vLLM-Omni + MindIE-SD (Ubuntu)

Quick Reference

Item	Value
Image	mindiesd
Tags	v3.0.0-A2-ubuntu22.04-py3.11-aarch64
	v3.0.0-A3-ubuntu22.04-py3.11-aarch64
Base Images	A2: quay.io/ascend/vllm-omni:v0.20.0
	A3: quay.io/ascend/vllm-omni:v0.20.0-a3
Architecture	linux/arm64 (aarch64)
OS	Ubuntu 22.04
Python	3.11
CANN	8.5.1
License	Mulan PSL v2

Image Overview

This image combines vLLM-Omni and MindIE-SD (Mind Inference Engine Stable Diffusion) into a single container, enabling both multi-modal LLM inference and Stable Diffusion image generation on Ascend NPUs.

It is built on top of the quay.io/ascend/vllm-omni base image (which includes CANN 8.5.1, torch, torch_npu, vllm, and vllm_ascend). Two variants are provided for different NPU series:

• A2: based on quay.io/ascend/vllm-omni:v0.20.0, for Ascend A2 series NPUs
• A3: based on quay.io/ascend/vllm-omni:v0.20.0-a3, for Ascend A3 series NPUs

Both variants add the following Ascend tuning and debugging tools:

Component	Version	Description
mindiesd	latest	MindIE Stable Diffusion inference engine
msprobe	0.1.4	Precision debugging tool
msmodelslim	8.2.1	Model compression and quantization tool
msprof-analyze	26.0.0	MindStudio Profiler analysis tool
msprof	(bundled with CANN)	NPU profiling tool

Image Tags & Dockerfile Path

Tag Naming Convention

{version}-cann{cann_version}-{series}-{os}-py{python_version}-{architecture}

Series	Example Tag	Base Image
A2	v3.0.0-A2-ubuntu22.04-py3.11-aarch64	quay.io/ascend/vllm-omni:v0.20.0
A3	v3.0.0-A3-ubuntu22.04-py3.11-aarch64	quay.io/ascend/vllm-omni:v0.20.0-a3

Dockerfile Path

The Dockerfiles are archived in the MindIE-SD source repository at:

docker/omni/Dockerfile.a2.ubuntu   # A2 series
docker/omni/Dockerfile.a3.ubuntu   # A3 series

Quick Start

Pull Base Image

Browse all available tags at quay.io/ascend/vllm-omni.

A2:

docker pull quay.io/ascend/vllm-omni:v0.20.0

A3:

docker pull quay.io/ascend/vllm-omni:v0.20.0-a3

Tip: You can also use podman pull in place of docker pull if you prefer Podman as your container runtime.

Run the Container

A2:

docker run -it --rm --name=mindiesd \
    --privileged \
    --shm-size=1g \
    --device /dev/davinci0 \
    --device /dev/davinci1 \
    --device /dev/davinci2 \
    --device /dev/davinci3 \
    --device /dev/davinci_manager \
    --device /dev/devmm_svm \
    --device /dev/hisi_hdc \
    -v /usr/local/dcmi:/usr/local/dcmi \
    -v /usr/local/bin/npu-smi:/usr/local/bin/npu-smi \
    -v /usr/local/Ascend/driver/lib64/:/usr/local/Ascend/driver/lib64/ \
    -v /usr/local/Ascend/driver/version.info:/usr/local/Ascend/driver/version.info \
    -v /etc/ascend_install.info:/etc/ascend_install.info \
    -v /root/.cache:/root/.cache \
    mindiesd:v3.0.0-A2-ubuntu22.04-py3.11-aarch64 \
    bash

A3:

docker run -it --rm --name=mindiesd \
    --privileged \
    --shm-size=1g \
    --device /dev/davinci0 \
    --device /dev/davinci1 \
    --device /dev/davinci2 \
    --device /dev/davinci3 \
    --device /dev/davinci_manager \
    --device /dev/devmm_svm \
    --device /dev/hisi_hdc \
    -v /usr/local/dcmi:/usr/local/dcmi \
    -v /usr/local/bin/npu-smi:/usr/local/bin/npu-smi \
    -v /usr/local/Ascend/driver/lib64/:/usr/local/Ascend/driver/lib64/ \
    -v /usr/local/Ascend/driver/version.info:/usr/local/Ascend/driver/version.info \
    -v /etc/ascend_install.info:/etc/ascend_install.info \
    -v /root/.cache:/root/.cache \
    mindiesd:v3.0.0-A3-ubuntu22.04-py3.11-aarch64 \
    bash

Note: The --privileged flag and device mappings are required for NPU access. The host must mount driver libraries (/usr/local/Ascend/driver/lib64), driver version info, DCMI, npu-smi, and Ascend install info into the container.

Build Locally

Clone the MindIE-SD repository and build from the docker/omni directory:

A2:

git clone https://github.com/Ascend/MindIE-SD.git
cd MindIE-SD/docker/omni

docker build -t mindiesd:v3.0.0-A2-ubuntu22.04-py3.11-aarch64 \
    -f Dockerfile.a2.ubuntu .

A3:

git clone https://github.com/Ascend/MindIE-SD.git
cd MindIE-SD/docker/omni

docker build -t mindiesd:v3.0.0-A3-ubuntu22.04-py3.11-aarch64 \
    -f Dockerfile.a3.ubuntu .

Customize (Secondary Development)

To add your own dependencies or application code, create a new Dockerfile based on this image:

FROM mindiesd:v3.0.0-A2-ubuntu22.04-py3.11-aarch64

# Add your custom packages
RUN pip install --no-cache-dir your-package

# Copy your application
COPY ./your-app /workspace/your-app
WORKDIR /workspace/your-app

Hardware Support

Item	Requirement
NPU	Ascend A2 series (e.g., Atlas 300I Duo, Atlas A2 training series)
	Ascend A3 series
Driver	Ascend NPU driver must be installed on the host
Host Mounts	/usr/local/dcmi, /usr/local/bin/npu-smi, /usr/local/Ascend/driver/lib64/, /usr/local/Ascend/driver/version.info, /etc/ascend_install.info, /root/.cache

Compatibility Changes

Refer to the MindIE-SD documentation for the latest release notes and compatibility information.

License & Disclaimer

This image is licensed under the Mulan Permissive Software License, Version 2 (Mulan PSL v2). See the LICENSE file for the full text.

By pulling and using this container image, you accept the terms and conditions of the Huawei Container License Agreement. A copy of the license is available at: https://www.hiascend.com/en/legal/ascendhub-download

You agree and undertake that when using Huawei or third-party software in this image, you will comply with the license agreement of the corresponding Huawei or third-party software.