### What this PR does / why we need it?
Remove unused layers assignment in mooncake connector
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
by nightly
Signed-off-by: liziyu <liziyu16@huawei.com>
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### What this PR does / why we need it?
Fix kv pool CLI flag typo and formatting
### Does this PR introduce _any_ user-facing change?
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Signed-off-by: Pz1116 <zpbzpb123123@gmail.com>
### What this PR does / why we need it?
change --compilation_config to --compilation-config
change --max-model-len 133008 to --max-model-len 131072 for matching
128k
### Does this PR introduce _any_ user-facing change?
No
Signed-off-by: Yang Yuxi <907276627@qq.com>
### What this PR does / why we need it?
fix tl.extract_slice and tl.insert_slice to extract_slice and
insert_slice from torch_utils
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
---------
Signed-off-by: wangx700 <wangxin700@huawei.com>
### What this PR does / why we need it?
Fix the issue where the Mooncake connector does not handle the MTP layer
KV cache when TP is unbalanced.
backport: #8540
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
by nightly
Signed-off-by: liziyu <liziyu16@huawei.com>
cherry-pick https://github.com/vllm-project/vllm-ascend/pull/8539
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### What this PR does / why we need it?
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Due to end-to-end testing , three optimization points for the decode
scenario have been reverted in dispatch_ffn_combine kernel.
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---------
Signed-off-by: l00893928 <liuquanlu@huawei.com>
Co-authored-by: l00893928 <liuquanlu@huawei.com>
### What this PR does / why we need it?
This PR updates the `MOONCAKE_TAG` version from `v0.3.8.post1` to
`v0.3.9` across all Dockerfiles.
Signed-off-by: wangli <wangli858794774@gmail.com>
### What this PR does / why we need it?
Fix the issue where a request does not return due to a specific NPU on
node D having no transmission tasks in the scenario where node D is
enabled with DCP.
### Does this PR introduce _any_ user-facing change?
### How was this patch tested?
by nightly
Signed-off-by: liziyu <liziyu16@huawei.com>
Backport of #7882 to releases/v0.18.0. Adds aime2025 benchmark test for
DeepSeek-V3.2-W8A8 EP with disaggregated prefill on A3 (4-node, 16 NPUs
per node, accuracy benchmark baseline 66.67%).
Signed-off-by: guozr <guozr1997@hotmail.com>
Co-authored-by: guozr <guozr1997@hotmail.com>
### What this PR does / why we need it?
This PR updates the model deployment tutorial template to include a
requirement for authors to add a comment when code examples contain
version numbers. This ensures that users are prompted to use the version
appropriate for their specific environment.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
N/A (Documentation change)
---------
Signed-off-by: herizhen <1270637059@qq.com>
Signed-off-by: herizhen <59841270+herizhen@users.noreply.github.com>
### What this PR does / why we need it?
This PR enables synchronization for the `PIECEWISE` runtime mode in ACL
graph replay. Previously, synchronization was only performed in `FULL`
mode. However, `PIECEWISE` mode also requires this barrier to ensure
that parameter updates are completed before the graph is replayed,
preventing accuracy loss.
The logic is also corrected to skip synchronization specifically for
EAGLE draft models, as intended.
Fixes #
### Does this PR introduce _any_ user-facing change?
N/A
### How was this patch tested?
CI passed.
---------
Signed-off-by: 1zzk <785396250@qq.com>
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### What this PR does / why we need it?
Update CI for GLM-5 configuration on vllm-ascend/releases/v0.18.0 branch
在0.18.0版本上对glm5-w4a8做测试
### Does this PR introduce _any_ user-facing change?
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---------
Signed-off-by: yangjiuhua <y00845194@china.huawei.com>
Co-authored-by: yangjiuhua <y00845194@china.huawei.com>
### What this PR does / why we need it?
The env `VLLM_ASCEND_ENABLE_FUSED_MC2` should only enabled in the
decoder node during Prefill-Decode Disaggregation scenario
---------
Signed-off-by: wangli <wangli858794774@gmail.com>
What this PR does / why we need it?
switch Ascend conv3d forward_oot to use forward_native and add ut
Does this PR introduce any user-facing change?
No
How was this patch tested?
by CI
---------
Signed-off-by: zouyizhou <zouyizhou@huawei.com>
…(#8405)"
This reverts commit b992b11545.
