Running two different independent PyTorch programs on a single GPU
I have a single NVIDIA GPU which has a memory of 16GB. I have to run two different (and independent; meaning, two different problems: one is a vision type task, another is NLP task) Python programs. The codes are written using PyTorch and both the codes can use GPU.
I have tested that program 1 takes roughly 5GB of GPU memory, and the rest is free. If I run the two programs, will it hamper the model performance or will it cause any process conflicts?
Linked question; but it does not necessarily mean PyTorch codes

I do not know the details of how this works, but I can tell from experience that both programs will run well (as long as they do not need more than 16GB of RAM when combined), and execution times should stay roughly the same.
However, computer vision usually requires a lot of IO (mostly reading images), if the other task needs to read files too, this part may become slower than when running both programs individually.
