18 Commits

Author SHA1 Message Date
HongtaoYang
80a4265717 [Feat] Support separate attention backend for target and draft model. (#7342)
### What this PR does / why we need it?
This PR enables separate attention backend configuration for target and
draft models in speculative decoding, decoupling the previously bound
attention backend settings between the two models.

It solves the compatibility issue where some draft models do not support
the attention backend used by the target model, and allows users to
select the optimal attention backend for each model individually to
maximize inference performance. The change is fully backward compatible.
---------
Signed-off-by: SidaoY <1024863041@qq.com>
2026-03-21 10:48:01 +08:00
zhenwenqi2024
5d9fde9819 [Feature] Refactor PCP &DCP related code (#5214)
### What this PR does / why we need it?
Refactor pcp& dcp related code. we use pcp_manager class to Unifiy
Manage pcp & dcp . as we do this , many code can be deleted from
model_runner, and can avoid break pcp & dcp by other developments.
RFC:https://github.com/vllm-project/vllm-ascend/issues/5449
### Does this PR introduce _any_ user-facing change?
NO

### How was this patch tested?

- vLLM version: release/v0.13.0
- vLLM main:
ad32e3e19c

---------

Signed-off-by: zhenwenqi2024 <zhenwenqi_2022@qq.com>
Co-authored-by: zzzzwwjj <34335947+zzzzwwjj@users.noreply.github.com>
2025-12-31 09:29:57 +08:00
wangxiyuan
d1f0df7b4b Revert "MLA prefill preformance optimization (#5275)" (#5410)
We'll release 0.13.0 soon. The main branch is freeze. Let's revert the
newest change and redo it once 0.13.0 is released
- vLLM version: release/v0.13.0
- vLLM main:
81786c8774
2025-12-27 09:48:56 +08:00
pichangping
711f1861e4 MLA prefill preformance optimization (#5275)
### What this PR does / why we need it?
Since the _npu_ring_mla operator deteriorates in long-sequencescenarios,
the long sequence is split into shorter sequences for input to improve
performance.
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?

- vLLM version: release/v0.13.0
- vLLM main:
ad32e3e19c

---------

Signed-off-by: pichangping <1337510399@qq.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
2025-12-27 09:19:45 +08:00
zhangsicheng5
78aa7f2693 [feature] support pcp + mtp in full graph (#4572)
1. support pcp + mtp in full graph
2. pcp/dcp related mtp bugfix
3. support pcp + mtpx

- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c

Signed-off-by: zhangsicheng5 <zhangsicheng5@huawei.com>
2025-12-22 16:13:39 +08:00
zhangsicheng5
07014e2101 [UT] Add model_runner pcp related UTs (#4951)
1. Add some uts for pcp related functions in NPUModelRunner
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c

Signed-off-by: zhangsicheng5 <zhangsicheng5@huawei.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
2025-12-18 10:54:57 +08:00
LookAround0301
bb7b74c14f add ut for model runner (#4991)
### What this PR does / why we need it?
add ut for model runner

- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c

---------

Signed-off-by: LookAround <lixushi@huawei.com>
2025-12-14 11:16:20 +08:00
zhenwenqi2024
f708d919f8 [Feature] model_runner refactor (#4764)
### What this PR does / why we need it?
refactor npu_modelrunner, we should be close to gpu_modelrunner 

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

- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c

---------

Signed-off-by: zhenwenqi2024 <zhenwenqi_2022@qq.com>
Signed-off-by: zhenwenqi2024 <155598497+zhenwenqi2024@users.noreply.github.com>
2025-12-12 17:27:09 +08:00
lidenghui1110
a82b0fa70e mooncake connector support pipeline parallel & fix pp with flashcomm1 (#4054)
### What this PR does / why we need it?
To support pipeline parallel with PD disaggregation, this PR support PP
in mooncake connector and fix other bugs when enable pp with other
optimization params, including following changes:
- mooncake connector support pp in prefill, we do not support decode pp
currently
- fix bugs when enable both pp and flashcomm1
- optimize ascend-scheduler to support full batch in multiple pipeline
stages, original implementation would cause all pipeline stages
batch_size total summed to max_num_seq, which makes pipeline is not
full, this optimization can make all stages running with full batch_size
= max_num_seq, the same changes will contribute to vllm scheduler too.

