How to execute python script (face detection on very large dataset) on Nvidia GPU
Your first problem is actually getting your Python code to run on all CPU cores!
Python is not fast, and this is pretty much by design. More accurately, the design of Python emphasizes other qualities. Multi-threading is fairly hard in general, and Python can't make it easy due to those design constraints. A pity, because modern CPU's are highly parallel. In your case, there's a lucky escape. Your problem is also highly parallel. You can just divide those 500,000 video's over CPU cores. Each core runs a copy of the Python script over its own input. Even a quad-core would process 4x125.000 files using that strategy.
As for the GPU, that's not going to help much with Python code. Python simply doesn't know how to send data to the GPU, send commands to the CPU, or get results back. Some Pythons extensions can use the GPU, such as Tensorflow. But they use the GPU for their own internal purposes, not to run Python code.
I have a python script that loops through a dataset of videos and applies a face and lip detector function to each video. The function returns a 3D numpy array of pixel data centered on the human lips in each frame. 
The dataset is quite large (70GB total, ~500,000 videos each about 1 second in duration) and executing on a normal CPU would take days. I have a Nvidia 2080 Ti that I would like to use to execute code. Is it possible to include some code that executes my entire script on the available GPU? Or am I oversimplifying a complex problem?
So far I have been trying to implement using numba and pycuda and havent made any progress as the examples provided don't really fit my problem well.