Quote:
Originally Posted by poisondeathray
I think so...I can only use 1x_Desharpen on smaller dimensions . You can look at GPU caps viewer or similar utilities and it looks like it's using all
I wonder if there is a way to share system memory with CUDA memory ? eg. Although it's slower, some 3D/CG renderers can offload graphics card memory to system memory when doing calculations (like a shared pool) enabling you to complete if the scene is too large
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I believe graphics drivers automatically do this in 3D programs, but that might not be the case with CUDA.
PyTorch does have a "empty cache" function. Maybe you could call it every few frames with
FrameEval.
https://pytorch.org/docs/stable/cuda...ory-management