yongquan Fu, Xiangyu Ye, Lei Cai, Linbo Qiao:
A Memory-Efficient Hybrid Parallel Framework for Deep Neural Network Training. IEEE Trans. Parallel Distributed Syst. 35(4): 577-591 (2024)- [j2]Shengwei Li, Kai Lu, Zhiquan Lai, Weijie Liu, Keshi Ge, Dong Sheng Li:
A Multidimensional Communication Scheduling Method for Hybrid Parallel DNN Training. IEEE Trans. Parallel Distributed Syst. 35(8): 1415-1428 (2024) - 2023
- [j1]Zhiquan Lai, Shengwei Li, Xudong Tang, Keshi Ge, Weijie Liu, Yabo Duan, Linbo Qiao, Dongsheng Li:
Merak: An Efficient Distributed DNN Training Framework With Automated 3D Parallelism for Giant Foundation Models. IEEE Trans. Parallel Distributed Syst. 34(5): 1466-1478 (2023) - [c13]Shengwei Li, Huajun Zhang:
Keyword Spotting Based on CTC and Similarity Matching for Chinese Speech. ICIS 2023: 79-84 - [c12]Xiaoge Deng, Tao Sun, Shengwei Li, Dongsheng Li:
Stability-Based Generalization Analysis of the Asynchronous Decentralized SGD. AAAI 2023: 7340-7348 - [c11]Wei Wang, Zhiquan Lai, Shengwei Li, Weijie Liu, Keshi Ge, Yujie Liu, Ao Shen, Dongsheng Li:
Prophet: Fine-grained Load Balancing for Parallel Training of Large-scale MoE Models. CLUSTER 2023: 82-94 - [c10]Zhiquan Lai, Yanqi Hao, Shengwei Li, Dongsheng Li:
Communication Analysis for Multidimensional Parallel Training of Large-scale DNN Models. HPCC/DSS/SmartCity/DependSys 2023: 728-729 - [c9]Chunlin Jin, Yong Xue, Tao Yuan, Shengwei Li, Botao He, Liang Zhao:
Observing Anthropogenic CO2 Emissions with TanSat in Northeast China. IGARSS 2023: 1059-1061 - [c8]Botao He, Yong Xue, Xi Lu, Chunlin Jin, Shengwei Li, Wenhao Liu, Peng Wang, Xiangkai Wang, Pei Li:
Monitoring of Xch4 Changes and Anomaly in Hebei Province, China Based on Tropomi. IGARSS 2023: 2107-2108 - [c7]Tao Yuan, Yong Xue, Liang Zhao, Chunlin Jin, Shengwei Li, Pei Li:
Improved Accuracy of XCO2 Retrieval Based on OCO-2 Rtretrieval Framework Model. IGARSS 2023: 2109-2112 - [i4]Shengwei Li, Zhiquan Lai, Yanqi Hao, Weijie Liu, Keshi Ge, Xiaoge Deng, Dongsheng Li, Kai Lu:
Automated Tensor Model Parallelism with Overlapped Communication for Efficient Foundation Model Training. CoRR abs/2305.16121 (2023) - [i3]Xiaoge Deng, Li Shen, Shengwei Li, Tao Sun, Dongsheng Li, Dacheng Tao:
Towards Understanding the Generalizability of Delayed Stochastic Gradient Descent. CoRR abs/2308.09430 (2023) - 2022
- [c6]Weijie Liu, Zhiquan Lai, Shengwei Li, Yabo Duan, Keshi Ge, Dongsheng Li:
AutoPipe: A Fast Pipeline Parallelism Approach with Balanced Partitioning and Micro-batch Slicing. CLUSTER 2022: 301-312 - [c5]Yabo Duan, Zhiquan Lai, Shengwei Li, Weijie Liu, Keshi Ge, Peng Liang, Dongsheng Li:
HPH: Hybrid Parallelism on Heterogeneous Clusters for Accelerating Large-scale DNNs Training. CLUSTER 2022: 313-323 - [c4]Shengwei Li, Zhiquan Lai, Dongsheng Li, Yiming Zhang, Xiangyu Ye, Yabo Duan:
EmbRace: Accelerating Sparse Communication for Distributed Training of Deep Neural Networks. ICPP 2022: 7:1-7:11 - [i2]Zhiquan Lai, Shengwei Li, Xudong Tang, Keshi Ge, Weijie Liu, Yabo Duan, Linbo Qiao, Dongsheng Li:
Merak: An Efficient Distributed DNN Training Framework with Automated 3D Parallelism for Giant Foundation Models. CoRR abs/2206.04959 (2022) - 2021
- [c3]Lizhi Zhang, Zhiquan Lai, Shengwei Li, Yu Tang, Feng Liu, Dongsheng Li:
2PGraph: Accelerating GNN Training over Large Graphs on GPU Clusters. CLUSTER 2021: 103-113 - [c2]Xiangyu Ye, Zhiquan Lai, Shengwei Li, Lei Cai, Ding Sun, Linbo Qiao, Dongsheng Li:
Hippie: A Data-Paralleled Pipeline Approach to Improve Memory-Efficiency and Scalability for Large DNN Training. ICPP 2021: 71:1-71:10 - [i1]Shengwei Li, Zhiquan Lai, Dongsheng Li, Xiangyu Ye, Yabo Duan:
EmbRace: Accelerating Sparse Communication for Distributed Training of NLP Neural Networks. CoRR abs/2110.09132 (2021)
2000 – 2009
- 2009
- [c1]Shengwei Li, Lingsheng Li, Chong Han:
Mining closed frequent itemset based on FP-Tree. GrC 2009: 354-357
Coauthor Index
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