Jade Zheng 955411611c Nominate Mengqing Cao as vllm-ascend maintainer (#2433)
I would like to nominate Mengqing Cao (@MengqingCao
https://github.com/MengqingCao) as a maintainer, starting with my +1.

## Reason

Review Quality‌: She has completed [120+
reviews](https://github.com/vllm-project/vllm-ascend/pulls?q=is%3Apr+is%3Aclosed+commenter%3Amengqingcao+-author%3Amengqingcao)
since Feb. 2025, include
[#review-3077842852](https://github.com/vllm-project/vllm-ascend/pull/2088#pullrequestreview-3077842852),
[comment-2990074116](https://github.com/vllm-project/vllm-ascend/pull/1032#issuecomment-2990074116),
[comment-2921063723](https://github.com/vllm-project/vllm-ascend/pull/1013#issuecomment-2921063723)
high quality review.

Sustained and Quality Contributions: She has Deep understanding of
‌vLLM‌ and ‌vLLM Ascend‌ codebases and solid contributions include The
vLLM contributions and help vLLM Ascend release is the main reason I
nominated her:

- vLLM: Things worth mentioning that she completed [28+ PR
contributions](https://github.com/vllm-project/vllm/pulls?q=is%3Apr+author%3AMengqingCao+is%3Amerged+)
in vllm-project/vllm, especially for vLLM platform module to improve
vLLM mult hardware support. She is one of the important co-authors of
[vllm#8054](https://github.com/vllm-project/vllm/pull/8054) and hardware
plugin RFC, this makes vllm-ascend plugin possible.
Community Involvement: She is also very active and involved in [60+
issues](https://github.com/vllm-project/vllm-ascend/issues?q=is%3Aissue%20state%3Aclosed%20-author%3AMengqingCao%20commenter%3AMengqingCao).

So I think she's a great addition to the vLLM Ascend Maintainer team.

- **Review Quality‌:**

She has completed 120+ reviews since Feb. 2025.

https://github.com/vllm-project/vllm-ascend/pulls?q=is%3Apr+is%3Aclosed+commenter%3Amengqingcao+-author%3Amengqingcao,
include
https://github.com/vllm-project/vllm-ascend/pull/2088#pullrequestreview-3077842852,
https://github.com/vllm-project/vllm-ascend/pull/1446#issuecomment-3015166908,
https://github.com/vllm-project/vllm-ascend/pull/1032#issuecomment-2990074116,
https://github.com/vllm-project/vllm-ascend/pull/1013#issuecomment-2921063723
quality review.

- **Sustained Contributions:**

99+ PR merged in vllm-project/vllm-ascend

https://github.com/vllm-project/vllm-ascend/pulls?q=is%3Apr+author%3AMengqingCao+is%3Amerged

- **Quality Contribution‌:**

She is one of the important co-authors of
https://github.com/vllm-project/vllm/pull/8054 , this makes vllm-ascend
plugin possible.

Things worth mentioning that she complete 28+ PR contributions in
vllm-project/vllm, especially for vLLM platform module to improve vLLM
mult hardware support:

https://github.com/vllm-project/vllm/pulls?q=is%3Apr+author%3AMengqingCao+is%3Amerged+.

At 2025 Q2, She also lead the [[RFC]: E2E CI test for key
features](https://github.com/vllm-project/vllm-ascend/issues/413) and
[[RFC]: Unit test coverage
improvement](https://github.com/vllm-project/vllm-ascend/issues/1298) to
help vllm ascend improve the coverage.

Her main contributions focus on the adaptation of parallel strategies
and communicator, such as
https://github.com/vllm-project/vllm-ascend/pull/1800,
https://github.com/vllm-project/vllm-ascend/pull/1856.

These contributions are sufficient to prove she has “Deep understanding
of ‌vLLM‌ and ‌vLLM Ascend‌ codebases”

- **Community Involvement‌:**

Involved in 63+ issue reviewer
https://github.com/vllm-project/vllm-ascend/issues?q=is%3Aissue%20state%3Aclosed%20-author%3AMengqingCao%20commenter%3AMengqingCao

She led the v0.10.1 release as release manager


- vLLM version: v0.10.0
- vLLM main:
78dba404ad

Signed-off-by: Jade Zheng <zheng.shoujian@outlook.com>
2025-08-19 14:13:54 +08:00
2025-08-11 22:21:29 +08:00
2025-08-19 09:10:01 +08:00
2025-02-05 10:53:12 +08:00
2025-01-29 02:44:13 -08:00
2025-08-11 11:22:32 +08:00
2025-08-11 11:22:32 +08:00

vllm-ascend

vLLM Ascend Plugin

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

English | 中文


Latest News 🔥

  • [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
    • 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
v0.10.0rc1 Latest release candidate QuickStart and Installation for more details
v0.9.1rc2 Next stable release QuickStart and Installation for more details
v0.7.3.post1 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:

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 0.10.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, 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

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
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C++ 31.8%
Shell 1%
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Dockerfile 0.1%
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