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A simple CLI tool to poll the NUS SOC cluster's GPU status, so you find a place to train your super model!

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NUS SoC cluster GPU status checker

Sample output

Sample Output

Usage

  1. Clone the project to one of the SoC servers' home directory. The home directory is shared across the cluster.
  2. Make sure dependencies are installed pip3 install -r req.txt
  3. Fill in your private key path in mi_nus_soc_gpu_status_reader.py if you are using key pair to authenticate, if not use this line instead(uncomment)
client.connect(f'{host}.comp.nus.edu.sg', username='mingda', password='PASSWORD_HERE')

Now run mi_nus_soc_gpu_status_reader.py :)

TODO

  • Multi-thread?
  • CLI args?

Please STAR if you find it useful!!!

Thanks!!!

Contributor

@YipingRuan

Thanks to him, the output looks a lot nicer now! 🎉

@lv2020

Thanks to lv2020, the program now executes in a thread pool, much faster!

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A simple CLI tool to poll the NUS SOC cluster's GPU status, so you find a place to train your super model!

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