petuum/adaptdl
Resource-adaptive cluster scheduler for deep learning training.
This project helps deep learning engineers and machine learning researchers efficiently train their deep learning models in shared cloud or on-premise computing environments. It takes your PyTorch training code and resource requirements as input, automatically adjusting batch sizes, learning rates, and resource allocation. The output is faster, more cost-effective training and better utilization of your computing infrastructure.
453 stars. Used by 1 other package. No commits in the last 6 months. Available on PyPI.
Use this if you are training deep learning models on shared clusters or in the cloud and want to optimize resource usage and training speed without manual tuning.
Not ideal if you are only running single-node deep learning training jobs or do not need to manage shared resources efficiently.
Stars
453
Forks
81
Language
Python
License
Apache-2.0
Category
Last pushed
Mar 05, 2023
Commits (30d)
0
Dependencies
6
Reverse dependents
1
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