Ryzen Limitations and recommended settings

6.4.4 release#

Note
ROCm 6.4.4 is a preview release, meaning that stability and performance are not yet optimized. Furthermore, only Pytorch is currently available on Windows - the rest of the ROCm stack is only supported on Linux.
AMD is aware and actively working on resolving these issues for future releases.

Linux#

Known issues#

  • Intermittent script failure may be observed while running Stable Diffusion inference workloads while suspending the system on AMD Ryzen™AI Max 300 series processors.

  • Intermittent script failure may be observed while running text-to-image inference workloads with PyTorch.

Windows#

Note
If you encounter errors related to missing .dll libraries, install Visual C++ 2015-2022 Redistributables.

Known issues#

  • If you encounter an error relating to Application Control Policy blocking DLL loading, check that Smart App Control is OFF. Note that to re-enable Smart App Control, you will need to reinstall windows. A future release will fix this requirement.

  • Intermittent script failure due to out-of-memory error may be observed while running inference workloads with PyTorch on Windows on Ryzen™ AI Max 300 series processors.

  • Intermittent application crash or driver timeout may be observed while running inference workloads with PyTorch on Windows while also running other applications (such as games or web browsers).

  • Failure to launch may be observed after installation while running ComfyUI with Smart App Control enabled.

Limitations#

  • No backward pass support (essential for ML training).

  • Only Python 3.12 is supported.

  • Only Pytorch is supported, not the entire ROCm stack.

  • The latest version of transformers should be installed, via pip install. Some older versions of transformers (<4.55.5) might not be supported.

  • The torch.distributed module is currently not supported. Some functions from diffusers and accelerate module may get affected.

  • On Linux, if you get an error regarding convolutions while running Generative AI workloads, setting this environment variable to 1 may help: MIOPEN_DEBUG_CONV_DIRECT_NAIVE_CONV_FWD

  • On Windows, only LLM batch sizes of 1 are officially supported.

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