Commit Graph

12 Commits

Author SHA1 Message Date
rjg-lyh
74903af460 [v0.11.0][refactor] refactor SequenceRowParallelOp forward (#3654)
### What this PR does / why we need it?
This PR refactors SequenceRowParallelOp forward. In order to further
expand the operator inclusion scope in dynamic judgment scenarios, this
PR customizes the entire matmul computation and communication as a
custom operator masking. With this refactor, it will support directly
writing code such as common operation fusion into the
SequenceRowParallelOp class's member function matmul_and_reduce, without
the need to register more redundant custom masking operators.

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

Signed-off-by: rjg-lyh <1318825571@qq.com>
2025-10-23 14:45:49 +08:00
linfeng-yuan
4c9af353ee Revert "[Feat] Shared expert dp for deepseek and deepseek_mtp (#3495)" (#3586)
### What this PR does / why we need it?
This reverts commit
bf87606932.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
E2E vllm serving with `enable_shared_expert_dp: true` in eager mode as
before.


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

Signed-off-by: linfeng-yuan <1102311262@qq.com>
2025-10-21 22:24:30 +08:00
zhaozx-cn
bf87606932 [Feat] Shared expert dp for deepseek and deepseek_mtp (#3495)
### What this PR does / why we need it?
shared expert dp for deepseek and deepseek_mtp, could be combined with
sp to improve performance.

### 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: zhaozx-cn <zhaozx2116@163.com>
Co-authored-by: realliujiaxu <realliujiaxu@163.com>
2025-10-17 15:06:37 +08:00
realliujiaxu
f69a83b7ba [Feat] Flash comm allgher ep (#3334)
Support flash comm v1(Sequence Parallelism) for Allgather EP.

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

---------

Signed-off-by: realliujiaxu <realliujiaxu@163.com>
Co-authored-by: zhaozx-cn <zhaozx2116@163.com>
2025-10-15 19:36:32 +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
Ruri
ff37575936 [1/N][Feat] Add weight prefetch feature for Attention layers (#3146)
### What this PR does / why we need it?

- Refacotr and integrate a unified `WeightPrefetchMethod`
- Integrate `qkv_proj.weight` and `o_proj.weight` in quantized Attention
modules
- Prefetching these weights ahead of matmul-like operators imporves
performance by reducing L2 cache transfer latency

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

Add a new config in `--additional-config` for configuration:
```json
{
    "weight_prefetch_config": {
        "enabled": false,
        "prefetch_ratio": {
            "attn": {
                "qkv": 1.0,
                "o": 1.0,
            },
        },
    },
}
```
This feature is enabled by default, and can be disabled through this
configuration

### How was this patch tested?


- vLLM version: v0.11.0

---------

Signed-off-by: yuzhup <15705211260@163.com>
Signed-off-by: zhoux77899 <zhouxiang100@huawei.com>
Co-authored-by: yuzhup <15705211260@163.com>
2025-10-09 20:38:39 +08:00
whx
14d4ed5f0c [BugFix] Fix aclgraph accu problem in A2. (#3163)
This PR fixes accuracy problem of aclgraph on A2. The problem is
introduced by PR #2980, which makes the `all_reduce` of shared_experts
exposed to torch dynamo. This PR moves all the codes into forward_impl
to shiled from torch dynamo.

- vLLM version: v0.10.2
- vLLM main:
17b4c6685c

---------

Signed-off-by: whx-sjtu <2952154980@qq.com>
2025-09-28 21:31:55 +08:00
weijinqian0
6aa4253798 [Refactor] [SP]The sequence parallelism characteristics in the MoE and Dense models are integrated into a single solution. (#3085)
What this PR does / why we need it?

there are two sets of sp implementations for moe and dense models. One
is called sequence_parallelism, and the other is flashcomm_v1.
We did the following things:

Merge two sets of code with the same implementation into one.
Remove the implementation of sequence_parallelism, as this solution
cannot support aclgraph.
Does this PR introduce any user-facing change?

No

How was this patch tested?

e2e&ut

- vLLM version: v0.10.2
- vLLM main:
f225ea7dd9

---------

Signed-off-by: weijinqian_v1 <weijinqian@huawei.com>
Co-authored-by: weijinqian_v1 <weijinqian@huawei.com>
2025-09-24 11:29:59 +08:00
rjg-lyh
bb1f0d5a62 [main] remove the redundant log prints in register_custom_ops.py (#3094)
### What this PR does / why we need it?
This PR removed the redundant log prints in register_custom_ops.py, in
order to make output clear.

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

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

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

Signed-off-by: rjg-lyh <1318825571@qq.com>
2025-09-22 17:17:31 +08:00
rjg-lyh
fc2bcbe21c [Ops] Fix bug in register_custom_ops without forward_context (#2883)
### What this PR does / why we need it?
This PR fixed the bug in register_custom_ops without forward_context. We
set try-except to consider this situation.

### 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:
7920de0a2a

Signed-off-by: rjg-lyh <1318825571@qq.com>
2025-09-12 16:58:08 +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
rjg-lyh
1bbb20ea13 [main] flashcomm_v1 optim in Qwen Dense Models (#2802)
### What this PR does / why we need it?
Flashcomm_v1 optim in Qwen Dense Models.

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

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

- vLLM version: v0.10.1.1
- vLLM main:
5e537f45b4

Co-authored-by: 1024daniel <xxltju324@gmail.com>
2025-09-08 22:52:24 +08:00