Optimizing Multi-Level Checkpointing for Distributed Deep Learning Workloads on Cloud Spot VM Clusters
Author:
Affiliation:
1. webOS SW Development Group, LG Electronics, Seoul, South Korea
2. Department of Computer Science and Engineering, Sogang University, Seoul, South Korea
3. Electronics and Telecommunications Research Institute (ETRI), Daejeon, South Korea
Funder
Institute of Information Communications Technology Planning Evaluation (IITP) grants
Korean Government, Ministry of Science and ICT
National Research Foundation of Korea (NRF) Grant
Korean Government, MSIT
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx8/6287639/10380310/10639967.pdf?arnumber=10639967
Reference25 articles.
1. Evaluating Multi-Level Checkpointing for Distributed Deep Neural Network Training
2. Check-n-run: A checkpointing system for training deep learning recommendation models;Eisenman
3. PyTorch distributed
4. Horovod: Fast and easy distributed deep learning in TensorFlow;Sergeev;arXiv:1802.05799,2018
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