fairDMS: Rapid Model Training by Data and Model Reuse
Author:
Affiliation:
1. Argonne National Laboratory,Data Science and Learning Division,Lemont,IL,USA,60439
2. Argonne National Laboratory,X-ray Science Division,Lemont,IL,USA,60439
3. SLAC National Accelerator Laboratory,Menlo Park,CA,USA,94025
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9912642/9912651/09912676.pdf?arnumber=9912676
Cited by 3 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. MalleTrain: Deep Neural Networks Training on Unfillable Supercomputer Nodes;Proceedings of the 15th ACM/SPEC International Conference on Performance Engineering;2024-05-07
2. Optimizing the Training of Co-Located Deep Learning Models Using Cache-Aware Staggering;2023 IEEE 30th International Conference on High Performance Computing, Data, and Analytics (HiPC);2023-12-18
3. Deep learning at the edge enables real-time streaming ptychographic imaging;Nature Communications;2023-11-03
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