# AMD ROCm

To use **AMD ROCm** with **SD.Next**:
1. Install ROCm libraries.
2. Run SD.Next with `--use-rocm` so it installs a compatible `torch` build.

> [!IMPORTANT]  
> AMD ROCm is officially supported for specific AMD GPUs.  
>
> [!IMPORTANT]  
> Currently, PyTorch support on Windows is not officially maintained by PyTorch team.  
> See [AMD's announcement](https://www.amd.com/en/resources/support-articles/release-notes/RN-AMDGPU-WINDOWS-PYTORCH-PREVIEW.html) for more information.  
>
> [!WARNING]  
> Unofficial support for other platforms is provided by the community and **SD.Next** does not guarantee it will work.  
> Use of any third-party libraries is at your own risk.  

- For preview support on Windows platform, see [ROCm on Windows](#rocm-on-windows) section.  
- For unofficial support for Windows platform, see [ZLUDA](https://github.com/vladmandic/sdnext/wiki/ZLUDA) page.  

## ROCm on Linux

### Install Guide for Ubuntu 24.04

Install ROCm:

```shell
sudo apt update
wget https://repo.radeon.com/amdgpu-install/6.4.3/ubuntu/noble/amdgpu-install_6.4.60403-1_all.deb
sudo apt install ./amdgpu-install_6.4.60403-1_all.deb
sudo amdgpu-install --usecase=rocm
sudo usermod -a -G render,video $LOGNAME
```

Install git and python:

```shell
sudo apt install git python3 python3-dev python3-venv python3-pip
```

### Install Guide for Ubuntu 22.04  

Simply change the wget line from "noble" to "jammy" if using Ubuntu 22.04.  

### Install Guide for openSUSE Tumbleweed

Install prerequisites:

```shell
sudo zypper in python312-devel python312-virtualenv python312-pip patterns-devel-base-devel_basis
```

Add the [ROCm repository](https://build.opensuse.org/project/show/science:GPU:ROCm) (not official, but maintained by AMD employees):

```shell
sudo zypper ar obs://science:GPU:ROCm/openSUSE_Factory ROCm
sudo zypper ref # Answer "ultimately trust"
```

Install the relevant packages (there is no pattern so you must install them all manually):

```shell
sudo zypper in rocm-runtime \
    miopen rccl rocblas amdsmi \
    hipblaslt hiprand hipcub \
    hipsolver hipfft rocm-cmake \
    rocm-compilersupport \
    rocm-llvm-filesystem \
    rocm-clang-runtime-devel \
    hipcub-devel rocm-hip-devel \
    libhipfft0-devel libhipsolver0-devel \
    libhipsparse1-devel rocthrust-devel \
    librocfft0 rocm-core rocrand rocsolver 
  ```

This procedure should also work for Leap-based distributions and Slowroll (adjust the distro-specific lines), but it is not tested.

**Note**: This also installs build dependencies for flash-attention.

### Install Guide for Arch Linux

Install ROCm and git:  

```shell
sudo pacman -S rocm-hip-runtime git
```

Install Python 3.12 (or anything between 3.10 and 3.13):  

```shell
sudo pacman -S base-devel python-pip python-virtualenv
git clone https://aur.archlinux.org/python312.git
cd python312
makepkg -si
cd ..
export PYTHON=python3.12

# remove the package builder residuals:
# rm -rf python312
```

Install ROCm SDK:  
> [!NOTE]
> ROCm SDK is optional. It is only required for building flash attention or similar custom kernels.  
> ROCm SDK uses 26 GB of disk space.  

```shell
sudo pacman -S rocm-hip-sdk libxml2-legacy gcc14 gcc14-libs
```

## Running SD.Next with ROCm locally

Open a terminal in the folder where you want to install SD.Next, then run:  

```shell
git clone https://github.com/vladmandic/sdnext
```bash

Then enter the `sdnext` folder:  

```shell
cd sdnext
```

Run SD.Next with:  

```shell
./webui.sh --use-rocm
```

> [!NOTE]
> It will install the necessary libraries at the first run so it will take a while depending on your internet.  

## Running SD.Next with Docker for ROCm  

See [Docker](https://github.com/vladmandic/sdnext/wiki/Docker) if you want to build a custom image.  

> [!NOTE]
> Installing ROCm on your system is not required when using Docker as Docker has no access to it anyway.  

To run a prebuilt Docker image:  

```shell
export SDNEXT_DOCKER_ROOT_FOLDER=~/sdnext
sudo docker run -it \
  --name sdnext-rocm \
  --device /dev/dri \
  --device /dev/kfd \
  -p 7860:7860 \
  -v $SDNEXT_DOCKER_ROOT_FOLDER/app:/app \
  -v $SDNEXT_DOCKER_ROOT_FOLDER/python:/mnt/python \
  -v $SDNEXT_DOCKER_ROOT_FOLDER/data:/mnt/data \
  -v $SDNEXT_DOCKER_ROOT_FOLDER/models:/mnt/models \
  -v $SDNEXT_DOCKER_ROOT_FOLDER/huggingface:/root/.cache/huggingface \
  disty0/sdnext-rocm:latest
```

> [!NOTE]
> It will install the necessary libraries at the first run so it will take a while depending on your internet.  
> Resulting docker image will use 3.2 GB disk space (uncompressed) for the docker image and 20 GB for the venv.

## ROCm performance tuning on Linux

For details, see [AMD-MIOpen Guide](AMD-MIOpen.md).

### MIOpen database tuning

On first use, on first use of a new resolution, or after a PyTorch upgrade, ROCm runs benchmarks to pick efficient kernels.  
This can make startup slow (up to 5-8 minutes), especially with high-resolution refine passes, but it usually happens once per resolution.

If startup time is the priority, set `MIOPEN_FIND_MODE=FAST`.  
If generation performance is the priority, set `MIOPEN_FIND_ENFORCE=SEARCH` and accept slower first-time startup.

### Reduce VRAM consumption

If you use `bf16` (*Settings > Compute Settings > Execution Precision > Device precision type*), which is auto-detected on RDNA3 and newer cards, VRAM usage can become very high (16+ GB) during final decode and non-latent upscaling.  
To reduce usage, set `Device precision type` to `fp16` and disable VAE upcasting in *Variational Auto Encoder > VAE upcasting*.

Using `fp16` can also improve performance.

### Composable Kernel (CK) Flash attention

On RDNA3 hardware (RX 7000 series), you can enable CK Flash Attention in *Compute Settings > Cross Attention > SDP Options* by toggling `CK Flash attention` and restarting SD.Next.  
This requires `rocm-hip-sdk`, because SD.Next downloads and compiles an additional Python package at startup.

In case you want to install it manually, activate the virtual environment then run `pip`:  

```shell
pip install --no-build-isolation git+https://github.com/Disty0/flash-attention@navi_rotary_fix
```

## ROCm on Windows

1. Install [Git](https://git-scm.com/downloads/win) and [Python 3.12](https://www.python.org/downloads/release/python-31210/).
2. Open the terminal in a folder you want to install SD.Next and install SD.Next from GitHub with this command:

```shell
git clone https://github.com/vladmandic/sdnext
```

1. Enter into the sdnext folder:

```shell
cd sdnext
```

1. Make sure that you are up to date.

```shell
git pull
```

1. Run SD.Next with this command:

```shell
./webui.bat --use-rocm
```