I have a 7900XTX I would like to use for AI. I tried to get ollama working on my windows gaming PC this last weekend through Docker and WSL, but that was a pain.
It seems that pytorch might have worked but I still need to try out TensorFlow. Both of those ecosystems seem a hair fractured when it comes to AMD.
While I am sure it can be done, its nowhere near the point and click experience like it was on my laptop with an Nvidia card.
I’ll keep trying, but I don’t know how far I’ll get.
I am still going to build a dedicated machine for AI work, so I am not sure if I want to break my gaming rig too hard. All of that mess would be so much easier on a Linux rig with none of the windows fluff getting in the way.
That’s the opposite of the feedback I got. AMD claims to support all of the transformers library but many people report this to be a lie.
I am in no love of companies that establish de-facto monopolices, but that is indeed what NVidia has right now. Everything is built over CUDA, AMD has a lot of catch-up to do.
I have the impression that Apple chips support more things than AMD does.
There are some people making things work on AMD, and I cheer to them, but let’s not pretend it is as easy as with Nvidia. Most packages depend on cuda for gpu acceleration.
Can’t wait! But really, this type of things is what makes it hard for me to cheer at AMD:
For reasons unknown to me, AMD decided this year to discontinue funding the effort and not release it as any software product. But the good news was that there was a clause in case of this eventuality: Janik could open-source the work if/when the contract ended.
I wish we had a champion of openness but in that respect AMD just looks like a worse version of NVidia. Hell, even Intel has been a better player!
I just got DirectML working with torch in WSL2 which was fairly painless.
I am wondering if that isn’t a better option than trying to emulate CUDA directly. Love it or hate it, Microsoft did do a fairly good job wrangling in different platforms with DirectX.
Yes, it’s about as easy as on Nvidia
Not nearly as flexible though.
I have a 7900XTX I would like to use for AI. I tried to get ollama working on my windows gaming PC this last weekend through Docker and WSL, but that was a pain.
It seems that pytorch might have worked but I still need to try out TensorFlow. Both of those ecosystems seem a hair fractured when it comes to AMD.
While I am sure it can be done, its nowhere near the point and click experience like it was on my laptop with an Nvidia card.
Mostly because of Nvidia’s dominance with CUDA, don’t stop trying to make it work though, don’t reward Nvidia for their BS lol
I’ll keep trying, but I don’t know how far I’ll get.
I am still going to build a dedicated machine for AI work, so I am not sure if I want to break my gaming rig too hard. All of that mess would be so much easier on a Linux rig with none of the windows fluff getting in the way.
That’s the opposite of the feedback I got. AMD claims to support all of the transformers library but many people report this to be a lie.
I am in no love of companies that establish de-facto monopolices, but that is indeed what NVidia has right now. Everything is built over CUDA, AMD has a lot of catch-up to do.
I have the impression that Apple chips support more things than AMD does.
There are some people making things work on AMD, and I cheer to them, but let’s not pretend it is as easy as with Nvidia. Most packages depend on cuda for gpu acceleration.
This is especially true in the research space (where 90% of this stuff is being built :)
Things might be about to change: https://www.phoronix.com/review/radeon-cuda-zluda
Can’t wait! But really, this type of things is what makes it hard for me to cheer at AMD:
I wish we had a champion of openness but in that respect AMD just looks like a worse version of NVidia. Hell, even Intel has been a better player!
That’s actually super interesting and potentially game changing! thanks!
I just got DirectML working with torch in WSL2 which was fairly painless.
I am wondering if that isn’t a better option than trying to emulate CUDA directly. Love it or hate it, Microsoft did do a fairly good job wrangling in different platforms with DirectX.
Over my dead body.
When I ran ollama on my amd GPU PC it said there was no nvidia GPU.