### What this PR does / why we need it?
This PR introduces the initial integration of **UCM (Unified Cache
Management)** into the vllm-ascend distributed KV-cache system.
Specifically, it adds:
- A new `UCMConnector` implementation under the distributed KV-transfer
framework.
- Support for offloading KV-cache blocks to external UCM backends (DRAM
/ NFS / Localdisk), depending on UCM configuration).
- Integration with vLLM V1 KV connector interface, including metadata
handling and role registration.
**Why it is needed:**
- UCM provides a unified, high-performance storage layer for KV-cache
externalization.
- This enables vllm-ascend to support out-of-core KV-cache workloads,
improve memory efficiency, and leverage hardware-accelerated storage
paths (RDMA / NFS / hybrid modes).
- This connector is a required component to allow future work on
multi-node inference + UCM-based scaling.
---
### Does this PR introduce _any_ user-facing change?
Yes, but limited:
- A new `kv_connector=UCMConnector` option becomes available through the
configuration interface.
- When selected, vllm-ascend workers may initialize UCM and offload
KV-cache blocks externally.
- No default behaviors are changed. Users must explicitly enable this
connector.
This PR does **not** modify:
- existing APIs,
- default execution paths,
- model runner behavior,
- user workflow unless `UCMConnector` is configured.
---
### How was this patch tested?
---
### Prefix Caching Benchmark
We provide preliminary measurements for TTFT (ms) under VLLM benchmark.
Tests run on 2 * Ascend 910B3, vllm-ascend 0.11.0, Tensor Parallel size
2, with UCM (Localdisk) enabled.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
Signed-off-by: UnifiedCacheManager <unifiedcachem@163.com>
### What this PR does / why we need it?
Upgrade vllm commit hash to `4429d934de3c5cc327b0d7aec8e473aeba38db90`
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: wangli <wangli858794774@gmail.com>
### What this PR does / why we need it?
Modify quantization tutorials to correct a few mistakes:
Qwen3-32B-W4A4.md and Qwen3-8B-W4A8.md
Qwen3-8B-W4A8: need to set one idle npu card.
Qwen3-32B-W4A4: need to set two idle npu cards for the flatquant
training and modify the calib_file path which does not match the
ModeSlim version.
### Does this PR introduce _any_ user-facing change?
N/A
### How was this patch tested?
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
Signed-off-by: IncSec <1790766300@qq.com>
### What this PR does / why we need it?
Supplement detailed descriptions for `ASCEND_CONNECT_TIMEOUT` and
`ASCEND_TRANSFER_TIMEOUT` in kvpool.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: LCAIZJ <leichao139636@163.com>
### What this PR does / why we need it?
This PR provides an introduction to the Qwen3-Next model, details on the
features supported by the model in the current version, the model
deployment process, as well as methods for performance testing and
accuracy testing.
With this document, the deployment and testing of the Qwen3-Next model
can be implemented more easily.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: ming1212 <2717180080@qq.com>
Signed-off-by: ming1212 <104972349+ming1212@users.noreply.github.com>
Signed-off-by: Mengqing Cao <cmq0113@163.com>
Co-authored-by: Mengqing Cao <cmq0113@163.com>
### What this PR does / why we need it?
Since the param `task` has been depprecated, we should use the latest
unified standard parameters for pooling models, this should be more
clear
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: wangli <wangli858794774@gmail.com>
### What this PR does / why we need it?
Correct more doc mistakes
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
Signed-off-by: lilinsiman <lilinsiman@gmail.com>
### What this PR does / why we need it?
Correct mistakes in doc
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: lilinsiman <lilinsiman@gmail.com>
### What this PR does / why we need it?
fix qwen2.5vl readme, del gen ranktable and add install mooncake
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
Signed-off-by: liziyu <liziyu16@huawei.com>
### What this PR does / why we need it?
Updated some issues that caused sleep mode document content to be
unavailable due to changes/outdated environment variables.