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### What this PR does / why we need it?
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Signed-off-by: l00893928 <liuquanlu@huawei.com>
Co-authored-by: l00893928 <liuquanlu@huawei.com>
### What this PR does / why we need it?
GDN Attention uses FIA's query_start_loc (padded), which may cause
conv1d update errors under high concurrency when dp > 1, and this PR is
to make GDN use its own query_start_loc (unpadded).
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
- vLLM version: v0.18.0
Signed-off-by: Wangbingjie <wangbj1207@126.com>
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Signed-off-by: l00893928 <liuquanlu@huawei.com>
Co-authored-by: l00893928 <liuquanlu@huawei.com>
Reverts vllm-project/vllm-ascend#8133
- Reversion of Logic: This pull request reverts the changes introduced
in a previous commit that attempted to handle dimension mismatches
during SP padding.
Signed-off-by: Wangbingjie <wangbj1207@126.com>
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### What this PR does / why we need it?
- Enforce recompute scheduler only in PD-disaggregated mode.
- Enforce balance scheduling only in PD-mixed mode.
- Enforce fused MC2 only on PD-disaggregated D-side (kv_consumer).
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### Does this PR introduce _any_ user-facing change?
No
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### How was this patch tested?
By ci
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---------
Signed-off-by: wangxiaoteng <wangxiaoteng@huawei.com>
### What this PR does / why we need it?
1. there is no synchronization between steps. However, in async
scheduling with aclgraph, it is possible that the CPU's record event for
the current iteration completes before the previous iteration's graph
execution has finished. If cpu is fast enough, device will hang on
event_wait in interation i+1 (assume that event_record is executed
immediately on update stream of device).
2. Under ENPU, eagle proposers also need to follow event.record first,
and then event.Wait.
### Does this PR introduce _any_ user-facing change?
N/A
### How was this patch tested?
---------
Signed-off-by: 1zzk <785396250@qq.com>
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### What this PR does / why we need it?
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and bug description.
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-->show known issues for Qwen3.5-397B
### Does this PR introduce _any_ user-facing change?
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### How was this patch tested?
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---------
Signed-off-by: 李少鹏 <lishaopeng21@huawei.com>
Cherry-picked from https://github.com/vllm-project/vllm-ascend/pull/7858
### What this PR does / why we need it?
This PR fixes a `RuntimeError` (dimension mismatch) that occurs when
Sequence Parallelism (SP) is enabled and the padding added for SP causes
`num_tokens_padded` to differ from `num_tokens_unpadded`. In such cases,
`_pad_query_start_loc_for_fia` adds a dummy request, increasing
`num_reqs_padded`. This mismatch between the actual number of requests
and the padded number of requests leads to errors in downstream token
count computations (e.g., `compute_num_computed_tokens`).
The fix modifies the restrictive condition `num_tokens_padded ==
num_tokens_unpadded` when reverting the dummy request padding if SP is
enabled, as SP padding is handled by stripping it after communication
and should not be treated as an additional request in the attention
metadata.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
vLLM version: v0.18.0
vLLM-Ascend version: releases/v0.18.0
Signed-off-by: Wangbj127 <wangbj1207@126.com>
### What this PR does / why we need it?
PR #8220 in v0.18.0
In a previous PR #7843 , the o_proj layer of GLM-5 was reverted to TP
(Tensor Parallel) splitting when flashcomm1 was enabled. However, this
was a temporary workaround and did not address the root cause of the
precision issues observed in the o_proj layer under flashcomm1.
I am working on a definitive fix for this issue. Currently, a clear bug
has been identified in
880e20fdde/vllm_ascend/quantization/methods/w8a8_static.py (L124):
during quantized matrix multiplication, quant_bias is not added if
tp_rank > 0. In the flashcomm1 scenario, all ranks actually require the
addition of quant_bias, meaning tp_rank=0 should be passed to ensure the
bias is applied correctly.
This PR aims to resolve this logic error and fix the underlying
precision issue.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
glm5 e2e test
---------
Signed-off-by: zjks98 <zhangjiakang4@huawei.com>
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: triomino <15924998+triomino@users.noreply.github.com>
Co-authored-by: zjks98 <zhangjiakang4@huawei.com>
### What this PR does / why we need it?
This PR is partially cherry-picked from #8172.
