Performance Modeling and Scalability Optimization of Distributed Deep Learning Systems

Author:

Yan Feng1,Ruwase Olatunji2,He Yuxiong2,Chilimbi Trishul2

Affiliation:

1. College of William and Mary, Williamsburg, VA, USA

2. Microsoft Research, Redmond, WA, USA

Publisher

ACM

Cited by 49 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 Generic Performance Model for Deep Learning in a Distributed Environment;IEEE Access;2024

2. RLPTO: A Reinforcement Learning-Based Performance-Time Optimized Task and Resource Scheduling Mechanism for Distributed Machine Learning;IEEE Transactions on Parallel and Distributed Systems;2023-12

3. Lyra: Elastic Scheduling for Deep Learning Clusters;Proceedings of the Eighteenth European Conference on Computer Systems;2023-05-08

4. AMPeD: An Analytical Model for Performance in Distributed Training of Transformers;2023 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS);2023-04

5. Modeling the Training Iteration Time for Heterogeneous Distributed Deep Learning Systems;International Journal of Intelligent Systems;2023-02-21

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