Yikun Jiang e63fc6f280 Init vLLM Ascend maintainers info (#1124)
### What this PR does / why we need it?
As plus of https://github.com/vllm-project/vllm-ascend/pull/1070, this
patch adds `Nominating and Removing Maintainers` section (reference some
design from [PyTorch
Governance](https://docs.pytorch.org/docs/stable/community/governance.html))

Below are key info about existing maintainers:

## @wangxiyuan: 
- Super active code and high quality reviewer [450+ PR
reviewed](https://github.com/vllm-project/vllm-ascend/pulls?q=commenter%3Awangxiyuan).
- One of the top contributors, he also active contribute [50+ commits
](https://github.com/vllm-project/vllm-ascend/pulls?q=is%3Apr+is%3Aclosed+review%3Aapproved+author%3Awangxiyuan+)
with good quality, he dares to [refactor the
code](https://github.com/vllm-project/vllm-ascend/pulls?q=is%3Apr+author%3Awangxiyuan+is%3Aclosed+refactor),
which also shows his deep understanding of vllm and vllm ascend.
- He leads the [[RFC]: Hardware
pluggable](https://github.com/vllm-project/vllm/issues/11162) feature,
this make vllm-ascend project become true.
- Active community involved cross wechat group, slack, github issue.
Involved on [150+
issue](https://github.com/vllm-project/vllm-ascend/issues?q=is%3Aissue%20state%3Aopen%20commenter%3Awangxiyuan)
and help users. He is also the spearker of vLLM Beijing meetup help more
users understand vLLM Ascend.
- Relase manager of
[v0.7.1rc1](https://github.com/vllm-project/vllm-ascend/releases/tag/v0.7.1rc1),
[v0.7.3rc1](https://github.com/vllm-project/vllm-ascend/releases/tag/v0.7.3rc1),
[v0.7.3rc2](https://github.com/vllm-project/vllm-ascend/releases/tag/v0.7.3rc2),
[v0.8.4rc1](https://github.com/vllm-project/vllm-ascend/releases/tag/v0.8.4rc1),
[v0.7.3.post1](https://github.com/vllm-project/vllm-ascend/releases/tag/v0.7.3.post1).

## @Yikun: 
- High active code reviewer: [190+ PR
reviewed](https://github.com/vllm-project/vllm-ascend/pulls?q=commenter%3AYikun),
especially for new developers to help them onboarding.
- One of the top contributors with sustained contributions: [50+
commits](https://github.com/vllm-project/vllm-ascend/pulls?q=is%3Apr+is%3Aclosed+review%3Aapproved+author%3AYikun+)
since the first day of vLLM Ascend.
- High quality contributions around vLLM compatibility guarantee and
also maintain [CI
](https://github.com/vllm-project/vllm-ascend/pull/1040) and [test
Framework](https://github.com/vllm-project/vllm-ascend/pull/730).
- Active community involved cross local group, github issue Involved on
[170+
issue](https://github.com/vllm-project/vllm-ascend/issues?q=is%3Aissue%20state%3Aopen%20commenter%3AYikun).
He is also main organizer of vLLM Beijing Meetup and speaker of [PyTorch
Day China
2025](https://pytorchdaychina2025.sched.com/event/2401V/poster-session)
to help vLLM Ascend growth.
- Relase manager of
[v0.8.4rc2](https://github.com/vllm-project/vllm-ascend/releases/tag/v0.8.4rc2),
[v0.8.5rc1](https://github.com/vllm-project/vllm-ascend/releases/tag/v0.8.5rc1),
[v0.7.3](https://github.com/vllm-project/vllm-ascend/releases/tag/v0.7.3).

## @ganyi1996ppo 
- High active code and high quality reviewer: [90+ PR
reviewed](https://github.com/vllm-project/vllm-ascend/pulls?q=commenter%3Aganyi1996ppo),
he has a deep understanding of Ascend operators can always find some key
issues, has deeply understand of the codebase, good code quality and
qualified judgement.
- Major and high quality contributions: [10+
commits](https://github.com/vllm-project/vllm-ascend/pulls?q=is%3Apr+is%3Aclosed+review%3Aapproved+author%3Aganyi1996ppo)
with high quality.
- He is the main contributor of [Custom AscendC op
support](https://github.com/vllm-project/vllm-ascend/pull/371),
[Deepseekv3 performance
optimization](https://github.com/vllm-project/vllm-ascend/pull/598).
- Community Involvement‌: Involved on [11+ issue and help
users](https://github.com/vllm-project/vllm-ascend/issues?q=is%3Aissue%20state%3Aopen%20commenter%3Aganyi1996ppo),
share [custom ops
topic](https://www.bilibili.com/video/BV1Z25az3EqS/?share_source=copy_web&vd_source=72ef9c665af5f2f1370abe26ce1f719f&t=1342)
on vLLM Ascend Weekly meeting.


### Does this PR introduce _any_ user-facing change?
No

### How was this patch tested?
Preview

Signed-off-by: Yikun Jiang <yikunkero@gmail.com>
2025-06-09 16:32:58 +08:00
2025-02-05 10:53:12 +08:00
2025-05-28 21:18:41 +08:00
2025-05-28 06:31:35 +08:00
2025-01-29 02:44:13 -08:00
2025-04-01 09:25:33 +08:00

vllm-ascend

vLLM Ascend Plugin

| About Ascend | Documentation | #sig-ascend | Users Forum | Weekly Meeting |

English | 中文


Latest News 🔥


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
  • OS: Linux
  • Software:
    • Python >= 3.9, < 3.12
    • CANN >= 8.1.RC1
    • PyTorch >= 2.5.1, torch-npu >= 2.5.1
    • vLLM (the same version as vllm-ascend)

Getting Started

Please refer to 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:

Branch

vllm-ascend has main branch and dev branch.

  • main: main branchcorresponds 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-dev is the dev branch for vLLM v0.7.3 version.

Below is maintained branches:

Branch Status Note
main Maintained CI commitment for vLLM main branch and vLLM 0.9.x branch
v0.7.1-dev Unmaintained Only doc fixed is allowed
v0.7.3-dev Maintained CI commitment for vLLM 0.7.3 version

Please refer to Versioning policy for more details.

Weekly Meeting

License

Apache License 2.0, as found in the LICENSE file.

Description
XC-LLM: A Specially Optimized LLM Inference Engine for ModelHub XC
Readme Apache-2.0 8.6 MiB
Languages
Python 66.8%
C++ 31.8%
Shell 1%
CMake 0.2%
Dockerfile 0.1%
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