18 Commits

Author SHA1 Message Date
LICO67373
71c21f76f5 [Refactor] Replace npu_ring_mla with FIA in MLA prefill (#5704)
### What this PR does / why we need it?

**Refactor: Replace npu_ring_mla with FIA in MLA prefill**

This PR refactors the MLA (Multi-Layer Attention) prefill implementation
by replacing `npu_ring_mla` with `npu_fused_infer_attention_score` (FIA)
operator, unifying the attention backend with the standard attention
implementation.

**Key changes:**

1. **Core prefill refactoring (`mla_v1.py`)**
- Replace `npu_ring_mla` with `npu_fused_infer_attention_score` in
`_forward_prefill` and `_compute_prefill_context`
   - Use TND layout with `softmax_lse_flag=True` for prefill attention
- Use `npu_attention_update` to merge multiple chunk outputs with LSE
(Log-Sum-Exp)
- Change `attn_mask` from `get_final_mla_mask()` to
`get_splitfuse_attn_mask()` for FIA compatibility

2. **Data type handling**
- Add automatic float16 → bfloat16 conversion (FIA with TND layout only
supports bfloat16)
   - Convert output back to original dtype after FIA computation

3. **Metadata optimization**
   - Pre-calculate `actual_seq_lengths_q` in `AscendMLAPrefillMetadata`
- Pre-calculate `chunk_actual_seq_lengths_kv_list` in
`ChunkedContextMetadata`
- Move `torch.cumsum` operations from forward pass to metadata building
phase

4. **CP compatibility (`mla_cp.py`)**
- Add `_ring_mla_mask_builder` to get `npu_ring_mla`-compatible masks
for Context Parallel scenarios
- Add `chunk_actual_seq_lengths_kv_list` field to
`CPChunkedContextMetadata`

**Why we need it:**
- **Backend unification**: Aligns MLA prefill with standard attention
implementation (`attention_v1.py`)
- **Better chunked context support**: FIA + `npu_attention_update`
provides native LSE-based output merging
- **Future compatibility**: Prepares for eventual `npu_ring_mla` removal
across the codebase

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

**No.** This is a pure refactoring with no functional changes - same
behavior, unified backend.

---
- Related issue: #5463 (item 7)
- vLLM version: v0.14.1

Signed-off-by: lico67373 <918688502@qq.com>
2026-03-16 10:33:09 +08:00
Ronald
c980e68d40 [Feature] support aclgraph for model runner v2 (#7110)
### What this PR does / why we need it?
This PR aims to support aclgraph for model runner v2, please see RFC
#5208. The PR contains these modifications:
- adapt to newest commit of vllm main branch.
- supply a unified interface of extra forward context for both model
runner v1 and model runner v2.
- implement graph mode for main model. 

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

### How was this patch tested?

- vLLM version: v0.16.0
- vLLM main:
4034c3d32e

---------

Signed-off-by: Ronald1995 <ronaldautomobile@163.com>
2026-03-13 09:11:46 +08:00
Nengjun Ma
66b60c9440 [Refact]Refact MLA/SFA weight prefetch to consist with moe weight prefetch (#6629)
### What this PR does / why we need it?
1. [Refact] Refact MLA/SFA weight prefetch to consist with moe weight
prefetch
2. Remove duplicated o_proj weight prefetch in forward for MLA/SFA

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

### How was this patch tested?

1) Performance result:
Perf test data:
*) MLA:

| | 1st test | 2nd test | Output Token Throughput(Avg) | Performance
improvement percentage |
| --- | --- | --- | --- | --- |
| o_proj duplicate prefetch | 11.9669 token/s | 12.0287 token/s |
11.9978 |
| o_proj no duplicate prefetch | 12.5594 token/s | 12.6216 token/s |
12.5905 | 4.94%| |

single layer performace improve: 5%~8%

*) SFA:

| | 1st test | 2nd test | Output Token Throughput(Avg) | Performance
improvement percentage |
| --- | --- | --- | --- | --- |
| o_proj duplicate prefetch | 13.0523 token/s | 13.1084 token/s |
13.08035 | |
| o_proj no duplicate prefetch | 13.9844 token/s | 14.1678 token/s |
14.0761 | 7.6% |

- vLLM version: v0.15.0
- vLLM main:
d7e17aaacd

---------

Signed-off-by: leo-pony <nengjunma@outlook.com>
2026-02-10 14:14:37 +08:00
Qiu
749e24f81e [bugfix] align max_num_batched_tokens with tp*pcp when using FLASHCOMM1 (#6000)
### What this PR does / why we need it?
Align max_num_batched_tokens with tp*pcp when using FLASHCOMM1 to avoid
assert error in `NPUModelRunner._dummy_run`.