---------
Signed-off-by: wangli <wangli858794774@gmail.com>
### What this PR does / why we need it?
doc tutorials add model feature matrix：
DeepSeekR1
DeepSeekV3.1
Qwen3-Dense
Qwen3-Moe
Qwen3-Next
Qwen2.5
Qwen2.5-VL
Qwen3-VL
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: 1092626063 <1092626063@qq.com>
Similar to #2309 , this PR introduces Embedding tensor model parallel to
achieve decreasing of memory consumption. It support both eager mode and
graph mode.
And this PR refactor module tensor parallel configurations supported in
#2309, #2167, #2120, merge all config into `finegrained_tp_config` in
`additional_config`, including:
`lmhead_tensor_parallel_size`
`oproj_tensor_parallel_size`
`embedding_tensor_parallel_size`
`mlp_tensor_parallel_size`
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: zzhx1 <zzh_201018@outlook.com>
Signed-off-by: zzhxx <zhangzihang23@mails.ucas.ac.cn>
Co-authored-by: zzhx1 <zzh_201018@outlook.com>
Co-authored-by: chenxiao <Jaychou1620@Gmail.com>
Co-authored-by: zzhxx <zhangzihang23@mails.ucas.ac.cn>
Co-authored-by: Jade Zheng <zheng.shoujian@outlook.com>
### What this PR does / why we need it?
Currently, the usage of structured output feature in vllm-ascend is
totally the same as that in vllm.
Thus, IMO, it's better to remove this doc directly to avoid some case
that there are some changes in the upstream doc and we don't update our
doc in time, which can be misleading to users.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: shen-shanshan <467638484@qq.com>
This PR clean up useless torchair logic in model runner. The moge doc is
only for torchair, it can be removed as well.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
Co-authored-by: Mengqing Cao <cmq0113@163.com>
### What this PR does / why we need it?
Refactor the e2e testcases.
- tests/e2e/multicard/test_weight_loader.py: Remove the unused code.
- tests/e2e/singlecard/multi-modal/test_internvl.py: Move to accuracy
test.
- tests/e2e/singlecard/test_aclgraph.py: Rename the file.
- tests/e2e/singlecard/test_embedding_aclgraph.py : Combine with
tests/e2e/singlecard/test_bge_model.py
- tests/e2e/singlecard/test_completion_with_prompt_embeds.py: Delete
eager mode and modify model to Qwen3-0.6B
- tests/e2e/singlecard/test_quantization.py: Modify model to
Qwen3-0.6B-W8A8
- tests/e2e/singlecard/test_vlm.py: Modify model to Qwen3-VL-8B
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: menogrey <1299267905@qq.com>
### What this PR does / why we need it?
Add local running multi-node nightly test case guide, help running
locally at developer env.
### Does this PR introduce _any_ user-facing change?
NA
### How was this patch tested?
Test with local running multi-node test.
Using this document can successfully start multi-node night e2e in
locall
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: leo-pony <nengjunma@outlook.com>
### What this PR does / why we need it?
This document employs the qwen3-vl-8b model and qwen2.5-vl-32b to
demonstrate the primary verification steps for the Qwen-VL series dense
models, including supported features, feature configuration, environment
preparation, NPU deployment, and accuracy and performance evaluation.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: MrZ20 <2609716663@qq.com>
### What this PR does / why we need it?
This PR adds tutorials for the DeepSeeK-R1 series models, including the
A2 and A3 series, and provides accuracy validation results.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: Gongdayao <gongdayao@foxmail.com>
### What this PR does / why we need it?
This PR adds tutorials for the Qwen3-Dense series models, including the
A2 and A3 series, and provides accuracy validation results.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: wind-all <anyuting@h-partners.com>
### What this PR does / why we need it?
Adds W4A16 quantization method for the Kimi-K2-Thinking model and
updates relevant modules to support the new quantization method.
- Implements complete W4A16 quantization method including weight
packing/unpacking, per-group quantization parameter generation,
post-processing logic and MoE method application.
- Adds parameters `use_int4_w4a16`, `w1_offset` and `w2_offset`, adjusts
`with_quant` conditional logic to support W4A16 matrix multiplication.
