I’m looking to buy a new GPU. My main use case will be training and running neural nets (tensorflow+pytorch); gaming isn’t really a priority.
Thing is, I use wayland (via sway), and so I’d really prefer to get an AMD GPU. Nvidia doesn’t seem very linux friendly at the moment, especially when it comes to wayland unfortunately.
On the other hand, Nvidia seems to be the clear frontrunner right now when it comes to NN acceleration. I’m worried that if I got an AMD GPU to accelerate my NN work, I’d just be wasting my money.
What do you all think?
Edit: I’ve used GPUs to accelerate NN models in the past, but they weren’t my own, they were provided by my uni’s research infra and/or google collab. So this would be the first time I’d be using my own GPU hardware for this purpose.
the unfortunate truth is that NVidia has a complete stranglehold on the compute market. They recognized the capabilities of massively parallel compute early on and pushed CUDA super super hard to any organization doing compute. And it worked- CUDA is much easier to implement than openCL, and was released two years earlier too, so everyone ended up standardizing on it. They are currently reaping the benefits of that monopolization through their now huge enterprise GPGPU market and can basically piss down the backs of consumers and competitors alike without repercussions. OpenCL and AMD’s implementation was a day late and harder to implement…
Do not buy AMD if you need to do any kind of compute- whether it be rendering ala Blender/AE, accelerated engineering CAD workflows, or big data handling. No tools are designed around anything but CUDA, and it sucks because Jensen is a greedy asshole, but you gotta pay your dues.