### What this PR does / why we need it?
If one expert handle more than 48 * 8 token, DispatchGmmCombineDecode
may incur acc problem, because a flag is set too early.
> Reason: LocalTensor ubInputRightHalf, ubInputTmp, ubInputRightHalf,
ubQuantF32, ubQuantS32, and ubQuantF16 use the same space with ubAbs, so
only after all of them are free, the copy from gm into ubInputRightHalf
can start, while before this pr,
AscendC::SetFlag<AscendC::HardEvent::V_MTE2>(0) is too early.
This pr sets flag at right time.
More info about this operator, please refer to RFC: issue
https://github.com/vllm-project/vllm-ascend/issues/5476
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
test qwen3-235b eplb with DispatchGmmCombineDecode on a single A3
node(ep16)
| dataset | version | metric | mode | vllm-api-stream-chat |
|----- | ----- | ----- | ----- | -----|
| aime2024 | 604a78 | accuracy | gen | 86.67 |
- vLLM version: v0.13.0
- vLLM main:
2f4e6548ef
Signed-off-by: wangqiankun <wangqiankun13@huawei.com>
#### What this PR does / why we need it?
This PR adapt DispatchGmmCombineDecode operator to eplb tensor list and
expert token numbers.
This operator support gmm1, gmm2, gmm1Scale and gmm2Scale in format of
list.
This operator support couting how many token each local expert recieves
by expertTokensNum .
- vLLM version: v0.13.0
- vLLM main:
7157596103
More info about this operator, please refer to RFC: issue
https://github.com/vllm-project/vllm-ascend/issues/5476
### What this PR does / why we need it?
In this PR, DispatchGmmCombineDecode add an optional input
x_active_mask, with which
only token masked True will be dispatched and handle.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
Signed-off-by: wangqiankun <wangqiankun13@huawei.com>
### What this PR does / why we need it?
1.Add the implementation of normal Aclnn operators: MoeCombineNormal,
MoeDispatchNormal, NotifyDispatch，and DispatchLayout.
- MoeCombineNormal: Implements the combine logic within MoE operations.
- MoeDispatchNormal: Implements the dispatch logic within MoE
operations.
- NotifyDispatch: Exchanges topk_idx information among different ranks
to calculate the device memory required for the dispatch stage.
- DispatchLayout: Used to calculate information related to the device
memory layout for the dispatch stage.
2.Provide PyTorch interfaces for normal operators—get_dispatch_layout,
dispatch_prefill, and combine_prefill—to be used for MoE communication
during the prefill stage in vLLM.
- get_dispatch_layout: Calculates information related to the device
memory layout for the dispatch operator, and is called before
dispatch_prefill.
- dispatch_prefill: Initiates the dispatch operation.
- combine_prefill: Initiates the combine operation.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
The functionality has already been validated using the local Qwen model.
Test cases will be added after support for multi-NPU use cases in the CI
pipeline is finalized.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
Signed-off-by: shiro-zzzz <zhangdianhao@huawei.com>
### What this PR does / why we need it?
This PR adapt DispatchGmmCombineDecode operator to parameters of small
operators.
1. This operator no longer requires permuting the weights and scales of
GMM1.
2. This operator no longer requires transposing the weights of GMM2.
Therefore, this operator and the small operator can use the same
parameters (weights and scales), which is beneficial for model
adaptation.
- vLLM version: v0.12.0
- vLLM main:
ad32e3e19c
Signed-off-by: wangqiankun <wangqiankun13@huawei.com>
