Commit Graph

13 Commits

Author SHA1 Message Date
wangxiyuan
a0c3b8dd2d [v0.11.0]cherry-pick fix ut (#3608) (#3614)
cherry-pick fix ut (#3608)

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
2025-10-22 14:14:15 +08:00
whx
bd11c0054f [BugFix] Fix torchair+mtp bug after deleting deepseek_mtp. (#3590)
This is a missing bug fix introduced by PR #3561

- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0

---------

Signed-off-by: whx-sjtu <2952154980@qq.com>
2025-10-21 22:23:52 +08:00
zhangxinyuehfad
fdac146f71 [UT] fix skip ut test and enable ut test run normally (#3410)
### What this PR does / why we need it?

fix skip ut test and enable ut test run normally

### Does this PR introduce _any_ user-facing change?

### How was this patch tested?


- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0

Signed-off-by: hfadzxy <starmoon_zhang@163.com>
2025-10-20 16:30:57 +08:00
zouyida2052
3642b64afc bugfix for mtp with multistream_moe (#3419)
### What this PR does / why we need it?
when infer deepseek mtp layer with multistream_moe, we should pass a
boolean to evaluate this feature and fix bugs when we are in mtp layer

- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0

---------

Signed-off-by: zouyida2052 <zouyida2002@gmail.com>
2025-10-15 08:59:58 +08:00
weijinqian0
6972df5951 [Feature] optimize sp & qwen3 next support sp. (#3225)
This PR will accomplish the following tasks: 
**optimize SP**
In the old version implementation, the first layer was all_reduce, which
used rms to split chunks. We changed it to perform reduce_scatter on the
embedding side, replace one all_reduce operation and one chunk with one
reduce_scatter operation.
**Support qwen3 next**
Since Qwen3 Next includes a linear attention module, the prefix name of
this module cannot take effect directly.


- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0

---------

Signed-off-by: weijinqian_v1 <weijinqian@huawei.com>
Co-authored-by: weijinqian_v1 <weijinqian@huawei.com>
2025-10-13 23:02:12 +08:00
Wang Yixuan
30c5d947c3 [bugfix]fix multistream moe in torchair (#3164)
### What this PR does / why we need it?

the multistream moe in tochari only validate in decode, but can't be
applied to chunked prefill, So add some judgments to isolate the
scenario

### Does this PR introduce _any_ user-facing change?

No

### How was this patch tested?


- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0

Signed-off-by: hust17yixuan <303660421@qq.com>
2025-10-09 19:00:32 +08:00
lidenghui1110
0f3939e5a9 [Feature]cpu offload connector (#1659)
This PR implements cpu offload connector to enable NPU kv cache offload
to host DRAM.

- vLLM version: v0.10.2
- vLLM main:
5aeb925452

Signed-off-by: lidenghui <lidenghui1110@gmail.com>
Signed-off-by: AlvisGong <gwly0401@163.com>
Signed-off-by: CalvinXKY <kyxiezju@163.com>
Co-authored-by: AlvisGong <gwly0401@163.com>
2025-09-23 14:25:05 +08:00
Li Wang
02f89d166f [CI] Update vllm version to 20250922(5aeb925) (#3091)
### What this PR does / why we need it?
This pr bump vllm commit hash to
5aeb925452
fix issues:  
1. https://github.com/vllm-project/vllm/pull/25345 has remove v0
metadata
2. https://github.com/vllm-project/vllm/pull/25332
3. https://github.com/vllm-project/vllm/pull/25334
4. https://github.com/vllm-project/vllm/pull/23558, note that this vllm
commit update the model register logic, which will check all the model
registered have the `vllm.model_executor.models` path , which breaks our
custom registration of the deepseek_v3 model (it doesn't exist in the
vllm model path). so I move deepseek_v3 model registy to deepseek_v2 to
solve temporary

### How was this patch tested?

- vLLM version: v0.10.2
- vLLM main:
9607d5eb44

---------

Signed-off-by: wangli <wangli858794774@gmail.com>
2025-09-22 22:18:13 +08:00
rjg-lyh
0005479b9c [main] mlp weight prefetch in Qwen Dense Models (#2816)
### What this PR does / why we need it?
This PR prefetchs the weight of mlp layers in Qwen Dense Models to
optimize the performance in Decode phase mainly.

