Running several Google Colab Notebooks at the same time
Each Colab notebook uses a distinct virtual machine backend in order to perform computations. From a performance perspective, each notebook will be isolated from the activity of distinct notebooks.
In order to offer more useful guidance, please share a self-contained example that shows, with code, what you are doing and the performance bottleneck you observe.
If I run several Google Colab Notebooks (runtimes) at the same time, is the perfomance shared?
I have a big dataframe to operate on so I decided to split it and let the code run on each part on a different notebook. However it seems to take as long as it would take on the whole thing in one.
Is there any information on that?