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So let’s face it, if you are doing anything with deep learning, GPUs are a must.
They are expensive, and infrastructure is hard to set up. Most of the time, you’re coding when the GPUs are sitting idle, and it’s a pain to pay for the uptime when no deep learning scripts work on the first go.
This was a problem I faced as “GPU Poor”. I didn’t want to spend money on GPUs when I was coding or doing something that didn’t leverage the GPU compute. Even for things like downloading data, models, and data transformation, you don’t need a GPU but still have to do it on a GPU.
And especially on cloud providers, where you will have to worry about infrastructure. You can set up a VM with a GPU attached, then choose an image which is not even well-documented. If not done properly, you will have to install CUDA and stuff from scratch. If that also doesn’t work, most of the time you…