如何在 jupyter notebook 中使用远程机器的 GPU

Question

I am trying to run tensorflow on a remote machine's GPU through Jupyter notebook. However, if I print the available devices using tf, I only get CPUs. I have never used a GPU before and am relatively new at using conda / jupyter notebook remotely as well, so I am not sure how to set up using the GPU in jupyter notebook.

I am using an environment set up by someone else who already executed the same code on the same GPU, but they did it via python script, not in a jupyter notebook.

this is the only code in the other person's file that had to do with the GPU

config = tf.ConfigProto()

config.gpu_options.allow_growth=True

set_session(tf.Session(config=config))

Answer 1

I think the problem was that I had tensorflow in my environment instead of tensorflow-gpu. But now I get this message "cudaGetDevice() failed. Status: CUDA driver version is insufficient for CUDA runtime version" and I don't know how to update the driver through terminal

Answer 2

How is your environment set up? Specifically, what is your remote environment, and what is your local environment? Sounds like your CUDA drivers are out of date, but it could be more than just that. If you are just getting started, I would recommend finding an environment that requires little to no configuration work on your part, so you can get started more easily/quickly.

For example, you can run GPUs on the cloud, and connect to them via local terminal. You also have your "local" frontend be Colab by connecting it to a local runtime. ( This video explains that particular setup , but there's lots of other options)

You may also want to try running nvidia-smi on the remote machine to see if the GPUs are visible.

Answer 3

Here is another solution, that describes how to set up a GPU-Jupyterlab instance with Docker.

To update your drivers via terminal, run:

ubuntu-drivers devices
sudo ubuntu-drivers autoinstall
sudo reboot

Are your CUDA paths set appropriately? Like that?

export PATH=/usr/local/cuda/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda/lib64:${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}