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

---------

Signed-off-by: QiuChunshuo <qiuchunshuo@huawei.com>
2026-01-23 14:19:49 +08:00
dsxsteven
8378bc28b0 [Misc] Remove CP Redundant Variables after FIA operator enables for CANN 8.5 (#6013)
### What this PR does / why we need it?
PCP/DCP splits the kv-cache onto different cards. After introducing the
parameter cp-kv-cache-interleave-size, the first size tokens will be
cached at Card 0, and so on.
However, if there are too few tokens, some cards will not store the
key-value pairs, resulting in values ​​of 0, corrupted values, and
precision issues. Currently, additional operations are introduced to
avoid this precision problem.

After we integrate FIA operator in mla_cp._forward_decode and CANN
updates to 8.5.0, we now can remove these additional operations.
### Does this PR introduce _any_ user-facing change?

### How was this patch tested?
passed all CI by CANN 8.5.0
- vLLM version: v0.13.0
- vLLM main:
2c24bc6996

Signed-off-by: dsxsteven <dsxsteven@sina.com>
Signed-off-by: dsxsteven <36877507+dsxsteven@users.noreply.github.com>
2026-01-23 14:13:12 +08:00
Bai Yongbin
7f91ac2649 [CP&SP] Integrate FIA operator in mla_cp._forward_decode (#5641)
### What this PR does / why we need it?
Replace the npu_multi_head_latent_attention with FIA operator in
mla_cp.py _forward_decode.
Adjust mla_attn_dpc_pcp in acl_graph.py

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

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

---------

Signed-off-by: 白永斌 <baiyongbin3@h-partners.com>
Signed-off-by: Bai Yongbin <845473182@qq.com>
Signed-off-by: tongyuzhou <t00886357@china.huawei.com>
Co-authored-by: 白永斌 <baiyongbin3@h-partners.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
Co-authored-by: tongyuzhou <t00886357@china.huawei.com>
2026-01-22 20:02:30 +08:00
LICO67373
380f089fbf [Refactor] Fix AttentionMaskBuilder singleton and remove redundant pcp_prefill_mask (#4870)
## What this PR does / why we need it?

This PR fixes the `AttentionMaskBuilder` singleton initialization issue
introduced in PR #4779 and removes the unused `pcp_prefill_mask` field.

### Background

After PR #4779 made `AttentionMaskBuilder` a singleton with `@singleton`
decorator, the class constructor now requires a `device` parameter.
However, two initialization sites were still using the old parameterless
constructor, causing failures.

### Changes

1. **Fix singleton initialization**
- Fixed `AttentionMaskBuilder()` → `AttentionMaskBuilder(self.device)`
in `AscendMLAMetadataBuilder.__init__()`
- Fixed `AttentionMaskBuilder()` → `AttentionMaskBuilder(self.device)`
in `AscendAttentionMetadataBuilder.__init__()`

2. **Remove unused field**
- Removed `pcp_prefill_mask` field from
`AscendPrefillContextParallelMetadata` (never used in codebase)
   - Updated related test assertions

### Related

- Issue #5463
- PR #4779 (Unify all mask generation methods)
- PR #5389 (Make AttentionMaskBuilder singleton)

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

No. This is an internal refactoring.

## How was this patch tested?

-  Local testing: No linter errors
-  Unit tests for attention modules verified
-  CI pipeline

Signed-off-by: lico67373 <918688502@qq.com>
Co-authored-by: weijinqian0 <1184188277@qq.com>
2026-01-07 17:09:52 +08:00
wangxiyuan
1112208052 [Refactor] Cleanup platform (#5566)
### What this PR does / why we need it?
1. add `COMPILATION_PASS_KEY` constant
2. clean up useless platform interface `empty_cache`, `synchronize`,
`mem_get_info`, `clear_npu_memory`
3. rename `CUSTOM_OP_REGISTERED` to `_CUSTOM_OP_REGISTERED`
4. remove uesless env `VLLM_ENABLE_CUDAGRAPH_GC`

NPUPlatform is the interface called by vLLM. Do not call it inner
vllm-ascend.

### Does this PR introduce _any_ user-facing change?
This PR is just  a cleanup. All CI should pass.

### How was this patch tested?

- vLLM version: v0.13.0
- vLLM main:
7157596103

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
2026-01-07 09:25:55 +08:00
wujinyuan1
4a3663327b [Refactor]7/N Extract common code to common_cp (#5490)
RFC: https://github.com/vllm-project/vllm-ascend/issues/4629
Reason:
Eliminate duplicate code for two file(mla_cp.py attention_cp.py) to
common_cp.py.

vLLM version: 0.13.0rc3
vLLM main:
ad32e3e19c

vLLM version: release/v0.13.0
vLLM main:
5fbfa8d9ef

- vLLM version: v0.13.0
- vLLM main:
5326c89803

---------

Signed-off-by: wujinyuan1 <wjy9595@qq.com>
Signed-off-by: wujinyuan1 <wujinyuan1@huawei.com>
Co-authored-by: wujinyuan1 <wjy9595@qq.com>
2026-01-05 17:41:12 +08:00
pichangping
50e7934415 MLA prefill preformance optimization (#5456)
### 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.

