Commit Graph

12 Commits

Author SHA1 Message Date
pu-zhe
85e33941e8 [Feat.]: 310p support MOE models (#6530)
### What this PR does / why we need it?
This pull request integrates comprehensive support for Mixture of
Experts (MoE) models on the Ascend 310P device within the vllm-ascend
framework. It achieves this by introducing specialized modules for
expert selection, fused MoE layers, and optimized all-gather
communication. The changes also refine existing NPU operations, making
them more consistent and efficient for 310P, ultimately enhancing the
performance and compatibility of MoE models on this hardware.

Highlights
310P MoE Support: Introduces dedicated implementations for Mixture of
Experts (MoE) models on Ascend 310P devices, including new modules for
expert selection, fused MoE layers, and communication.
All-Gather Communication: Enforces the use of ALLGATHER communication
for MoE operations on 310P, optimizing data transfer and leveraging
NPU-specific token dispatching.
Simplified NPU Operations: Removes conditional type casting for
npu_swiglu and enables custom rotary embedding kernels unconditionally,
suggesting improved native support for 310P.
New MoE Classes Registered: Registers AscendFusedMoE310 and
AscendSharedFusedMoE310 to integrate 310P-specific MoE layers into the
system's custom operation registry.

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

### How was this patch tested?
offline test and server test, with qwen3-30b-a3b,tp/ep 4 on 310p

- vLLM version: v0.15.0
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.15.0

---------

Signed-off-by: pu-zhe <zpuaa@outlook.com>
2026-02-06 10:30:56 +08:00
Nengjun Ma
78fad4e348 [Refactor] MLP weight prefetch to consistency with MoE Model's prefetching in terms of code and usage (#6442)
### What this PR does / why we need it?
Refactor MLP weight prefetch to consistency with MoE Model's prefetching
in terms of code and usage.
Environments VLLM_ASCEND_ENABLE_PREFETCH_MLP,
VLLM_ASCEND_MLP_DOWN_PREFETCH_SIZE and
VLLM_ASCEND_MLP_GATE_UP_PREFETCH_SIZE is removed, usage as following:

--additional-config '{"weight_prefetch_config": { "enabled": true,
"prefetch_ratio": {"mlp": { "gate_up": 1.0, "down": 1.0} }}}'

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

### How was this patch tested?

- vLLM version: v0.14.1
- vLLM main:
dc917cceb8

---------

Signed-off-by: leo-pony <nengjunma@outlook.com>
2026-02-04 09:08:18 +08:00
Shaoxu Cheng
39e77fb9e4 [Feat.]: support 310p w8a8 (#6454)
### What this PR does / why we need it?
Introduced 310P W8A8 Quantization Support: New modules and methods have
been added to enable W8A8 static quantization specifically for the
Ascend 310P platform.
Platform-Specific Quantization Configuration Loading: The system now
dynamically loads the appropriate quantization configurations
(AscendCompressedTensorsConfig, AscendModelSlimConfig) based on whether
the current hardware is an Ascend 310P device.
Implemented AscendW8A8LinearMethod310P: A dedicated linear quantization
method for 310P is provided, handling the specifics of weight and
activation quantization, including input parameter broadcasting and
weight data manipulation.
Extended AscendModelSlimConfig for 310P: A specialized configuration
class for 310P integrates the new W8A8 linear method for both standard
linear layers and vocabulary parallel embeddings, ensuring proper
quantization application.

- vLLM version: v0.14.1
- vLLM main:
dc917cceb8

---------

Signed-off-by: Tflowers-0129 <2906339855@qq.com>
Signed-off-by: Shaoxu Cheng <2906339855@qq.com>
2026-02-03 14:13:06 +08:00
debuger
c1618a0427 [Bugfix]Fix the compatibility issue of may_reinitialize_input_batch (#6290)
### What this PR does / why we need it?
Added a check in the may_reinitialize_input_batch method to verify
whether the backend implements the get_supported_block_size method

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

### How was this patch tested?
Only a few lines of code within the methods were modified, and the
format check test has been passed.
- vLLM version: v0.14.1
- vLLM main:
dc917cceb8

---------

Signed-off-by: Debuuuuger <huangzr@cmbchina.com>
Signed-off-by: debuger <102402761+huangazazaz@users.noreply.github.com>
Signed-off-by: Debuuuuger <12110718@mail.sustech.edu.cn>
Co-authored-by: Debuuuuger <huangzr@cmbchina.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
2026-02-02 19:16:26 +08:00
Shaoxu Cheng
460ea88276 [Refact.]: Refactor some leftover implementations of 300I DUO in the main branch. (#6425)
### What this PR does / why we need it?
- Replace the RoPE operator implementation.
- Refactor some leftover implementations of 300I DUO in the main branch.

