I\'m working on a Jupyter Notebook and would like to make it run faster by using Google GPU. I\'ve already made a few researches and found a solution, but it didn\'t work fo
I think what you're asking is not possible. Some explanations:
In your situation you have two frontends, that you are using to interact with your code:
Jupyter Notebook
(served to your browser by a local server running your computer)Google Colab
(served from google servers)Additionally you have two backends that run the code they're receiving from your frontend:
IPython kernels
(started by your jupyter process)Google cloud runtimes
(running on google cloud infrastructure, possibly with GPU acceleration)The following combinations are possible:
Jupyer Notebook --> IPython kernel
which is probably the setup you started with.Google Colab --> Google cloud runtimes
is the default setup of Google colab. You upload a notebook file to your google drive (or create a new one). The code you're executing in the Colab interface get's run on google cloud infrastructure. This also give you access to GPU acceleration by activating it in Runtime -> Change Runtime TypeGoogle Colab --> IPython kernel
You're still writing code in the Google Colab interface as in (2), but when you execute a cell it's run by a IPython kernel on your computer using your local hardware. This setup is described in the 'local runtime' help article you linked.What you're trying to do sounds like:
Jupyter Notebook --> Google cloud runtime
which is the only combination here that is not possible.If you want to run a notebook using with GPU acceleration on google cloud hardware you have two options: