There are three submissions for running stable diffusion on amd: https://hn.algolia.com/?q=amd+stable+diffusion https://hn.algolia.com/?q=amd+stable+diffusion

There are three submissions for running stable diffusion on amd: https://hn.algolia.com/?q=amd+stable+diffusion https://hn.algolia.com/?q=amd+stable+diffusion All in all HIP is pretty decent, from what I understand. There's just a lot a lot a lot of algorithms CUDA & associate also-on-metal add-on libraries have & it's hard to have great coverage. AMD keeps adding more. With Intel also trying to get into GPUs I feel like there's more chance something longer term viable & open emerges, whereas it's been AMD with their compatibility tooling fighting this war alone for a long time. Sounds like GPUFORT is out but I dont think it's very relavant... > Most of those efforts to date have been focused on C/C++ code while GPUFORT is about taking CUDA-focused Fortran code and adapting it for Radeon GPU execution. GPUFORT supports the source-to-source translation of CUDA Fortran and OpenACC-based Fortran code over to OpenMP 4.5+ for GPU execution or Fortran + HIP C++ code. Longer term, it should matter less. More and more machine learning platforms will target Vulkan or other generic acceleration frameworks. Developers wont target CUDA directly forever- they increasingly do & increasingly will use good ML frameworks. Everyone but bad guy Nvidia at least will harken increasingly in that direction.