Commit Graph

16 Commits

Author SHA1 Message Date
Li Wang
bf84f2dbfa [Doc] Support kimi-k2-w8a8 (#2162)
### What this PR does / why we need it?
In fact, the kimi-k2 model is similar to the deepseek model, and we only
need to make a few changes to support it. what does this pr do:
1. Add kimi-k2-w8a8 deployment doc
2. Update quantization doc
3. Upgrade torchair support list
### Does this PR introduce _any_ user-facing change?

### How was this patch tested?


- vLLM version: v0.10.0
- vLLM main:
9edd1db02b

---------

Signed-off-by: wangli <wangli858794774@gmail.com>
2025-08-06 19:28:47 +08:00
22dimensions
8cf97d8310 [Misc] Add extra checking to torchair_graph_config. (#1939)
### What this PR does / why we need it?

cherry-pick #1675  to main
This PR adds validation checking to torchair_graph_config for better
reliability.

Co-authored-by: whx-sjtu <2952154980@qq.com>

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

No

### How was this patch tested?


- vLLM version: v0.10.0
- vLLM main:
2836dd73f1

Signed-off-by: 22dimensions <waitingwind@foxmail.com>
2025-08-01 09:24:11 +08:00
Mengqing Cao
8cfd257992 [Dist][EP] Remove ETP/EP maintained in vllm-ascend (#1681)
### What this PR does / why we need it?
Remove ETP/EP maintained in branch main. We drop this as there is no
relevant scenarios to use ETP now, and we may subsequently advocate
implementing expert tensor parallelism in vLLM to support scenarios
where the expert is needed to be sliced

This is a part of #1422 backport.

Fixes https://github.com/vllm-project/vllm-ascend/issues/1396
https://github.com/vllm-project/vllm-ascend/issues/1154

### Does this PR introduce _any_ user-facing change?
We'll not maintain etp/ep in vllm-ascend anymore, and use the tp/ep in
vllm instead.

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


- vLLM version: v0.9.2
- vLLM main:
fe8a2c544a

Signed-off-by: MengqingCao <cmq0113@163.com>
2025-07-21 09:08:04 +08:00
wangxiyuan
7bdada58eb [Misc] Remove VLLM_USE_V1 usage in code (#1764)
We plan to remove V0 code from this version. The first step is to delete
v0 usage.

Related: https://github.com/vllm-project/vllm-ascend/issues/1620

- vLLM version: v0.9.2
- vLLM main:
61e20828da

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
2025-07-15 11:52:16 +08:00
wangxiyuan
343955c7ac [CI] Follow vLLM FusedMoEParallelConfig interface change and clean up unused config (#1625)
This commit
78fe77534b
from vllm reverted the change for FusedMoEParallelConfig

This PR do the same to fix the CI error

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
2025-07-04 17:54:33 +08:00
Angazenn
a5f33590d3 [CORE]initial support for torchair with non-mla backend (#1506)
### What this PR does / why we need it?
This PR supports torchair graph mode with non-mla backend on both 800IA2
and 300I Duo platforms. The main change is to add
`attention_v1_torchair.py` to support specific attention related
operations that are required by torchair.

### Does this PR introduce _any_ user-facing change?
Before this PR, vLLM-Ascend only allows deepseek to use torchair. Now we
can also use it with pangu. Besides, we add a support model list to
control which type of models that can use torchair.

### How was this patch tested?
We have test it with PanguProMoE on both 800IA2 and 300I Duo platforms,
and model generates answer normally.

---------

Signed-off-by: angazenn <zengyanjia@huawei.com>
Signed-off-by: tianyitang <tangtianyi4@huawei.com>
Co-authored-by: angazenn <zengyanjia@huawei.com>
Co-authored-by: tianyitang <tangtianyi4@huawei.com>
2025-07-03 22:21:42 +08:00
wangxiyuan
69b817ed65 [CI] Add unit test framework (#1201)
This PR added the unit test framework to enable ut for vLLM Ascend. Unit
test runs on CPU machines. It'll be ran once lint check is passed the
same as e2e test.