### Does this PR introduce _any_ user-facing change?
add `pp_size` in mooncake connector kv_connector_extra_config
```
"kv_connector_extra_config": {
            "use_ascend_direct": true,
            "prefill": {
                    "dp_size": 1,
                    "tp_size": 4,
                    "pp_size": 4
             },
             "decode": {
                    "dp_size": 16,
                    "tp_size": 1
             }
        }
```

### How was this patch tested?

- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c

---------

Signed-off-by: chenxiao <Jaychou1620@Gmail.com>
Signed-off-by: Kurumi5210 <Jaychou1620@Gmail.com>
Signed-off-by: Kurumi5210 <jaychou1620@gmail.com>
Signed-off-by: 秋刀鱼 <jaychou1620@Gmail.com>
Co-authored-by: chenxiao <Jaychou1620@Gmail.com>
Co-authored-by: zss <zss@qq.com>
Co-authored-by: zss <3265779424@qq.com>
2025-12-10 16:01:43 +08:00
zzzzwwjj
136ea9ff56 [refact] unified soc_version code (#4359)
### What this PR does / why we need it?

Currently, there are two paths to judge the chip type in code,
`get_ascend_soc_version` use `get_soc_version` api in torch_npu, and
`is_310p` `use _build_info.__soc_version__`, which generate when
install. We need to unify the two paths.

We need to unify these codes based on the following points:

1. We need to ensure consistency in chip type judgment between compiling
and running states;
2. In compiling state, we need chip type to complete op's compilation,
but in running state, we only need device
type(910B/910_93/310P/910_95/etc) to make code branch judgement;
3. In compiling state, torch_npu may not have been installed yet, so we
can't use torch_npu's api.

Based on the above points, we have made the following changes:

1. When user set env `SOC_VERSION`, use it; when not set, query
soc_version by `npu-smi`;
2. generate device_type based on soc_version when compiling, and write
`__device_type__` instead of `__soc_version__` in `_build_info.py`;
3. In running state, use `__device_type__` to judge code branch.

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

When not set env `SOC_VERSION`, it will not be `ASCEND910B1` by default,
we will query soc_version by `npu-smi`. And env `SOC_VERSION` must be in
the list `soc_to_device` in `setup.py`.

- vLLM version: v0.11.0
- vLLM main:
2918c1b49c

Signed-off-by: zzzzwwjj <1183291235@qq.com>
2025-11-26 14:28:55 +08:00
weijinqian0
ae068a3342 [Refactor] remove moe type of multicast. (#4224)
The main purposes of this PR are as follows: 
1. Remove the multicast-related code; 

Reason:
1. In the scenario like a2 Dual-System Back-to-Back Networking,the
performance is worse than all_gather. Before the modification, in e2e
test, it was 3 tps; after the modification, it is 10 tps.
2. At the same time, we usually enable the SP feature,it is consistent
with the current logic.
3. The advantage of broadcast communication lies in the fact that it
does not suffer from uneven DP load and does not require the prefill ACL
graph to be enabled. But we support prefill Acl graph recently.

So we think there is no need to maintain the multicast as one choice in
moe communication.

Performance benefits are as follows:
When not enable_flashcomm1, TTFT remains relatively stable at around
43000ms, which is approximately 15000ms faster than before the
modification.

When enable_flashcomm1, there is no diffenence, TTFT remains relatively
stable at around 29000ms.


- vLLM version: v0.11.0
- vLLM main:
2918c1b49c

---------

Signed-off-by: weijinqian_v1 <weijinqian@huawei.com>
Signed-off-by: weijinqian0 <1184188277@qq.com>
Co-authored-by: weijinqian_v1 <weijinqian@huawei.com>
2025-11-24 17:32:37 +08:00
realliujiaxu
74191864b7 [Perf] Delete redundant operations in model_runner and forward_context (#3677)
### What this PR does / why we need it?

Remove redundant operations from `model_runner` and `forward_context`.
This optimization can significantly reduce the idle time (bubble) before
decoding when running models with small parameter counts (e.g.,
Qwen/Qwen2.5-0.5B).

Testing on 800I A2, bubble is reduced from 3.8ms to 2.8ms :
Before
<img width="1655" height="696" alt="image"
src="https://github.com/user-attachments/assets/d7608e52-2438-46dd-8fc9-391fd6274495"
/>

After
<img width="1607" height="774" alt="image"
src="https://github.com/user-attachments/assets/56daf081-2dba-4d2e-99d4-e055187d9806"
/>

### 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/releases/v0.11.1

---------

Signed-off-by: realliujiaxu <realliujiaxu@163.com>
2025-10-29 15:59:55 +08:00
wangxiyuan
0794f64a18 Revert "[Disagg][Perf] Use NPU event sync instead of blocking tolist (#3194)
…to avoid unintentional copy ops blocking across different NPU streams,
improving disagg TTIT/TTFT (#2788)"



### What this PR does / why we need it?
This reverts commit 6995a7bc5b. We'll add
it back once the issue is fixed.

related issue: https://github.com/vllm-project/vllm-ascend/issues/3195

### How was this patch tested?

- vLLM version: v0.10.2
- vLLM main:
52d0cb8458
2025-09-26 06:17:36 +08:00
Song Zhixin
6995a7bc5b [Disagg][Perf] Use NPU event sync instead of blocking tolist to avoid unintentional copy ops blocking across different NPU streams, improving disagg TTIT/TTFT (#2788)
### What this PR does / why we need it?
When we copy the sampled valid token ids from device to host, avoid
using tolist which would trigger a CUDA wise stream sync if the source
is on device. We change it to use non-blocking copy followed by an
explicit CUDA event sync.

