[ReleaseNote] Release note of v0.10.0rc1 (#2225)

### What this PR does / why we need it? Release note of v0.10.0rc1 - vLLM version: v0.10.0 - vLLM main: 8e8e0b6af1 --------- Signed-off-by: MengqingCao <cmq0113@163.com>
2025-08-07 14:46:49 +08:00
parent 58c8d4fdcd
commit 4604882a3e
10 changed files with 100 additions and 21 deletions
--- a/docs/source/user_guide/release_notes.md
+++ b/docs/source/user_guide/release_notes.md
@@ -1,5 +1,61 @@
 # Release note

+## v0.10.0rc1 - 2025.08.07
+
+This is the 1st release candidate of v0.10.0 for vLLM Ascend. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/) to get started. V0 is completely removed from this version.
+
+### Highlights
+* Disaggregate prefill works with V1 engine now. You can take a try with DeepSeek model [#950](https://github.com/vllm-project/vllm-ascend/pull/950), following this [tutorial](https://github.com/vllm-project/vllm-ascend/blob/main/examples/disaggregated_prefill_v1/README.md).
+* W4A8 quantization method is supported for dense and MoE model now. [#2060](https://github.com/vllm-project/vllm-ascend/pull/2060) [#2172](https://github.com/vllm-project/vllm-ascend/pull/2172)
+
+### Core
+* Ascend PyTorch adapter (torch_npu) has been upgraded to `2.7.1.dev20250724`. [#1562](https://github.com/vllm-project/vllm-ascend/pull/1562) And CANN hase been upgraded to `8.2.RC1`. [#1653](https://github.com/vllm-project/vllm-ascend/pull/1653) Don’t forget to update them in your environment or using the latest images.
+* vLLM Ascend works on Atlas 800I A3 now, and the image on A3 will be released from this version on. [#1582](https://github.com/vllm-project/vllm-ascend/pull/1582)
+* Kimi-K2 with w8a8 quantization, Qwen3-Coder and GLM-4.5 is supported in vLLM Ascend, please following this [tutorial](https://vllm-ascend.readthedocs.io/en/latest/tutorials/multi_node_kimi.md.html) to have a try. [#2162](https://github.com/vllm-project/vllm-ascend/pull/2162)
+* Pipeline Parallelism is supported in V1 now. [#1800](https://github.com/vllm-project/vllm-ascend/pull/1800)
+* Prefix cache feature now work with the Ascend Scheduler. [#1446](https://github.com/vllm-project/vllm-ascend/pull/1446)
+* Torchair graph mode works with tp > 4 now. [#1508](https://github.com/vllm-project/vllm-ascend/issues/1508)
+* MTP support torchair graph mode now [#2145](https://github.com/vllm-project/vllm-ascend/pull/2145)
+
+## Other
+
+* Bug fixes:
+    * Fix functional problem of multi-modality models like Qwen2-audio with Aclgraph. [#1803](https://github.com/vllm-project/vllm-ascend/pull/1803)
+    * Fix the process group creating error with external launch scenario. [#1681](https://github.com/vllm-project/vllm-ascend/pull/1681)
+    * Fix the functional problem with guided decoding. [#2022](https://github.com/vllm-project/vllm-ascend/pull/2022)
+    * Fix the accuracy issue with common MoE models in DP scenario. [#1856](https://github.com/vllm-project/vllm-ascend/pull/1856)
+* Performance improved through a lot of prs:
+    * Caching sin/cos instead of calculate it every layer. [#1890](https://github.com/vllm-project/vllm-ascend/pull/1890)
+    * Improve shared expert multi-stream parallelism [#1891](https://github.com/vllm-project/vllm-ascend/pull/1891)
+    * Implement the fusion of allreduce and matmul in prefill phase when tp is enabled. Enable this feature by setting `VLLM_ASCEND_ENABLE_MATMUL_ALLREDUCE` to `1`. [#1926](https://github.com/vllm-project/vllm-ascend/pull/1926)
+    * Optimize Quantized MoE Performance by Reducing All2All Communication. [#2195](https://github.com/vllm-project/vllm-ascend/pull/2195)
+    * Use AddRmsNormQuant ops in the custom model to optimize Qwen3's performance [#1806](https://github.com/vllm-project/vllm-ascend/pull/1806)
+    * Use multicast to avoid padding decode request to prefill size [#1555](https://github.com/vllm-project/vllm-ascend/pull/1555)
+    * The performance of LoRA has been improved. [#1884](https://github.com/vllm-project/vllm-ascend/pull/1884)
+* A batch of refactoring prs to enhance the code architecture:
+    * Torchair model runner refactor [#2205](https://github.com/vllm-project/vllm-ascend/pull/2205)
+    * Refactoring forward_context and model_runner_v1. [#1979](https://github.com/vllm-project/vllm-ascend/pull/1979)
+    * Refactor AscendMetaData Comments. [#1967](https://github.com/vllm-project/vllm-ascend/pull/1967)
+    * Refactor torchair utils. [#1892](https://github.com/vllm-project/vllm-ascend/pull/1892)
+    * Refactor torchair worker. [#1885](https://github.com/vllm-project/vllm-ascend/pull/1885)
+    * Register activation customop instead of overwrite forward_oot. [#1841](https://github.com/vllm-project/vllm-ascend/pull/1841)
+* Parameters changes:
+    * `expert_tensor_parallel_size` in `additional_config` is removed now, and the EP and TP is aligned with vLLM now. [#1681](https://github.com/vllm-project/vllm-ascend/pull/1681)
+    * Add `VLLM_ASCEND_MLA_PA` in environ variables, use this to enable mla paged attention operator for deepseek mla decode.
+    * Add `VLLM_ASCEND_ENABLE_MATMUL_ALLREDUCE` in environ variables, enable `MatmulAllReduce` fusion kernel when tensor parallel is enabled. This feature is supported in A2, and eager mode will get better performance.
+    * Add `VLLM_ASCEND_ENABLE_MOE_ALL2ALL_SEQ` in environ variables, Whether to enable moe all2all seq, this provides a basic framework on the basis of alltoall for easy expansion.
+
+* UT coverage reached 76.34% after a batch of prs followed by this rfc: [#1298](https://github.com/vllm-project/vllm-ascend/issues/1298)
+* Sequence Parallelism works for Qwen3 MoE. [#2209](https://github.com/vllm-project/vllm-ascend/issues/2209)
+* Chinese online document is added now. [#1870](https://github.com/vllm-project/vllm-ascend/issues/1870)
+
+### Known Issues
+* Aclgraph could not work with DP + EP currently, the mainly gap is the number of npu stream that Aclgraph needed to capture graph is not enough. [#2229](https://github.com/vllm-project/vllm-ascend/issues/2229)
+* There is an accuracy issue on W8A8 dynamic quantized DeepSeek with multistream enabled. This will be fixed in the next release. [#2232](https://github.com/vllm-project/vllm-ascend/issues/2232)
+* In Qwen3 MoE, SP cannot be incorporated into the Aclgraph. [#2246](https://github.com/vllm-project/vllm-ascend/issues/2246)
+* MTP not support V1 scheduler currently, will fix it in Q3. [#2254](https://github.com/vllm-project/vllm-ascend/issues/2254)
+* When running MTP with DP > 1, we need to disable metrics logger due to some issue on vLLM. [#2254](https://github.com/vllm-project/vllm-ascend/issues/2254)
+
 ## v0.9.1rc2 - 2025.08.04
 This is the 2nd release candidate of v0.9.1 for vLLM Ascend. Please follow the [official doc](https://vllm-ascend.readthedocs.io/en/v0.9.1-dev/) to get started.

