It's necessary for my very important hobby of generating anime nudes.
3D rendering with optix. I don't do AI nonsense other than chatgpt for the occasional shell script or python function.
this post was submitted on 16 Mar 2024
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If anything AMD (for ML) is the hardware "I use [x] btw" (as in I go through unnecessary pain for purism or to one up my own superiority complex)
Earlier in my career, I compiled tensorflow with CUDA/cuDNN (NVIDIA) in one container and then in another machine and container compiled with ROCm (AMD) for cancerous tissue detection in computer vision tasks. GPU acceleration in training the model was significantly more performant with NVIDIA libraries.
It's not like you can't train deep neural networks without NVIDIA, but their deep learning libraries combined with tensor cores in Turing-era GPUs and later make things much faster.
AMD is catching up now. There are still performance differences, but they are probably not as big in the latest generation.
I must admit when I learned this was Crowder I had a sad
Just change and reupload :D
Man I just built a new rig last November and went with nvidia specifically to run some niche scientific computing software that only targets CUDA. It took a bit of effort to get it to play nice, but it at least runs pretty well. Unfortunately, now I'm trying to update to KDE6 and play games and boy howdy are there graphics glitches. I really wish HPC academics would ditch CUDA for GPU acceleration, and maybe ifort + mkl while they're at it.
Use driver 535 until explicit sync is implemented by NVIDIA.
Rocm is the AMD version
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