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FastestLearner t1_j6v8nsz wrote

Being able to use the GPU doesn’t have anything to do with Jupyter. It’s the packages (TensorFlow, PyTorch, etc.) that must be installed with CUDA support and also you must have the correct drivers installed. My recommendation would be simply use a conda environment, which automatically installs the correct CUDA packages during a PyTorch install or a Tensorflow install.

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Appropriate_Ant_4629 t1_j6vmpm8 wrote

> Being able to use the GPU doesn’t have anything to do with Jupyter.

It's certainly not required....

.. but Nvidia makes it extremely convenient through the notebooks they provide:

https://catalog.ngc.nvidia.com/resources

>> The NGC catalog offers step-by-step instructions and scripts through Jupyter Notebooks for various use cases, including machine learning, computer vision, and conversational AI. These resources help you examine, understand, customize, test, and build AI faster, while taking advantage of best practices.

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BellyDancerUrgot t1_j6v9w0p wrote

Last I checked for tensorflow-gpu conda install didn’t install the correct cuda version for some reason and it was annoying to roll back and then reinstall correct cuda and cudnn versions. PyTorch is fking clean tho.

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