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

### How was this patch tested?
CI passed with new added/existing test.

- vLLM version: main
- vLLM main:
a1213fae5f

Signed-off-by: rjg-lyh <1318825571@qq.com>
Co-authored-by: Shuming19 <313093131@qq.com>
2025-09-11 21:20:09 +08:00
lidenghui1110
5a7181569c [feat]: oproj tensor parallelism in pure DP and graph-mode scenarios. (#2167)
### What this PR does / why we need it?
This PR introduces Oproj matrix tensor model parallel to achieve
decreasing of memory consumption. It only support graph mode in pure DP
scenario.

In deepseek r1 w8a8 PD disagregated Decode instance, using pure DP, with
oproj_tensor_parallel_size = 8, we have 1 ms TPOT increasing, saved 5.8
GB NPU memory per RANK. We got best performance when
oproj_tensor_parallel_size=4 without TPOT increasing.

performance data:
<img width="1442" height="442" alt="image"
src="https://github.com/user-attachments/assets/83270fc5-868a-4387-b0a9-fac29b4a376d"
/>

### Does this PR introduce _any_ user-facing change?
This PR introduces one new config in `additional_config`.
| Name | Effect | Required | Type | Constraints |
| :---------------------------- |
:--------------------------------------- | :------- | :--- |
:----------------- |
| oproj_tensor_parallel_size | Split the o_proj matrix along the row
dimension (head num * head dim) into oproj_tensor_parallel_size pieces.
| No | int | default value is None, once this value is set, the feature
will be enabled, head num * head dim must be divisible by this value. |

example

`--additional_config={"oproj_tensor_parallel_size": 8}`

### How was this patch tested?


- vLLM version: v0.10.1.1
- vLLM main:
eddaafc1c7

---------

Signed-off-by: zzhx1 <zzh_201018@outlook.com>
Co-authored-by: zzh <zzh_201018@outlook.com>
2025-09-07 10:31:32 +08:00
lidenghui1110
600b08f754 [Feat]: Add custom lmhead tensor model parallel (#2309)
### What this PR does / why we need it?
This PR introduces LMhead tensor model parallel to achieve decreasing of
memory consumption, and TPOT performance improvement. It support both
eager mode and graph mode.

In deepseek r1 w8a8 PD disagregated Decode instance, using pure DP, with
lmhead_tensor_parallel_size = 8, we have 1 ms TPOT optimization, saved
1.48 GB NPU memory per RANK.

performance data:
<img width="1444" height="438" alt="image"
src="https://github.com/user-attachments/assets/3c5ef0d3-a7c7-46fd-9797-4de728eb0cb0"
/>

### Does this PR introduce _any_ user-facing change?
This PR introduces one new config in `additional_config`.
| Name | Effect | Required | Type | Constraints |
| :---------------------------- |
:--------------------------------------- | :------- | :--- |
:----------------- |
| lmhead_tensor_parallel_size | Split the lm_head matrix along the
column dimension (vocab_size) into lmhead_tensor_parallel_size pieces |
No | int | default value is None, once this value is set, the feature
will be enabled, vocab_size must be divisible by this value. |

example

`--additional_config={"lmhead_tensor_parallel_size": 8}`

### How was this patch tested?


- vLLM version: v0.10.1.1
- vLLM main:
de533ab2a1

---------

Signed-off-by: zzhx1 <zzh_201018@outlook.com>
Co-authored-by: zhangzihang <zzh_201018@outlook.com>
2025-08-29 11:41:21 +08:00
Wang Yixuan
0f81e032f0 [1/N][refactor] torchair fused_moe refactor (#2438)
### What this PR does / why we need it?
Move torchair related fused_moe section into torchair_fused_moe to make
the code clear. Next step we'll remove all torchair related code outside
of torchair_fused_moe .

### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
vLLM version: v0.10.0
vLLM main:
08d5f7113a

- vLLM version: v0.10.1.1
- vLLM main:
170e8ea9ea

Signed-off-by: hust17yixuan <303660421@qq.com>
2025-08-25 15:46:10 +08:00
linfeng-yuan
3fc31ee1cb [1/N][refactor] torchair deepseek modeling refactor (#2384)
### What this PR does / why we need it?

Move torchair related model arch into torchair moduel to make the code
clear. Next step we'll remove all torchair related code outside of
torchair moduel.

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

- vLLM version: v0.10.0
- vLLM main:
08d5f7113a

Signed-off-by: linfeng-yuan <1102311262@qq.com>
2025-08-18 15:00:37 +08:00