I know those cards are second class citizens in the world of deep learning, but they have had (experimental) pytorch support for a while now, where are the offerings?
> I know those cards are second class citizens in the world of deep learning,
It's worse than that. AMD cards aren't second class citizens, they're not even on the same playing field. ROCm can't compete with CUDA and its ecosystem at all, the most popular deep learning frameworks are only experimentally supported, and Nvidia ships more dedicated tensor processing cores for AI acceleration on their cards. Nvidia has a near monopoly in AI not because they're particularly amazing, but because it seems like AMD is just uninterested in competing.
With NVidia I can just buy any random GPU and expect it to work for everything I throw at it (at long as it has enough VRAM). With AMD it's a roulette, and only a handful of very expensive server/workstation GPUs (8 in total if I'm counting it right) are actually officially supported. It's a joke.
They need to better support their own products, and they need to officially support all of their consumer GPUs to expand their mindshare. They're not doing that. From what I can see they only seem to be interested in the traditional HPC space.
Why would anyone offer a strictly worse product unless it were lots cheaper to offer, which it isn't? (Even for non-AI use cases, I don't think AMD has much that's more attractive in servers?)
They are simply put not price competitive in instruction per dollar at the high end though they are starting to catch up. But to me the biggest reason is software wise they are behind Nvidia. NVidia might be considered a hardware company because of its gpus but they are underappreciated as a the software company that build tools for other to utilise its gpus.
They’re not price competitive anywhere in the line.
By the time you spend hours/days/weeks constantly dealing with random edge cases and issues with the poor software support of AMD you could have bought 2-3x the Nvidia hardware (minimum) and still come out ahead.
It's worse than that. AMD cards aren't second class citizens, they're not even on the same playing field. ROCm can't compete with CUDA and its ecosystem at all, the most popular deep learning frameworks are only experimentally supported, and Nvidia ships more dedicated tensor processing cores for AI acceleration on their cards. Nvidia has a near monopoly in AI not because they're particularly amazing, but because it seems like AMD is just uninterested in competing.