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Bump v0.9.1rc1 release (#1349)

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### What this PR does / why we need it?
Bump v0.9.1rc1 release

Closes: https://github.com/vllm-project/vllm-ascend/pull/1341
Closes: https://github.com/vllm-project/vllm-ascend/pull/1334

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

### How was this patch tested?
CI passed


---------

Signed-off-by: Shanshan Shen <87969357+shen-shanshan@users.noreply.github.com>
Signed-off-by: Yikun Jiang <yikunkero@gmail.com>
Signed-off-by: leo-pony <nengjunma@outlook.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
Co-authored-by: leo-pony <nengjunma@outlook.com>
Co-authored-by: shen-shanshan <467638484@qq.com>
This commit is contained in:
Yikun Jiang
2025-06-22 13:15:36 +08:00
committed by GitHub
parent 097e7149f7
commit c30ddb8331
9 changed files with 474 additions and 13 deletions
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8
docs/source/user_guide/graph_mode.md
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@@ -7,11 +7,11 @@ This guide provides instructions for using Ascend Graph Mode with vLLM Ascend. P
## Getting Started
From v0.9.0rc1 with V1 Engine, vLLM Ascend will run models in graph mode by default to keep the same behavior with vLLM. If you hit any issues, please feel free to open an issue on GitHub and fallback to eager mode temporarily by set `enforce_eager=True` when initializing the model.
From v0.9.1rc1 with V1 Engine, vLLM Ascend will run models in graph mode by default to keep the same behavior with vLLM. If you hit any issues, please feel free to open an issue on GitHub and fallback to eager mode temporarily by set `enforce_eager=True` when initializing the model.
There are two kinds for graph mode supported by vLLM Ascend:
- **ACLGraph**: This is the default graph mode supported by vLLM Ascend. In v0.9.0rc1, only Qwen series models are well tested.
- **TorchAirGraph**: This is the GE graph mode. In v0.9.0rc1, only DeepSeek series models are supported.
- **ACLGraph**: This is the default graph mode supported by vLLM Ascend. In v0.9.1rc1, only Qwen series models are well tested.
- **TorchAirGraph**: This is the GE graph mode. In v0.9.1rc1, only DeepSeek series models are supported.
## Using ACLGraph
ACLGraph is enabled by default. Take Qwen series models as an example, just set to use V1 Engine is enough.
@@ -55,7 +55,7 @@ outputs = model.generate("Hello, how are you?")
online example:
```shell
vllm serve Qwen/Qwen2-7B-Instruct --additional-config='{"torchair_graph_config": {"enabled": True},"ascend_scheduler_config": {"enabled": True,}}'
vllm serve Qwen/Qwen2-7B-Instruct --additional-config='{"torchair_graph_config": {"enabled": true},"ascend_scheduler_config": {"enabled": true,}}'
```
You can find more detail about additional config [here](./additional_config.md)

