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Out of interest, when did you try this? I just set up pytorch on a machine the other day and while I don't own an AMD GPU I saw that they offer a ROCm version

Out of interest, when did you try this? I just set up pytorch on a machine the other day and while I don't own an AMD GPU I saw that they offer a ROCm version on their "getting started" page [1] and it doesn't seem to be more difficult than the other options. I could imagine if you run other frameworks, or if you compile custom (c++) modules for pytorch then it could be an issue, but frankly that has been becoming exceedingly rare (at least for me). Would love to hear your or anyone's experiences since I, like the sibling comment, don't want to shove any more money to nvidia. [1]: https://pytorch.org/get-started/locally/ https://pytorch.org/get-started/locally/

krastanov 4y ago
ROCm (AMD's answer to CUDA) is already pretty great on supported GPUs. For me the problem at this point is that not many of their consumer GPUs have "official" support for it (although unofficially things are a bit better).
homarp 4y ago
installing ROCm is bit of a pain (there is little packaging, so you have to rebuild it yourself, and like fellow comment is saying, support is uncertain (and it does _not_ work on APU)) Search who's running Stable Diffusion on Nvidia and who's running on AMD: if you are using AMD, you are kind of on your own. Finally, you have model with custom CUDA code (e.g. https://github.com/sniklaus/3d-ken-burns https://github.com/sniklaus/3d-ken-burns )
- mey 4y ago
  Just tried to setup Stable Diffusion tonight on Windows/AMD tonight. ROCm doesn't support Windows. Pytorch doesn't support OpenCL. WSL2 can't plug into HIP even through it's apparently hiding in Windows somewhere. Nvidia would in theory just work. Granted AMD supports SR-IOV in it's consumer GPUs, so when I have a moment, I may setup a full Hyper-V VM and pass thru the GPU. Lastly, most AI researchers simply assume you are running CUDA, and don't develop around portability.
  - terafo 4y ago
    There is DirectML build of Pytorch that should work on AMD.
  - dogma1138 4y ago
    AMD doesn’t support SR-IOV on consumer GPUs, you can do only VFIO passthrough. Open source SR-IOV support used to be accessible via GIM but there only supported GPUs upto Tonga and the closest you had for a consumer GPU was the W series of workstation cards.

krastanov 4y ago

ROCm (AMD's answer to CUDA) is already pretty great on supported GPUs. For me the problem at this point is that not many of their consumer GPUs have "official" support for it (although unofficially things are a bit better).

homarp 4y ago

installing ROCm is bit of a pain (there is little packaging, so you have to rebuild it yourself, and like fellow comment is saying, support is uncertain (and it does _not_ work on APU)) Search who's running Stable Diffusion on Nvidia and who's running on AMD: if you are using AMD, you are kind of on your own. Finally, you have model with custom CUDA code (e.g. https://github.com/sniklaus/3d-ken-burns https://github.com/sniklaus/3d-ken-burns )

mey 4y ago
Just tried to setup Stable Diffusion tonight on Windows/AMD tonight. ROCm doesn't support Windows. Pytorch doesn't support OpenCL. WSL2 can't plug into HIP even through it's apparently hiding in Windows somewhere. Nvidia would in theory just work. Granted AMD supports SR-IOV in it's consumer GPUs, so when I have a moment, I may setup a full Hyper-V VM and pass thru the GPU. Lastly, most AI researchers simply assume you are running CUDA, and don't develop around portability.
- terafo 4y ago
  There is DirectML build of Pytorch that should work on AMD.
- dogma1138 4y ago
  AMD doesn’t support SR-IOV on consumer GPUs, you can do only VFIO passthrough. Open source SR-IOV support used to be accessible via GIM but there only supported GPUs upto Tonga and the closest you had for a consumer GPU was the W series of workstation cards.