- vLLM version: v0.13.0
- vLLM main:
5326c89803

---------

Signed-off-by: pichangping <1337510399@qq.com>
2026-01-05 11:41:59 +08:00
Qiu
96775a27a8 [refactor](UT,PCP,DCP) refactor pcp&dcp patches in UTs (#5505)
### What this PR does / why we need it?
Refactor PCP & DCP patches in UTs: Merge and reuse communication groups
and communication function patches to reduce code duplication.
### Does this PR introduce _any_ user-facing change?
No
- vLLM version: v0.13.0
- vLLM main:
45c1ca1ca1

Signed-off-by: QiuChunshuo <qiuchunshuo@huawei.com>
2026-01-05 09:05:45 +08:00
wujinyuan1
23169021d9 [Refactor]6/N Extract common code of class AscendMLAImpl (#5314)
RFC: https://github.com/vllm-project/vllm-ascend/issues/4629
Reason:
Eliminate duplicate code for two file(mla_v1.py mla_cp.py) of IMPL
classes.

vLLM version: 0.13.0rc3
vLLM main:
ad32e3e19c


- vLLM version: release/v0.13.0
- vLLM main:
5fbfa8d9ef

---------

Signed-off-by: wujinyuan1 <wjy9595@qq.com>
Co-authored-by: wujinyuan1 <wjy9595@qq.com>
Co-authored-by: weijinqian0 <1184188277@qq.com>
2025-12-28 10:40:45 +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
wujinyuan1
7ff1db4b84 [Refactor]5/N Extract common code of mla_v1.py & extract mla_cp (#5097)
RFC: https://github.com/vllm-project/vllm-ascend/issues/4629
Reason:
The functions related to Cp differ significantly from those of normal
MLA-Attention, but the coupling is quite severe.

Steps:
1)Extract common code AscendMLAMetadataBuilder.build to 4 functions: 
build_prefill_metadata, build_decode_metadata,build_cp_metadata,
build_chunked_metadata

todo:
1)refactor function _compute_prefill_context;
2)refactor function _mla_preprocess,_mla_decode_preprocess
3)Extract public data and processing functions from the attention_cp.py
and mla_cp.py files to the common_cp file.

vLLM version: 0.13.0rc3
vLLM main:
ad32e3e19c

- vLLM version: 0.13.0rc3
- vLLM main:
ad32e3e19c

---------

Signed-off-by: wujinyuan1 <wjy9595@qq.com>
Signed-off-by: wujinyuan1 <wujinyuan1@huawei.com>
Co-authored-by: wujinyuan1 <wjy9595@qq.com>
Co-authored-by: weijinqian0 <1184188277@qq.com>
2025-12-24 10:25:19 +08:00
Feng Liu
e117b3d693 [Perf] vectorize PCP/DCP loops in mla_v1.py (#5003)
### What this PR does / why we need it?
- Replace nested PCP/DCP Python loops with fully vectorized tensor
operations

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

---------

Signed-off-by: F.Liu <liufeng248@huawei.com>
Co-authored-by: F.Liu <liufeng248@huawei.com>
2025-12-22 11:06:30 +08:00
Feng Liu
eda3cabf5b [UT] add pcp&dcp UT for mla_cp (#4953)
### What this PR does / why we need it?
Add UT of mla_cp, which include:
- test_compute_prefill_context_with_dcp_pcp
- test_reorg_kvcache_with_dcp_pcp
- test_out_lse_reshape
- test_npu_attention_update_with_dcp_pcp
- test_attention_with_mask_and_nomask_with_dcp_pcp
- test_process_attn_out_lse_with_dcp_pcp
- test_forward_prefill_cp_with_dcp_pcp

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

---------

Signed-off-by: F.Liu <liufeng248@huawei.com>
Co-authored-by: F.Liu <liufeng248@huawei.com>
2025-12-17 16:19:27 +08:00
zengzengran
6029bea480 [UT]add pcp dcp ut (#4949)
### What this PR does / why we need it?
Adding UT for DCP/PCP

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

Signed-off-by: zengran <zengran2@huawei.com>
2025-12-15 18:41:38 +08:00