For unit test, this PR created a new folder called `ut` under `tests`
module. All the test file in `ut` should keep the same with the code in
`vllm-ascend`. The file name should be start with `test_` prefix. For
example, in this PR. the `test_ascend_config.py` is added for
`ascend_config.py` test.

A new fille `worker/test_worker_v1.py` is also added as the placeholder.
This file should be the unit test for `vllm-ascend/worker/worker_v1.py`.

Additional, a new `fake_weight` folder is added, it contains the
config.json from `facebook/opt-125m`, so that the test will not always
visit huggingface.

TODO:
We should add all the unit test file one by one in the future.

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
2025-06-16 18:32:28 +08:00
fems14
ab5d110fcc vllm-ascend support chunked prefill (#1172)
### What this PR does / why we need it?
vllm-ascend support chunked prefill for MLA


---------

Signed-off-by: fems14 <1804143737@qq.com>
2025-06-14 22:31:16 +08:00
sdmyzlp
e72f94e38f Support multistream of MLA vector operations (#1135)
### What this PR does / why we need it?
Move all vector operations to a secondary stream, with the expected
overlaping being:
```
              | q_rmsnorm |                  | kv_norm_rope_cache |       | q_rope |
| matmul W_DQ | matmul W_DKV | index | index |    matmul W_UQ     | split | matmul W_KV_T |
```

Currently, the `IndexByTensor` operators introduced by computation of
`cos` and `sin` can't be offloaded to the secondary stream due to a
known bug of graph fusion optimization pass. So we instead keep it in
the main stream, only requires it be computed before `matmul W_UQ` to
avoid hindering later overlapping. The problem may be solved by later
optimization (#993), which hoists the computation of `cos` and `sin` up
to the first layer.

### Does this PR introduce _any_ user-facing change?
Controlled by `torchair_graph_config.enable_multistream_mla`, defaulted
to False.

### How was this patch tested?
Tested on 1x16 910 node, with tailored 2 layer DSKv2.

Signed-off-by: sdmyzlp <lrwei2@petalmail.com>
2025-06-12 21:42:09 +08:00
chenwaner
e46dc142bf Enable kvcache_nz for the decode process in torchair graph mode (#1098)
What this PR does / why we need it?
Enable kvcache_nz for the decode process in torchair graph mode, which
reduces the time consumed by FA in long sequences.

Does this PR introduce any user-facing change?
If need to enable kvcache_nz, should set the
additional_config.torchair_graph_config.enable_kv_nz=True

How was this patch tested?
1. Tested in deepseek model:
with batchsize 64 and seq_len 1k+3k, 61 layers FA total time improves
20.80ms -> 19.76ms
2. operator precision test: 

[aclnnFusedInferAttentionScoreV3_result.csv](https://github.com/user-attachments/files/20664138/aclnnFusedInferAttentionScoreV3_result.csv)
3. tpot test from @ttanzhiqiang, and curl one result is normal

https://github.com/vllm-project/vllm-ascend/pull/1098#issuecomment-2948542159

https://github.com/vllm-project/vllm-ascend/pull/1098#issuecomment-2954496588

---------

Signed-off-by: chenwaner <861645847@qq.com>
2025-06-11 14:09:28 +08:00
sdmyzlp
7bdc606677 Support multistream of shared experts in FusedMoE (#997)
Contains on #1111 for completeness.

<!--  Thanks for sending a pull request!

BEFORE SUBMITTING, PLEASE READ
https://docs.vllm.ai/en/latest/contributing/overview.html

-->
### What this PR does / why we need it?
Implement multi-stream parallelism for MoE layers with shared experts,
where computation of shared experts will be overlapped with expert token
dispatch and combine. Also, when multi-stream is enabled, weights of
shared experts will be force to replicate across all cards, regardless
of any tensor parallelism configurations, to avoid AllReduce operations.