--- a/docs/source/user_guide/support_matrix/supported_features.md
+++ b/docs/source/user_guide/support_matrix/supported_features.md
@@ -9,7 +9,6 @@ You can check the [support status of vLLM V1 Engine][v1_user_guide]. Below is th
 | Chunked Prefill               | 🟢 Functional  | Functional, see detail note: [Chunked Prefill][cp]                     |
 | Automatic Prefix Caching      | 🟢 Functional  | Functional, see detail note: [vllm-ascend#732][apc]                    |
 | LoRA                          | 🟢 Functional  | [vllm-ascend#396][multilora], [vllm-ascend#893][v1 multilora]          |
-| Prompt adapter                | 🔴 No plan     | This feature has been deprecated by vLLM.                              |
 | Speculative decoding          | 🟢 Functional  | Basic support                                                          |
 | Pooling                       | 🟢 Functional  | CI needed and adapting more models; V1 support rely on vLLM support.   |
 | Enc-dec                       | 🟡 Planned     | vLLM should support this feature first.                                |
@@ -17,15 +16,13 @@ You can check the [support status of vLLM V1 Engine][v1_user_guide]. Below is th
 | LogProbs                      | 🟢 Functional  | CI needed                                                              |
 | Prompt logProbs               | 🟢 Functional  | CI needed                                                              |
 | Async output                  | 🟢 Functional  | CI needed                                                              |
-| Multi step scheduler          | 🔴 Deprecated  | [vllm#8779][v1_rfc], replaced by [vLLM V1 Scheduler][v1_scheduler]     |
-| Best of                       | 🔴 Deprecated  | [vllm#13361][best_of]                                                  |
 | Beam search                   | 🟢 Functional  | CI needed                                                              |
 | Guided Decoding               | 🟢 Functional  | [vllm-ascend#177][guided_decoding]                                     |
 | Tensor Parallel               | 🟢 Functional  | Make TP >4 work with graph mode                                        |
 | Pipeline Parallel             | 🟢 Functional  | Write official guide and tutorial.                                     |
 | Expert Parallel               | 🟢 Functional  | Dynamic EPLB support.                                                  |
 | Data Parallel                 | 🟢 Functional  | Data Parallel support for Qwen3 MoE.                                   |
-| Prefill Decode Disaggregation | 🚧 WIP         | working on [1P1D] and xPyD.                                            |
+| Prefill Decode Disaggregation | 🟢 Functional  | Functional, xPyD is supported.                                         |
 | Quantization                  | 🟢 Functional  | W8A8 available; working on more quantization method support(W4A8, etc) |
 | Graph Mode                    | 🔵 Experimental| Experimental, see detail note: [vllm-ascend#767][graph_mode]           |
 | Sleep Mode                    | 🟢 Functional  |                                                                        |
@@ -38,10 +35,7 @@ You can check the [support status of vLLM V1 Engine][v1_user_guide]. Below is th

 [v1_user_guide]: https://docs.vllm.ai/en/latest/getting_started/v1_user_guide.html
 [multimodal]: https://vllm-ascend.readthedocs.io/en/latest/tutorials/single_npu_multimodal.html
-[best_of]: https://github.com/vllm-project/vllm/issues/13361
 [guided_decoding]: https://github.com/vllm-project/vllm-ascend/issues/177
-[v1_scheduler]: https://github.com/vllm-project/vllm/blob/main/vllm/v1/core/sched/scheduler.py
-[v1_rfc]: https://github.com/vllm-project/vllm/issues/8779
 [multilora]: https://github.com/vllm-project/vllm-ascend/issues/396
 [v1 multilora]: https://github.com/vllm-project/vllm-ascend/pull/893
 [graph_mode]: https://github.com/vllm-project/vllm-ascend/issues/767