This PR aims to fix mismatched capture sizes after rounding operations
when using sp or speculative. The reason is that original
`self.cudagraph_capture_sizes` is no longer updated and remains as the
initial sizes. Now we use `self.cudagraph_dispatcher.get_capture_descs`
to the get up-to-date sizes.
### Does this PR introduce _any_ user-facing change?
N/A
### How was this patch tested?
by ci
Signed-off-by: Zetong Li <slippersss@126.com>
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### What this PR does / why we need it?
This PR updates the documentation to replace specific hardware terms
(e.g., HBM, 910B, 310P) with more generic or branded terms (e.g.,
on-chip memory, Atlas inference products) to comply with sensitive word
requirements.
### Does this PR introduce _any_ user-facing change?
no
### How was this patch tested?
---------
Signed-off-by: herizhen <1270637059@qq.com>
Signed-off-by: herizhen <59841270+herizhen@users.noreply.github.com>
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### What this PR does / why we need it?
## Problem
In PD-disaggregated serving with `mooncake_connector` and
`VLLM_ASCEND_BALANCE_SCHEDULING=1`, requests may enter
`WAITING_FOR_REMOTE_KVS` and never be promoted back to runnable state
after remote KV transfer finishes.
The issue is in `BalanceScheduler`'s handling of
`WAITING_FOR_REMOTE_KVS` requests. The current code treats
`_update_waiting_for_remote_kv()` as if it returns a boolean readiness
flag:
```python
is_ready = self._update_waiting_for_remote_kv(request)
if is_ready:
...
else:
...
```
### Does this PR introduce _any_ user-facing change?
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Signed-off-by: Pz1116 <zpbzpb123123@gmail.com>
### What this PR does / why we need it?
This PR backports the DSA-CP PD role gating fix to `releases/v0.18.0`.
The existing helper logic on the release branch does not handle the PD
mixed-role case correctly when deciding whether layer sharding or TP
`o_proj` handling should be enabled. Layer sharding should only run on
the P-side instance, while TP `o_proj` handling should stay enabled for
normal non-PD deployments and for the PD mixed-role (`kv_both`)
instance. This patch makes those conditions explicit and adds unit
coverage for the allowed and disallowed combinations, including the
DSA-CP-disabled path.
Such wrong condition lead to **vllm serve failures** in case: **FC1 +
PD-colocated KV pooling + no layer_sharding**, specifically causing:
1. insufficient Available KV cache memory
2. o_proj shape error in sfa_v1 attention module
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
E2E test with dsv32 + FC1 + FULL_DECODE_ONLY +
kv_transfer_config(kv_both) + no layer_sharding
---------
Signed-off-by: chenchuw886 <chenchuw@huawei.com>
Co-authored-by: chenchuw886 <chenchuw@huawei.com>
### What this PR does / why we need it?
This PR improves the readability of the documentation by fixing typos,
correcting command extensions, and fixing broken links in the Chinese
README.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Documentation changes only.
---------
Signed-off-by: sunshine202600 <sunshine202600@163.com>
### What this PR does / why we need it?
This PR implements the `AscendW8A8DynamicLinearMethod310` quantization
scheme specifically for 310P hardware. It includes the logic for weight
retrieval, per-channel parameter generation, and the application of
dynamic quantization using NPU-specific kernels. Additionally, it
updates `ShardedStateLoader310` to handle quantization configurations
more robustly when generating parameter type maps.
Feedback from the review identified two critical issues in the
implementation:
1. The tensor squeezing logic in the `apply` method incorrectly handles
2D inputs, which may lead to shape mismatches in subsequent layers.
2. The weight tensor in `process_weights_after_loading` is transposed
after being converted to the private NZ format; the transpose operation
should be performed on the ND tensor before conversion to ensure correct
physical layout.
cherry-pick from : #7546#7725
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
New unit tests were added in
`tests/ut/_310p/quantization/test_w8a8_dynamic_310.py` to verify the
quantization method, and
`tests/ut/_310p/test_sharded_state_loader_310p.py` was updated to test
the state loader changes.
---------
Signed-off-by: csoulnd <daidaicurry@foxmail.com>
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For the ENPU scenario, it is required that device events follow the
principle of "record first, wait later", otherwise the inference process
may become stuck. However, in the current model_forward function,
event.wait precedes event.record. Therefore, for the ENPU scenario,
graph parameter updates should be performed before model execution.
