Is ROCm actually usable in this years machine learning ecosystem? Can I just drop in any PyTorch model that was developed on CUDA and expect it to work?
On an MI250+ system or other similar architectures that mirror what El-Capitan is going to look like, ROCm is stable and there are pytorch + cupy backends for it. It mostly just works. If you have custom kernels as part of your pipeline you'd need to convert them from CUDA to HIP though.
If you're looking for something on AMD consumer cards...then you have to keep waiting.
Mesa advertises support for OpenCL[1], so the idea of using it as an ML backend isn't ridiculous. But I can't speak to whether or not anybody has actually tried to make that work, or where it stands. [1]: https://www.khronos.org/opencl/
I think OpenCL lost the battle in ML era, CUDA crashed it, followed by newcomers like SYCL and ROCm these days.
Oh yeah. I didn't mean to suggest this as something anybody would want to do for any kind of serious use. Just pointing out that, in the abstract, the idea of doing it isn't totally ridiculous.
Honestly, the likes of OpenAI and Mosaic need to consider Nvidia a huge threat long term. Nvidia has shown time and time again, they will royally fuck over anyone they have to in order to drive profit. Then, if they dare talk negatively about them, they will just discontinue their access to hardware. Not saying AMD is a savior, but having only ONE option will lead to long term issues.
> they will just discontinue their access to hardware Yup - which is exactly what is going on in the cloud space right now. Because AWS and GCP chose to innovate with their own accelerators, Nvidia heavily favoured Azure for a while. Recently, GCP seem to have capitulated somehow and so are back on the bandwagon. Oracle, of course, never had any hope of success in cloud without leaning on some form of non-technical m…
> Because AWS and GCP chose to innovate with their own accelerators, Nvidia heavily favoured Azure for a while.
AWS and GCP work on competitors to Nvidia's products, so Nvidia favors Azure who is not doing that, and this is somehow Nvidia's fault or even a problem?
Looks more like Nvidia was hedging its bets in case AWS or GCP succeeded at developing competitive AI chips and then transitioned completely away from Nvidia.
> they will just discontinue their access to hardware Yup - which is exactly what is going on in the cloud space right now. Because AWS and GCP chose to innovate with their own accelerators, Nvidia heavily favoured Azure for a while. Recently, GCP seem to have capitulated somehow and so are back on the bandwagon. Oracle, of course, never had any hope of success in cloud without leaning on some form of non-technical m…
> Because AWS and GCP chose to innovate with their own accelerators, Nvidia heavily favoured Azure for a while. AWS and GCP work on competitors to Nvidia's products, so Nvidia favors Azure who is not doing that, and this is somehow Nvidia's fault or even a problem? Looks more like Nvidia was hedging its bets in case AWS or GCP succeeded at developing competitive AI chips and then transitioned completely away from Nvi…
It's not a problem from Nvidia's perspective, and AWS/GCP wouldn't have a right to complain - but users might reasonably conclude that this is a problem, and likewise regulators might consider it unacceptable for Nvidia to have this much market power, if they actually had the technical expertise to examine such things.