> Best of all is that I simply set the device to `torch.device('cuda')` rather than openCL, which does wonders for compatibility
Man oh man where did we go wrong that cuda is the more compatible option over OpenCL?
Man oh man where did we go wrong that cuda is the more compatible option over OpenCL?
AMD should just get it's shit together. This is ridiculous. Not the name, but the fact that you can only do FP64 on a GPU. Everybody is moving to FP16 and AMD is stuck on doubles?
The API level I could target was at least two or three versions behind the latest they have to offer.
But this is one of the great strengths of CUDA: I can develop a kernel on my workstation, my boss can demo it on his laptop and we can deploy it on Jetsons or the multi-gpu cluster with minimal changes and i can be sure that everything runs everywhere.
I just don't understand the details enough to understand why things are problematic without CUDA :(
Some architectures provide fast F16->F32 and F32->F16 conversion instructions so you can DIY the memory bandwidth saving - that always seemed reasonable to me, but I don't know if the AMD hardware people are/will go down that path.
Keeping all those FPUs busy is another problem and not easy, but in cases where it can be done FP32 is clearly desirable.