- Adds `packed_modules_model_mapping` for Kimi-K2-Thinking model and
processing logic for `weight_packed` field.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: zhoux77899 <zhouxiang100@huawei.com>
Signed-off-by: Ruri <33858552+zhoux77899@users.noreply.github.com>
Signed-off-by: Ruri <zhouxiang100@huawei.com>
### What this PR does / why we need it?
Support pooling models (like `bge-reranker-v2-m3`) in vllm-ascend, this
pr covered the three model types of embed (cls_token, mean_token,
lasttoken).
After this
[commit](17373dcd93),
vllm has provided support for adapting pooling models on the v1 engine.
This PR includes corresponding adaptations on the vllm-ascend side.
Fixes#1960
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: lianyibo <lianyibo1@kunlunit.com>
Signed-off-by: MengqingCao <cmq0113@163.com>
Co-authored-by: MengqingCao <cmq0113@163.com>
aclgraph is stable and fast now. Let's drop torchair graph mode now.
TODO: some logic to adapt torchair should be cleaned up as well. We'll
do it in the following PR.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
Co-authored-by: Mengqing Cao <cmq0113@163.com>
### What this PR does / why we need it?
As support for the mooncake connector is now available, the llmdatadist
connector is no longer being maintained, so the llmdatadist-related
files need to be retired.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
By ci
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: wangxiaoteng <wangxiaoteng@huawei.com>
Signed-off-by: liziyu <liziyu16@huawei.com>
Co-authored-by: liziyu <liziyu16@huawei.com>
### What this PR does / why we need it?
Fix configuration error in our documentations.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
NA.
Signed-off-by: linfeng-yuan <1102311262@qq.com>
### What this PR does / why we need it?
Add Qwen3-235B tutorial including the following examples
- Single-node Online Deployment for 128k context inference
- Multi-node Deployment with MP
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: xuyexiong <xuyexiong@huawei.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
This patch adds support for the xlite graph wrapper to vllm_ascend.
Xlite provides operator implementations of the transformer network on
Ascend hardware. For details about xlite, please refer to the following
link: https://gitee.com/openeuler/GVirt/blob/master/xlite/README.md
The latest performance comparison data between xlite and the default
aclgraph mode is as follows:
## Qwen3 32B TPS 910B3(A2) Online Inference Performance Comparison
- aclgraph: main(c4a71fc6)
- xlite-full: main(c4a71fc6) + xlite-full
- xlite-decode-only: main(c4a71fc6) + xlite-decode-only
- diff1: Performance comparison between xlite-full and aclgraph
- diff2: Performance comparison between xlite-decode-only and aclgraph
### Does this PR introduce _any_ user-facing change?
Enable the xlite graph mode by setting xlite_graph_config:
--additional-config='{"xlite_graph_config": {"enabled": true}}' #
Enabled for decode only
--additional-config='{"xlite_graph_config": {"enabled": true,
"full_mode": true}}' # Enabled for prefill and decode
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: lulina <lina.lulina@huawei.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
check kv extra config & del hccl backend
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: liziyu <liziyu16@huawei.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
Translate remaining Chinese comments in the `dispatch_ffn_combine` code
to English and update the installation guide to remind users to
initialize submodules when building from source.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
---------
Signed-off-by: mojave2 <chenchen145@huawei.com>
Signed-off-by: Chen Chen <0109chenchen@gmail.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
As title shows, upgrade vllm commit hash to `ad32e3e`
- vLLM version: v0.12.0
---------
Signed-off-by: wangli <wangli858794774@gmail.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
### What this PR does / why we need it?
fix deepseekv3.1 doc to recomand developers to use Mooncake instead of LLMDatadist
### Does this PR introduce _any_ user-facing change?
<!--
Note that it means *any* user-facing change including all aspects such
as API, interface or other behavior changes.
Documentation-only updates are not considered user-facing changes.
-->
### How was this patch tested?
<!--
CI passed with new added/existing test.
If it was tested in a way different from regular unit tests, please
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If tests were not added, please describe why they were not added and/or
why it was difficult to add.
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Signed-off-by: AiChiMomo <1092626063@qq.com>
