AMD support for Microsoft® DirectML optimization of Stable Diffusion

This page summarizes the projects mentioned and recommended in the original post on /r/Amd

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  • stable-diffusion-webui-directml

    Stable Diffusion web UI

    To be specific, Automatic1111 run on Linux (ROCm) or the fork for Windows DirectML use ( Some people mistakenly pull the main branch instead of the directml fork.

  • automatic

    SD.Next: Advanced Implementation of Stable Diffusion

    The Vladmandic fork of Automatic1111 (SD.Next) can do the Linux and DirectML from the same branch. Speeds being poor on DirectML's end of the problem. It is to the point that you might as well load a Linux boot and use ROCm there. All hope is on ROCm coming to Windows eventually.

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    Write Clean Python Code. Always.. Sonar helps you commit clean code every time. With over 225 unique rules to find Python bugs, code smells & vulnerabilities, Sonar finds the issues while you focus on the work.

  • Olive

    Olive is an easy-to-use hardware-aware model optimization tool that composes industry-leading techniques across model compression, optimization, and compilation. (by microsoft)

    Microsoft has provided a path in DirectML for vendors like AMD to enable optimizations called ‘metacommands’. In the case of Stable Diffusion with the Olive pipeline, AMD is building driver support for a metacommand implementation intended to improve performance and reduce the time it takes to generate output from the model. This feature will be validated on AMD RDNA™ 3 devices including AMD Radeon™ RX 7900 Series graphics cards and AMD Ryzen™ 7040 Series Mobile processors with Radeon™ graphics.

  • StableDiffusionUI

    Stable Diffusion UI: Diffusers (CUDA/ONNX)


    SHARK - High Performance Machine Learning Distribution

  • OnnxDiffusersUI

    UI for ONNX based diffusers

  • stable-diffusion-webui

    Stable Diffusion web UI

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    Collect and Analyze Billions of Data Points in Real Time. Manage all types of time series data in a single, purpose-built database. Run at any scale in any environment in the cloud, on-premises, or at the edge.

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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