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N/A
### How was this patch tested?
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---------
Signed-off-by: 1zzk <785396250@qq.com>
Signed-off-by: 1kzk <785396250@qq.com>
Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>
### What this PR does / why we need it?
This PR backports the CPU binding locale normalization fix from #7274 to
`releases/v0.18.0`, including the follow-up review fixes already applied
on `main`.
The change forces `LC_ALL`, `LANG`, and `LC_MESSAGES` to `C` before
spawning subprocesses in `vllm_ascend.cpu_binding.execute_command()`, so
parser-dependent command output stays stable on localized systems. It
also handles `subprocess.TimeoutExpired` by killing the child process
before collecting output, and updates the existing unit tests to keep
command-argument coverage while adding timeout-path coverage.
Fixes#6992
### Does this PR introduce _any_ user-facing change?
Yes.
Users running CPU binding on non-English OS environments should now get
consistent English subprocess output for parser-dependent commands,
avoiding failures caused by inherited locale settings.
### How was this patch tested?
- Updated the existing unit tests in
`tests/ut/device_allocator/test_cpu_binding.py` to assert the locale
environment, retain command argument coverage, and cover the timeout
cleanup path.
- Attempted to run targeted pytest cases locally, but the pytest
invocation did not complete normally in this environment, so I could not
record a clean passing run here.
Attribution:
- Co-authored-by: stdjhs <1601599324@qq.com>
- Signed-off-by: chenchuw886 <chenchuw@huawei.com>
Signed-off-by: chenchuw886 <chenchuw@huawei.com>
Co-authored-by: chenchuw886 <chenchuw@huawei.com>
Co-authored-by: stdjhs <1601599324@qq.com>
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### What this PR does / why we need it?
ref:https://github.com/vllm-project/vllm-ascend/issues/8184
following https://github.com/vllm-project/vllm/pull/31057, add
`requires_piecewise_for_cudagraph` for `AscendStoreConnector`
### Does this PR introduce _any_ user-facing change?
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Signed-off-by: Pz1116 <zpbzpb123123@gmail.com>
### What this PR does / why we need it?
Fix a bug in the GLM tool call parser where the `function.name` field
was incorrectly included in the final (non-first) chunks of streaming
tool calls.
Per OpenAI streaming semantics, `id`, `type`, and `function.name` must
only appear in the **first** chunk for a given tool call index. When
`_create_remaining_args_delta` was called for continuing/finishing
chunks, it was incorrectly reading the function name from
`delta_message.tool_calls` and re-emitting it, causing clients to see a
duplicate/extra function name in the final chunk.
**Root cause**: The original code always looked up the tool call in
`delta_message.tool_calls` to get the name, id, and type — even when
this was not the first chunk being streamed. This caused the function
name to appear again in the final argument-completion chunk.
**Fix**:
- Track whether arguments have already been streamed
(`already_streamed_args`) for each tool call index.
- Only populate `fallback_tool_call_id`, `fallback_tool_call_type`, and
`fallback_tool_call_name` when `already_streamed_args` is empty (i.e.,
this is genuinely the first chunk).
- Refactored `_create_remaining_args_delta` to omit header fields
entirely when all fallback values are `None`, which is the correct
behavior for continuing/finishing chunks.
### Does this PR introduce _any_ user-facing change?
Yes. Clients consuming the streaming tool call response will no longer
receive a duplicate `function.name` in the final chunk. This fixes
incorrect behavior visible in the OpenAI-compatible streaming API output
for GLM models using tool calls.
### How was this patch tested?
- Code review and logic analysis of the streaming tool call path in
`patch_glm_tool_call_parser.py`.
- Existing unit tests in
`tests/ut/platform/test_patch_glm_tool_call_parser.py`.
---------
Signed-off-by: chen-weipeng12 <chen-weipeng12@noreply.gitcode.com>
Signed-off-by: chenweiqiang11 <chenweiqiang11@noreply.github.com>
Co-authored-by: chen-weipeng12 <chen-weipeng12@noreply.gitcode.com>
### What this PR does / why we need it?
Adds a `check_rank0_process_count` validation step to the
DeepSeek-R1-W8A8-HBM nightly single-node test.
