Commit Graph

16 Commits

Author SHA1 Message Date
linfeng-yuan
068ed706c8 [feat][torchair] support super kernel feat for quantized dsr1 (#3485)
### What this PR does / why we need it?
Port #1916 and #2157 to master branch to fuse operators in deepseek moe
layers, which can reduce scheduling overhead on devices. Note that this
feature is valid only when `tp_size = 1` and
`multistream_overlap_shared_expert` is enabled with torchair graph mode.

### Does this PR introduce _any_ user-facing change?
Users can enable this feature with `--additional-config
'{"torchair_graph_config":{"enabled":true, "enable_super_kernel":true},
"multistream_overlap_shared_expert":true}'`.

### How was this patch tested?
E2E deepseek serving with 2P1D disaggregated prefill scenarios.


- 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>
2025-10-20 20:04:37 +08:00
Jade Zheng
e04a5e3dd3 [Bugfix] Fix race condition in d2h transfer (#3372)
### What this PR does / why we need it?

Using non-blocking operations for device-to-host transfers can lead to
data corruption in later steps. The CPU tensor is accessed right after
the transfer is triggered, but the transfer might not be complete yet.
As a result, the data could be wrong. This problem was seen in the A3
environment during `profile_run`.

### How was this patch tested?
CI pass.

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

Signed-off-by: Jade Zheng <zheng.shoujian@outlook.com>
2025-10-20 18:24:21 +08:00
offline893
6c9909c861 [Patch]patch of v1 executor when enable eplb. (#3511)
### What this PR does / why we need it?
when using dynamic eplb, patch v1 executor to avoid create child process
failed.

### How was this patch tested?
deepseek in v3.

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

---------

Signed-off-by: offline0806 <3337230449@qq.com>
Co-authored-by: offline0806 <3337230449@qq.com>
2025-10-19 10:54:26 +08:00
yechao237
4750d45d86 [BugFix]Support redundant experts in EPLB (#3473)
This PR adds support for redundant experts in the EPLB. 

Key points: 
- Use global_num_experts = num_experts + num_redundant_experts
consistently.
- Backward compatible when num_redundant_experts=0. 

Tested 
On a 16-rank setup (W8A8) with static EPLB and expert_map_path,
verifying router logits shape and successful requests.

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

Signed-off-by: yechao237 <yechao20180411@gmail.com>
2025-10-18 00:09:16 +08:00
offline893
5a3082cd15 [EPLB]Record expert map without dynamic eplb. (#3409)
What this PR does / why we need it?
1.Record expert map without dynamic eplb.
2.Add export PYTHONOPTIMIZE=1  when using dynamic eplb.
3.change eplb doc

Does this PR introduce any user-facing change?
How was this patch tested?
Qwen3_moe in A3.

- vLLM version: v0.11.0

---------

Signed-off-by: offline0806 <3337230449@qq.com>
Co-authored-by: offline0806 <3337230449@qq.com>
2025-10-15 14:21:15 +08:00
linfeng-yuan
c55d99d13e [bugfix][torchair] fix missing weight nz cast for w13_weight in torchair_w8a8_dynamic.py (#3446)
### What this PR does / why we need it?
Fix the issue of missing NZ conversion for quantized weights in GMM
after moe_dispatch operator in torchair scenario, which does not involve
aclgraph & single scenarios.

### How was this patch tested?
vllm serving passed with lower latency (~5ms TPOT with bs_per_rank=28 &
ep_size=32)

- 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>
2025-10-14 21:11:05 +08:00
anon189Ty
07e39620ea [Feat] Unquantized Linear to nz and control all nz-cast (#3356)
### What this PR does / why we need it?
Currently, when executing to the Linear layer of models in vLLM-Ascend,
the weights format is ND in unquantized case and skipped ascend case.
This PR supplements the execution logic for Linear layer. We use a new
global variable: VLLM_ASCEND_ENABLE_NZ. When VLLM_ASCEND_ENABLE_NZ=1 and
CANN version is 8.3, the weights of the Linear layer will be converted
to FRACTAL_NZ, in both unquantized case and skipped ascend case. We also
use VLLM_ASCEND_ENABLE_NZ to control the existing NZ conversion, such as
w8a8-quantized case.

### Does this PR introduce _any_ user-facing change?
Add a new global variable VLLM_ASCEND_ENABLE_NZ. If you want to use NZ
format, you should set VLLM_ASCEND_ENABLE_NZ=1.

### 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: anon189Ty <Stari_Falcon@outlook.com>
2025-10-14 17:39:26 +08:00
realliujiaxu
31682961af [Feat] enable hierarchical communication for mc2 ops on A2 (#3015)
Currently, when in A2, setting the environment variables
`HCCL_INTRA_PCIE_ENABLE=1` and `HCCL_INTRA_ROCE_ENABLE=0` can reduce
cross-machine communication traffic and significantly improve
communication performance.

For more details, please refer to
[document](https://www.hiascend.com/document/detail/zh/Pytorch/710/apiref/torchnpuCustomsapi/context/torch_npu-npu_moe_distribute_dispatch_v2.md)

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

---------

Signed-off-by: realliujiaxu <realliujiaxu@163.com>
2025-10-13 16:13:17 +08:00
dsxsteven
847d12a389 [BugFix]Fix moe load problems in torchair when using dynamic eplb (#3381)
### What this PR does / why we need it?