With the expected overlaping being:
```
| shared gate_up | shared act |              | shared down |
|    dispatch    | routed gate_up, act, down |   combine   |
```

<!--
- Please clarify what changes you are proposing. The purpose of this
section is to outline the changes and how this PR fixes the issue.
If possible, please consider writing useful notes for better and faster
reviews in your PR.

- Please clarify why the changes are needed. For instance, the use case
and bug description.

- Fixes #
-->

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

<!--
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?
Tested on 1x16 910 node, with tailored 2 layer DSKv2.
<!--
CI passed with new added/existing test.
If it was tested in a way different from regular unit tests, please
clarify how you tested step by step, ideally copy and paste-able, so
that other reviewers can test and check, and descendants can verify in
the future.
If tests were not added, please describe why they were not added and/or
why it was difficult to add.
-->

---------

Signed-off-by: sdmyzlp <lrwei2@petalmail.com>
2025-06-11 09:18:38 +08:00
Yuxiao-Xu
6b853f15fe Add static EPLB (#1116)
### What this PR does / why we need it?
   Add EPLB expert map import capabilities
### Does this PR introduce _any_ user-facing change?
When importing the EPLB expert map you need import expert map file by
vllm args additional_config
### How was this patch tested?
1.You need to collect expert hotness and generate an expert placement
file based on the hotness and the EPLB algorithm, or you can directly
use an existing expert placement table.
2.When launching vLLM, enable EC2 and pass the configuration via the
command-line argument:
      --additional-config '{"expert_map_path": "/xxx/xxx/xx.json"}
Co-authored-by: songshanhu07 <1763685535@qq.com>

---------

Signed-off-by: songshanhu07 <1763685535@qq.com>
Signed-off-by: Yuxiao-Xu <664988918@qq.com>
Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
Co-authored-by: songshanhu07 <1763685535@qq.com>
Co-authored-by: Xu Yuxiao <xuyuxiao2@huawei.com>
Co-authored-by: wangxiyuan <wangxiyuan1007@gmail.com>
2025-06-09 19:28:11 +08:00
sdmyzlp
3640c60b0e Avoid unfused Transpose in DeepSeekV3 EP256 MoE layer (#1091)
### What this PR does / why we need it?

View optimization in torchair (defaulted to on for Transpose with any of
its axis being 1) prevents the weight Transpose to be fused with later
GroupedMatmul, which decrease the performance of MoE layer when expert
parallelism equals the total number of experts (e.g. EP256 for DSKv3).
Add an option to solve this problem by disabling the optimization.

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

Controlled by
`additional_config.torchair_graph_config.enable_view_optimize`,
defaulted to `True`.

### How was this patch tested?

Tested on 1x16 910 node, with tailored 2 layer DSKv2.

Signed-off-by: sdmyzlp <lrwei2@petalmail.com>
2025-06-07 14:28:20 +08:00
wangxiyuan
dab19d5dca [BugFix] Fix ascend config check (#1092)
Fix the ascend config check logic:
1. refactor check_ascend_config to make it clear:
    1. torchair graph should not work with enforce_eager=True
    2. aclgraph should not work with torchair graph
3. add refresh config for rlhf case
4. fix a typo in model runner
5. change expert_tensor_parallel_size default to 0 to keep the same as
before

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
2025-06-06 18:54:37 +08:00
David9857
78431b3469 [perf]Support MOE Multi-stream in Deepseek (#947)
### What this PR does / why we need it?
Support MOE inner Multi-stream for Deepseek. 
This feature requires graph mode with mc2 enabled.

---------

Signed-off-by: David9857 <985700846@qq.com>
2025-06-05 23:39:38 +08:00
wangxiyuan
e1ab6d318e [Misc] Refactor additional_config (#1029)
More and more config options are added to additional_config. This PR
provide a new AscendConfig to manage these config options by an easier
way to make code cleaner and readable.

 This PR also added the `additional_config` doc for users.

Added the test_ascend_config.py to make sure the new AscendConfig works
as expect.

TODO: Add e2e test with torchair and deepseek once the CI resource is
available.

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
2025-06-05 16:28:01 +08:00