### Does this PR introduce _any_ user-facing change?
NA
### How was this patch tested?

- vLLM version: v0.14.1
- vLLM main:
dc917cceb8

---------

Signed-off-by: Tflowers-0129 <2906339855@qq.com>
2026-02-02 16:12:04 +08:00
Shaoxu Cheng
9fadc8df4f [Fixbugs]: fix refactor cause to 310p chunkprefill error (#6340)
Adapt modelrunner refactor change to make 310p work

- vLLM version: v0.14.1
- vLLM main:
dc917cceb8

Signed-off-by: Tflowers-0129 <2906339855@qq.com>
2026-01-28 16:41:32 +08:00
pu-zhe
57fd6e4bd9 [Refact.]: refactoring 310p-kv cache allocator, align with main branch (#6270)
### What this PR does / why we need it?
refactoring 310p-kv cache allocator, align with main branch

vLLM version: v0.14.0
vLLM main: https://github.com/vllm-project/vllm-ascend/pull/6270
Qwen2.5-7B E2E Test

---------

Signed-off-by: pu-zhe <puzhe1@h-partners.com>
Signed-off-by: pu-zhe <zpuaa@outlook.com>
Co-authored-by: pu-zhe <puzhe1@h-partners.com>
2026-01-27 16:26:48 +08:00
Nengjun Ma
f910cebe04 [Doc] 310P Documents update (#6246)
### What this PR does / why we need it?
310P support guides updates, as currently has supported in main branch.

---------

Signed-off-by: leo-pony <nengjunma@outlook.com>
2026-01-26 14:33:21 +08:00
Li Wang
c26ad78f86 [CI][lint] Add rule codespell back (#6236)
### What this PR does / why we need it?
After removing codepsell a while, we discovered that typo had a problem
correctly recognizing certain misspelled words, so I suggested adding it
back.

- vLLM version: v0.14.1
- vLLM main:
d68209402d

---------

Signed-off-by: wangli <wangli858794774@gmail.com>
2026-01-26 14:12:33 +08:00
Shaoxu Cheng
fbae41697e [310P]: refactoring for 310p kvcache and some ops class (#6117)
### What this PR does / why we need it?
* Refactor the LayerNorm and activation operator classes to decouple the
310P device implementation from the main branch.
* Refactor `mm_encoder_attention` on 310P to use the
`torch_npu._npu_flash_attention_unpad` operator.
* Refactor the QKV inputs in the prefill stage of `attention_v1` on 310P
so they are no longer padded to 16× alignment.
* Refactor `model_runner` on 310P to align the KV-cache initialization
logic with the mainline implementation.

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

### How was this patch tested?
use the e2e tests.

- vLLM version: v0.13.0
- vLLM main:
d68209402d

---------

Signed-off-by: Tflowers-0129 <2906339855@qq.com>
2026-01-24 20:34:29 +08:00
Li Wang
484e7c59dc [CI] optimize lint term (#5986)
### What this PR does / why we need it?
This patch purpose to optimize the lint check term. The main idea is to
reduce unnecessary installation time.
1. The installation of vllm is not must, only append the path of vllm
src to the `PATHONPATH` is effective
2. This installation of `requirements-dev.txt` is not must, we have a
pre-built image `quay.io/ascend-ci/vllm-ascend:lint` with all the
requirements installed in advance.
**NOTE**: the conditions for triggering image builds are: 1).Daily
scheduled build; 2) Build when requirements are modified; 3) Manual
build. This ensures that the dependencies in our image are up-to-date to
the greatest extent possible.
3. The `mypy` was separated from the `pre-commit` hook for performance
reasons; we found that integrating `mypy` into the `pre-commit` hook
resulted in poor performance.
4. Reduce the CPU core consumption from 16 -> 8

### Does this PR introduce _any_ user-facing change?
The end-to-end lint time was optimized from 20min/per PR to 8min/per PR
### How was this patch tested?

- vLLM version: v0.13.0
- vLLM main:
2c24bc6996

---------

Signed-off-by: wangli <wangli858794774@gmail.com>
2026-01-22 15:46:59 +08:00
Shaoxu Cheng
1ffca8673f [Feature]: Support 310P device run qwen2.5/3 dense and qwen2.5vl models (#5776)
### What this PR does / why we need it?
Add basic 310p support. Only dense models work with eager mode now.

- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef

---------

Signed-off-by: Tflowers-0129 <2906339855@qq.com>
Signed-off-by: Shaoxu Cheng <2906339855@qq.com>
2026-01-17 11:49:18 +08:00