When using dynamic eplb, moe load is not imported. We fix this problem
by modifying the return value of hidden states in torchair.

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

### How was this patch tested?
DeepseekV3 in A3.


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

---------

Signed-off-by: daishixun <dsxsteven@sina.com>
2025-10-13 11:38:57 +08:00
Wang Kunpeng
859e861d92 [main][quantization] Support deepseek w4a8 per-channel quantization (#3011)
### What this PR does / why we need it?
1.Support deepseek w4a8 per-channel quantization
2.The eager mode supports converting weights to the NZ format
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
#### How to get weights using Modelslim

##### Installation steps

git clone https://gitcode.com/Ascend/msit.git
cd msit/msmodelslim
bash install.sh

##### Generate w4a8 per-channel weights

cd /example/DeepSeek
Command reference: msmodelslim/example/DeepSeek/README.md

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

---------

Signed-off-by: Wang Kunpeng <1289706727@qq.com>
2025-09-27 21:01:16 +08:00
linfeng-yuan
d01fd1d1c3 [misc][torchair] fix bugs around deepseek mtp, enable_shared_expert_dp and use_cached_kv_cache_bytes (#3074)
### What this PR does / why we need it?
This miscellaneous​ contains several small fixes:
1) fix initialization and forward bugs of DeepseekMTPLayer with
`shared_expert_dp` enabled.
2) fix a tensor shape mismatches after o_proj caused by a work-aroud
change in NPUModelRunner.
3) avoid unnecessary decline of kv_cache memory (default: 64MB) with
`use_cached_kv_cache_bytes` disabled.
4) fall back `fused_moe_state` from `MC2` to `All2All` since the padding
logic of `mc2_mask` is incompatible with input hidden_states when
`shared_expert_dp` enabled.

Once this PR is merged, users can launch disaggregated_prefill
deployments (large_ep) with `deepseek_mtp` and `shared_expert_dp` as
`v0.9.1-dev` branch. The remaining problem of kv_cache tokens decline
compared to `v0.9.1-dev` will be resolved by
https://github.com/vllm-project/vllm-ascend/pull/3073.
 
### Does this PR introduce _any_ user-facing change?

No.
### How was this patch tested?
E2E vllm serving about deepseek_mtp with torchair graph mode and
`enable_shared_expert_dp` with eager mode. Large ep deployments are also
tested with this PR.


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

---------

Signed-off-by: linfeng-yuan <1102311262@qq.com>
2025-09-23 14:52:42 +08:00
linfeng-yuan
ffdd1a36e2 [bugfix][torchair] fix wasted NPU memory buffer allocation for quantized deepseek with unquantized MTP layer (#3068)
### What this PR does / why we need it?
While running quantized deepseek models with unquantized MTP layer, free
NPU memory abnormally decreases for `2*HCCL_BUFFSIZE` bytes. This
results from the wasted VRAM buffer allocation casued by calling
`dist.all_to_all_single` without correct device process group argument.

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

### How was this patch tested?
We run vllm online serving with quantized deepseek-r1 and unquantized
MTP layer, and observed that free_memory increased without redundat VRAM
buffer for HCCL communication op (all_to_all_single).

- vLLM version: v0.10.2
- vLLM main:
6d8246aaff

Signed-off-by: linfeng-yuan <1102311262@qq.com>
2025-09-22 14:06:43 +08:00
Angazenn
aeffe27b30 [Perf]set moe w2_weight default to be nz (#2842)
### What this PR does / why we need it?

This PR sets the default format of GMM w2_weight in w8a8_dynamic to be
NZ to improve performance.

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

No.

### How was this patch tested?


- vLLM version: main
- vLLM main:
e40827280b

---------

Signed-off-by: Angazenn <supperccell@163.com>
2025-09-11 21:40:54 +08:00
22dimensions
37f5a29cd4 [1/N][Refactor][Quantization] remove redundant quantizer class (#2680)
### What this PR does / why we need it?

AscendQuantizer/LLMQuantizer class is used to select quant method based
on quant config and some other arguments,
but it is more simple and clean replacing these classes with map. So i
remove them.

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

### How was this patch tested?

ut and e2e test


- vLLM version: v0.10.1.1
- vLLM main:
6997a25ac6

Signed-off-by: 22dimensions <waitingwind@foxmail.com>
2025-09-04 11:35:14 +08:00
Wang Yixuan
936c102105 [bugfix][refactor]fix torchair_w8a8 (#2569)
### What this PR does / why we need it?
torchair w8a8 and w4a8 Separate from fused_moe due to the refactor and
change for fused_moe

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

### How was this patch tested?
vLLM version: main
vLLM main:
ab9f2cfd19


- vLLM version: v0.10.1.1
- vLLM main:
69244e67e6

Signed-off-by: hust17yixuan <303660421@qq.com>
2025-08-28 09:10:31 +08:00
Wang Yixuan
20a7bc4b71 [3/N][refactor] refactoer quantization (#2504)
### What this PR does / why we need it?
Move torchair related qunatization section into torchair dir to make the
code clear. Next step we'll remove all torchair related code outside of
torchair quantization.

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

### How was this patch tested?
vLLM version: main
vLLM main:
ab9f2cfd19


- vLLM version: v0.10.1.1
- vLLM main:
959783fb99

Signed-off-by: hust17yixuan <303660421@qq.com>
2025-08-27 10:45:50 +08:00