vPipe: A Virtualized Acceleration System for Achieving Efficient and Scalable Pipeline Parallel DNN Training

Author:

Zhao ShixiongORCID,Li Fanxin,Chen XushengORCID,Guan Xiuxian,Jiang JianyuORCID,Huang Dong,Qing Yuhao,Wang Sen,Wang Peng,Zhang Gong,Li ChengORCID,Luo Ping,Cui HemingORCID

Funder

Huawei Innovation Research Program

Croucher Innovation Award

National Natural Science Foundation of China

USTC Research Funds of Double First-Class Initiative

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Hardware and Architecture,Signal Processing

Cited by 20 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A snapshot of parallelism in distributed deep learning training;Revista Colombiana de Computación;2024-06-30

2. Advances of Pipeline Model Parallelism for Deep Learning Training: An Overview;Journal of Computer Science and Technology;2024-05

3. AdaPipe: Optimizing Pipeline Parallelism with Adaptive Recomputation and Partitioning;Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 3;2024-04-27

4. LaANIL: ANIL with Look-Ahead Meta-Optimization and Data Parallelism;Electronics;2024-04-22

5. HCPipe: Hidden Computation Pipeline Model Parallelism for Large-scale DCNN Model Training;2024 5th International Conference on Computer Engineering and Application (ICCEA);2024-04-12

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