I'd like to play with CUDA, but I just got a new laptop without an Nvidia GPU, coming from one that had a built in Nvidia GPU. It's got a thunderbolt port, but unfortunately most of the gpu's are quite expensive at around 400$. Does anyone know any cheaper options?
If you just want to try for a few hours, you can add GPU(s) onto a GCP CE instance. Along with the trial credits it should get you a few hours poking around with cuda.
Otherwise, get a pre-owned GTX950 (one that doesn't require external power supply) and a TB3 to PCI-E x16 adapter. Not enclousure, adapter. Should cost you around $200 all in IIRC. And it allows you to upgrade the card furthur down the line since most of the cost is the adapter.
Do you know what exactly I should search for when looking for a "TB3 to PCI-E x16 adapter"? Will this utilize all thunderbolt lanes available? I've got a newer laptop that, I believe, has all lanes available.
For tinkering around, just use Googe Colab[1]. They offer free hosted Jupyter notebooks and have both Nvidia GPU[2] and Google TPU[3] runtime options available.
Here[4] is a notebook that shows how to install CUDA into an environment using the GPU accelerated runtime.
Only major downside is that resources aren't guaranteed (see first section under "Resource Limits" here[5]), so you sporadically may not be able to start a GPU-accelerated runtime session. But that shouldn't be much of a blocker for tinkering purposes.