The check verifies that after the server starts, there is **exactly 1**
`vllm serve` process running on rank0. This guards against the
regression fixed in #8041 (extra NPU context leaking on device 0),
ensuring it does not silently reappear in future releases.
#### Changes
-
**`tests/e2e/nightly/single_node/models/scripts/test_single_node.py`**:
Add `run_check_rank0_process_count` async handler. It calls `npu-smi
info` for diagnostics, then uses `psutil` to assert exactly one `vllm
serve` process exists on rank0.
-
**`tests/e2e/nightly/single_node/models/configs/DeepSeek-R1-W8A8-HBM.yaml`**:
Register `check_rank0_process_count` in the `test_content` list for the
HBM test case.
Signed-off-by: hfadzxy <starmoon_zhang@163.com>
### What this PR does / why we need it?
This PR is cherry-pick from #8263.
This PR aims to fix short prompt problem. The root cause can be found in
#8029. Since the previous pr may miss mixed long and short prompt batch,
after discussion, we decide to add PrefillNoCache state in mla
_forward_decode now instead.
Signed-off-by: Zetong Li <slippersss@126.com>
### What this PR does / why we need it?
This PR improves the validation of `max_cudagraph_capture_size` by
comparing it against the potential maximum tokens required for decoding,
derived from the scheduler configuration. It introduces a warning to
alert users when the capture size might be insufficient for the
workload, which could lead to suboptimal performance.
ref: #8227
### Does this PR introduce _any_ user-facing change?
Yes, a warning log is added when the `max_cudagraph_capture_size` is
smaller than the potential decode workload.
---------
Signed-off-by: QiuChunshuo <qiuchunshuo@huawei.com>
### What this PR does / why we need it?
This PR fixes a service startup failure for DeepSeek-V3.1 models by
removing a strict type assertion for `MLAAttentionSpec` in
`NPUModelRunner.get_kv_cache_spec`. The assertion was failing due to
class identity mismatches caused by the runtime patching of
`MLAAttentionSpec` with `AscendMLAAttentionSpec`.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Verified that the service starts correctly for DSV3.1 models.
Signed-off-by: mayumeng <m30059191@china.huawei.com>
Co-authored-by: mayumeng <m30059191@china.huawei.com>
### What this PR does / why we need it?
Fix Qwen3.5 MoE MTP layer shared expert shape error when flash comm v1
is enabled.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
- vLLM version: v0.18.0
- vLLM main:
35141a7eed
Signed-off-by: Wangbingjie <wangbj1207@126.com>
### What this PR does / why we need it?
bugfix short squence has no respone. This pull request refactors the
event handling for KV cache reshaping in mla_v1.py by centralizing the
reshape_cache_event creation and recording within the _mla_preprocess
function, ensuring it covers both decode and prefill operations.
Signed-off-by: wangxiaoteng <wangxiaoteng@huawei.com>
### What this PR does / why we need it?
Introduce a check to not using asynchronous communication under
`enable_dsa_cp_with_layer_shard` branch on capturing mode. This change
prevents potential stream and event issues when operating in
graph/capturing mode, ensuring safer communication practices.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
E2E test with dsv32 + FC1 + FULL_DECODE_ONLY +
kv_transfer_config(kv_both)
---------
Signed-off-by: chenchuw886 <chenchuw@huawei.com>
Co-authored-by: chenchuw886 <chenchuw@huawei.com>
### What this PR does / why we need it?
1. This PR cherry pick commit that contains current best performance at
3.5k/1.5k and 128k/1k from main to 0.18.0 branch.
2. This PR introduce MiniMax-M2.7 0day information to users.
3. To finish previous step we also changes MiniMax doc name from
MiniMax-M2.5.md to MiniMax-M2.md
---------
Signed-off-by: limuyuan <limuyuan3@huawei.com>
Co-authored-by: limuyuan <limuyuan3@huawei.com>
### What this PR does / why we need it?
This PR adds description of preemption into FAQs in vLLM-Ascend. This
FAQ stats:
- how preemption affects the performance of a vLLM server.
- how reduce the negative impacts of preemption.
The reason why we add this FAQ is that we find that the origin
description of preemption in vLLM is not very straightforward. If
preemption causes performance drop, users might not be aware that this
is caused by Preemption.
### Does this PR introduce _any_ user-facing change?
No.
Signed-off-by: Angazenn <supperccell@163.com>