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

### How was this patch tested?
Bring up vLLM server
```bash
VLLM_USE_V1=1 vllm serve Qwen/Qwen2.5-14B-Instruct --disable-l
og-requests -tp 8 --max-num-seqs 64 --no-enable-prefix-caching --max_num_batched_tokens=8000
```
## Before:

![76218085a0cde9b2a73214e35fb7fc08](https://github.com/user-attachments/assets/38cbd02d-d380-47f8-a111-4bd859102eb1)
## After

![6c2111136673332244d3ce11060f4048](https://github.com/user-attachments/assets/957f9bf1-ec50-4f49-9318-f4876b3e3691)

As shown in the figure, the TTFT decreased


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

---------

Signed-off-by: jesse <szxfml@gmail.com>
2025-09-24 11:21:58 +08:00
weichen
37a0715eda [Refactor] Adjustments to moe_comm_method selection process (#3001)
### What this PR does / why we need it?
Fix issues mentioned in
https://github.com/vllm-project/vllm-ascend/pull/2791 and some minor
refactoring.
1. Use Enum instead of string.
2. Avoid setting a new property to forward_context in
AscendFusedMoE.forward().
3. Enabling TokenDispatcherWithMoge.
4. Remove redundant code.

### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?

Qwen3-30B-A3B/Qwen3-30B-A3B-W8A8/DeepSeek-V3-W4A8-Pruing/deepseek-mtp/pangu-pro-moe-pruing:
1. Enable/Disable EP
2. Aclgraph & eager


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

Signed-off-by: Pr0Wh1teGivee <calvin_zhu0210@outlook.com>
Co-authored-by: weijinqian0 <12153182+weijinqian0@users.noreply.github.com>
2025-09-22 19:12:58 +08:00
weichen
18ca7861f6 [Main] [Refactor] Enable MoECommMethod in Eager Mode (#2791)
### What this PR does / why we need it?
1. Replace prepare/finalize operation in fused_moe.py by
moe_comm_method.prepare()/finalize()
2. Replace unified_fused_experts by moe_comm_method.fused_experts() in
fused_moe.py/w8a8_dynamic.py/w4a8_dynamic.py
3. Add calling _select_moe_comm_method in spec-decode proposers.
4. Currently, w4a8_dynamic does not support gatherep, use all2allv
instead.
5. Remove redundant code.
### Does this PR introduce _any_ user-facing change?
AllgatherEP switch is disabled in aclgraph/eager mode, just follow the
rules in modelrunner_v1._select_moe_comm_method()
### How was this patch tested?
e2e & ut


- vLLM version: v0.10.2
- vLLM main:
7f6f2c1182

Signed-off-by: Pr0Wh1teGivee <calvin_zhu0210@outlook.com>
Co-authored-by: weijinqian0 <12153182+weijinqian0@users.noreply.github.com>
2025-09-16 11:06:00 +08:00
wangxiyuan
382c29f3e1 [BugFix] Fix world size bug in model_runner (#2915)
- Fix world size bug in model_runner to make sure ep>16 runs with MC2 
- enable e2e test for vl

Co-Authored-By: whx-sjtu <2952154980@qq.com>
Co-Authored-By: Icey <1790571317@qq.com>
- vLLM version: v0.10.2
- vLLM main:
3e903b6cb4

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
2025-09-14 12:20:25 +08:00
yiz-liu
83eb40a51c [Fix][MoE] Refine MoE communication strategy (#2734)
### What this PR does / why we need it?
Refactors the Mixture-of-Experts (MoE) communication method selection
logic. The choice between all-gather, all-to-all, and mc2 is now
determined by expert parallel configuration, SoC version (A2/A3), and
token count for better performance.

### Does this PR introduce _any_ user-facing change?
None.

### How was this patch tested?
Added.


- vLLM version: v0.10.1.1
- vLLM main:
eafa8dcde6

---------

Signed-off-by: Yizhou Liu <liu_yizhou@outlook.com>
2025-09-05 09:04:04 +08:00