097e7149f7
### What this PR does / why we need it? Add initial experimental support for Ascend 310P, this patch squash below PR into one to help validation: - https://github.com/vllm-project/vllm-ascend/pull/914 - https://github.com/vllm-project/vllm-ascend/pull/1318 - https://github.com/vllm-project/vllm-ascend/pull/1327 ### Does this PR introduce _any_ user-facing change? User can run vLLM on Altlas 300I DUO series ### How was this patch tested? CI passed with: - E2E image build for 310P - CI test on A2 with e2e test and longterm test - Unit test missing because need a real 310P image to have the test, will add in a separate PR later. - Manually e2e test: - Qwen2.5-7b-instruct, Qwen2.5-0.5b, Qwen3-0.6B, Qwen3-4B, Qwen3-8B: https://github.com/vllm-project/vllm-ascend/pull/914#issuecomment-2942989322 - Pangu MGoE 72B The patch has been tested locally on Ascend 310P hardware to ensure that the changes do not break existing functionality and that the new features work as intended. #### ENV information CANN, NNAL version: 8.1.RC1 > [!IMPORTANT] > PTA 2.5.1 version >= torch_npu-2.5.1.post1.dev20250528 to support NZ format and calling NNAL operators on 310P #### Code example ##### Build vllm-ascend from source code ```shell # download source code as vllm-ascend cd vllm-ascend export SOC_VERSION=Ascend310P3 pip install -v -e . cd .. ``` ##### Run offline inference ```python from vllm import LLM, SamplingParams prompts = ["水的沸点是100摄氏度吗？请回答是或者否。", "若腋下体温为38摄氏度，请问这人是否发烧？请回答是或者否。", "水的沸点是100摄氏度吗？请回答是或者否。", "若腋下体温为38摄氏度，请问这人是否发烧？请回答是或者否。"] # Create a sampling params object. sampling_params = SamplingParams(temperature=0.0, top_p=0.95, max_tokens=10) # Create an LLM. llm = LLM( model="Qwen/Qwen2.5-7B-Instruct", max_model_len=4096, max_num_seqs=4, dtype="float16", # IMPORTANT cause some ATB ops cannot support bf16 on 310P disable_custom_all_reduce=True, trust_remote_code=True, tensor_parallel_size=2, compilation_config={"custom_ops":['none', "+rms_norm", "+rotary_embedding"]}, ) # Generate texts from the prompts. outputs = llm.generate(prompts, sampling_params) for output in outputs: prompt = output.prompt generated_text = output.outputs[0].text print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}") ``` --------- Signed-off-by: Vincent Yuan <farawayboat@gmail.com> Signed-off-by: Yikun Jiang <yikunkero@gmail.com> Signed-off-by: angazenn <zengyanjia@huawei.com> Co-authored-by: Vincent Yuan <farawayboat@gmail.com> Co-authored-by: angazenn <zengyanjia@huawei.com> Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com> Co-authored-by: leo-pony <nengjunma@outlook.com> Co-authored-by: shen-shanshan <467638484@qq.com>
vLLM Ascend Plugin
| About Ascend | Documentation | #sig-ascend | Users Forum | Weekly Meeting |
English | 中文
Latest News 🔥
- [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
- OS: Linux
- Software:
- Python >= 3.9, < 3.12
- CANN >= 8.1.RC1
- PyTorch >= 2.5.1, torch-npu >= 2.5.1.post1.dev20250528
- 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:
- 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 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
- 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.