eed1957f03
Added instructions for resolving 'invalid tar header' error on Kylin OS with an ARM64 architecture on Atlas300I hardware during docker
pull, including steps for offline loading of docker images.
---
### What this PR does / why we need it?
The primary motivation for this PR is to address a critical `docker
pull` failure that occurs on specific, yet important, enterprise
environments. Specifically, when operating on **Kylin OS (麒麟操作系统) with
an ARM64 architecture on Atlas300I hardware**, users frequently
encounter an `archive/tar: invalid tar header` error, which completely
blocks the setup process. This issue has been consistently reproduced,
with multiple retries failing with the same error, confirming that it is
a persistent environmental problem rather than a transient network
issue.
<img width="2060" height="525" alt="image"
src="https://github.com/user-attachments/assets/6c1c5728-de27-476f-8df4-723564fc290b"
/>
This guide provides a robust, step-by-step workaround using an
offline-loading method (`docker save` on a host machine and `docker
load` on the target machine). This solution is crucial for enabling
users on this platform to use vLLM.
This contribution does not directly fix an existing issue number, but it
proactively solves a significant environmental and usability problem for
a growing user base.
### Does this PR introduce _any_ user-facing change?
No.It does not alter any code, APIs, interfaces, or existing behavior of
the vLLM project.
### How was this patch tested?
The instructions and troubleshooting steps in this guide were validated
through a real-world, end-to-end test case on the my hardware and OS.
The testing process was as follows:
1. **Problem Reproduction**: An attempt was made to directly `docker
pull` the `vllm-ascend:v0.10.0rc1-310p` image on a target machine
running Kylin OS (ARM64). The `invalid tar header` failure was
successfully and consistently reproduced, confirming the existence of
the problem.
2. **Solution Implementation**: The workaround detailed in the guide was
executed:
* On a separate host machine (Ubuntu x86_64), the image was successfully
pulled using the `--platform linux/arm64` flag.
* The image was then saved to a `.tar` archive using `docker save`.
* The `.tar` archive was transferred to the target Kylin OS machine.
* The image was successfully loaded from the archive using `docker load
-i ...`.
3. **End-to-End Validation**: After loading the image, the vLLM
container was launched on the target machine following the instructions
in the guide. Both online inference (via `curl` to the API server) and
offline inference (via the Python script) were executed successfully,
confirming that the entire workflow described in the document is
accurate and effective.
Since this is a documentation-only change based on a validated workflow,
no new unit or integration tests were added to the codebase.
- vLLM version: v0.11.0rc3
- vLLM main:
83f478bb19
---------
Signed-off-by: Liwx <liweixuan1014@gmail.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
vLLM Ascend Plugin
| About Ascend | Documentation | #sig-ascend | Users Forum | Weekly Meeting |
English | 中文
Latest News 🔥
- [2025/09] We released the new official version v0.9.1! Please follow the official guide to start deploy large scale Expert Parallelism (EP) on Ascend.
- [2025/08] We hosted the vLLM Beijing Meetup with vLLM and Tencent! Please find the meetup slides here.
- [2025/06] User stories page is now live! It kicks off with LLaMA-Factory/verl//TRL/GPUStack to demonstrate how vLLM Ascend assists Ascend users in enhancing their experience across fine-tuning, evaluation, reinforcement learning (RL), and deployment scenarios.
- [2025/06] Contributors page is now live! All contributions deserve to be recorded, thanks for all contributors.
- [2025/05] We've released first official version v0.7.3! We collaborated with the vLLM community to publish a blog post sharing our practice: Introducing vLLM Hardware Plugin, Best Practice from Ascend NPU.
- [2025/03] We hosted the vLLM Beijing Meetup with vLLM team! Please find the meetup slides here.
- [2025/02] vLLM community officially created vllm-project/vllm-ascend repo for running vLLM seamlessly on the Ascend NPU.
- [2024/12] We are working with the vLLM community to support [RFC]: Hardware pluggable.
Overview
vLLM Ascend (vllm-ascend) is a community maintained hardware plugin for running vLLM seamlessly on the Ascend NPU.
It is the recommended approach for supporting the Ascend backend within the vLLM community. It adheres to the principles outlined in the [RFC]: Hardware pluggable, providing a hardware-pluggable interface that decouples the integration of the Ascend NPU with vLLM.
By using vLLM Ascend plugin, popular open-source models, including Transformer-like, Mixture-of-Expert, Embedding, Multi-modal LLMs can run seamlessly on the Ascend NPU.
Prerequisites
- Hardware: Atlas 800I A2 Inference series, Atlas A2 Training series, Atlas 800I A3 Inference series, Atlas A3 Training series, Atlas 300I Duo (Experimental)
- OS: Linux
- Software:
- Python >= 3.9, < 3.12
- CANN >= 8.2.rc1 (Ascend HDK version refers to here)
- PyTorch >= 2.7.1, torch-npu >= 2.7.1.dev20250724
- vLLM (the same version as vllm-ascend)
Getting Started
Please use the following recommended versions to get started quickly:
| Version | Release type | Doc |
|---|---|---|
| v0.11.0rc0 | Latest release candidate | QuickStart and Installation for more details |
| v0.9.1 | Latest stable version | QuickStart and Installation for more details |
Contributing
See CONTRIBUTING for more details, which is a step-by-step guide to help you set up development environment, build and test.
We welcome and value any contributions and collaborations:
- Please let us know if you encounter a bug by filing an issue
- Please use User forum for usage questions and help.
Branch
vllm-ascend has main branch and dev branch.
- main: main branch，corresponds to the vLLM main branch, and is continuously monitored for quality through Ascend CI.
- vX.Y.Z-dev: development branch, created with part of new releases of vLLM. For example,
v0.7.3-devis the dev branch for vLLMv0.7.3version.
Below is maintained branches:
| Branch | Status | Note |
|---|---|---|
| main | Maintained | CI commitment for vLLM main branch and vLLM v0.11.0 tag |
| v0.7.1-dev | Unmaintained | Only doc fixed is allowed |
| v0.7.3-dev | Maintained | CI commitment for vLLM 0.7.3 version, only bug fix is allowed and no new release tag any more. |
| v0.9.1-dev | Maintained | CI commitment for vLLM 0.9.1 version |
| v0.11.0-dev | Maintained | CI commitment for vLLM 0.11.0 version |
| rfc/feature-name | Maintained | Feature branches for collaboration |
Please refer to Versioning policy for more details.
Weekly Meeting
- vLLM Ascend Weekly Meeting: https://tinyurl.com/vllm-ascend-meeting
- Wednesday, 15:00 - 16:00 (UTC+8, Convert to your timezone)
License
Apache License 2.0, as found in the LICENSE file.