41
docs/source/user_guide/release_notes.md
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@@ -1,5 +1,44 @@
# Release note
## v0.9.1rc1 - 2025.06.22
This is the 1st release candidate of v0.9.1 for vLLM Ascend. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/) to get started.
### Highlights
- Atlas 300I series is experimental supported in this release. [#1333](https://github.com/vllm-project/vllm-ascend/pull/1333) After careful consideration, this feature **will NOT be included in v0.9.1-dev branch** taking into account the v0.9.1 release quality and the feature rapid iteration to improve performance on Atlas 300I series. We will improve this from 0.9.2rc1 and later.
- Support EAGLE-3 for speculative decoding. [#1032](https://github.com/vllm-project/vllm-ascend/pull/1032)
### Model
- MoGE model is now supported. You can try with Pangu Pro Moe-72B on Atlas A2 series and Atlas 300I series. Please follow the official [tutorials](https://vllm-ascend.readthedocs.io/en/latest/tutorials/multi_npu_moge.html) and [300I series tutorials](https://vllm-ascend.readthedocs.io/en/latest/tutorials/single_node_300i.html). [#1204](https://github.com/vllm-project/vllm-ascend/pull/1204)
### Core
- Ascend PyTorch adapter (torch_npu) has been upgraded to `2.5.1.post1.dev20250528`. Don’t forget to update it in your environment. [#1235](https://github.com/vllm-project/vllm-ascend/pull/1235)
- Support Atlas 300I series container image. You can get it from [quay.io](https://quay.io/repository/vllm/vllm-ascend)
- Fix token-wise padding mechanism to make multi-card graph mode work. [#1300](https://github.com/vllm-project/vllm-ascend/pull/1300)
- Upgrade vllm to 0.9.1 [#1165]https://github.com/vllm-project/vllm-ascend/pull/1165
### Other Improvements
- Initial support Chunked Prefill for MLA. [#1172](https://github.com/vllm-project/vllm-ascend/pull/1172)
- An example of best practices to run DeepSeek with ETP has been added. [#1101](https://github.com/vllm-project/vllm-ascend/pull/1101)
- Performance improvements for DeepSeek using the TorchAir graph. [#1098](https://github.com/vllm-project/vllm-ascend/pull/1098), [#1131](https://github.com/vllm-project/vllm-ascend/pull/1131)
- Supports the speculative decoding feature with AscendScheduler. [#943](https://github.com/vllm-project/vllm-ascend/pull/943)
- Improve `VocabParallelEmbedding` custom op performance. It will be enabled in the next release. [#796](https://github.com/vllm-project/vllm-ascend/pull/796)
- Fixed a device discovery and setup bug when running vLLM Ascend on Ray [#884](https://github.com/vllm-project/vllm-ascend/pull/884)
- DeepSeek with [MC2](https://www.hiascend.com/document/detail/zh/canncommercial/81RC1/developmentguide/opdevg/ascendcbestP/atlas_ascendc_best_practices_10_0043.html) (Merged Compute and Communication) now works properly. [#1268](https://github.com/vllm-project/vllm-ascend/pull/1268)
- Fixed log2phy NoneType bug with static EPLB feature. [#1186](https://github.com/vllm-project/vllm-ascend/pull/1186)
- Improved performance for DeepSeek with DBO enabled. [#997](https://github.com/vllm-project/vllm-ascend/pull/997), [#1135](https://github.com/vllm-project/vllm-ascend/pull/1135)
- Refactoring AscendFusedMoE [#1229](https://github.com/vllm-project/vllm-ascend/pull/1229)
- Add initial user stories page (include LLaMA-Factory/TRL/verl/MindIE Turbo/GPUStack) [#1224](https://github.com/vllm-project/vllm-ascend/pull/1224)
- Add unit test framework [#1201](https://github.com/vllm-project/vllm-ascend/pull/1201)
### Known Issues
- In some cases, the vLLM process may crash with a **GatherV3** error when **aclgraph** is enabled. We are working on this issue and will fix it in the next release. [#1038](https://github.com/vllm-project/vllm-ascend/issues/1038)
- Prefix cache feature does not work with the Ascend Scheduler but without chunked prefill enabled. This will be fixed in the next release. [#1350](https://github.com/vllm-project/vllm-ascend/issues/1350)
### Full Changelog
https://github.com/vllm-project/vllm-ascend/compare/v0.9.0rc2...v0.9.1rc1
## v0.9.0rc2 - 2025.06.10
This release contains some quick fixes for v0.9.0rc1. Please use this release instead of v0.9.0rc1.
@@ -21,7 +60,7 @@ This is the 1st release candidate of v0.9.0 for vllm-ascend. Please follow the [
- The performance of multi-step scheduler has been improved. Thanks for the contribution from China Merchants Bank. [#814](https://github.com/vllm-project/vllm-ascend/pull/814)
- LoRA、Multi-LoRA And Dynamic Serving is supported for V1 Engine now. Thanks for the contribution from China Merchants Bank. [#893](https://github.com/vllm-project/vllm-ascend/pull/893)
- prefix cache and chunked prefill feature works now [#782](https://github.com/vllm-project/vllm-ascend/pull/782) [#844](https://github.com/vllm-project/vllm-ascend/pull/844)
- Prefix cache and chunked prefill feature works now [#782](https://github.com/vllm-project/vllm-ascend/pull/782) [#844](https://github.com/vllm-project/vllm-ascend/pull/844)
- Spec decode and MTP features work with V1 Engine now. [#874](https://github.com/vllm-project/vllm-ascend/pull/874) [#890](https://github.com/vllm-project/vllm-ascend/pull/890)
- DP feature works with DeepSeek now. [#1012](https://github.com/vllm-project/vllm-ascend/pull/1012)
- Input embedding feature works with V0 Engine now. [#916](https://github.com/vllm-project/vllm-ascend/pull/916)