Files
xc-llm-ascend/docs/source/user_guide/configuration/additional_config.md
ChenCangtao 6c30f8bf87 [Feature]refactor the npugraph_ex config, support online-infer with static kernel (#5775)
### What this PR does / why we need it?
This is a part of
https://github.com/vllm-project/vllm-ascend/issues/4715#issue-3694310762
1. refactor the npugraph_ex config,modified the default configuration of
the static kernel, new default value of static kernel is false
2. support online-infer with static kernel
3. fixed the issue where manually modifying FX graphs caused an abnormal
model return type, and removed the related redundant code.

### Does this PR introduce _any_ user-facing change?
yes,the new config of npugraph_ex is as follow:
```
additional_config={
            "npugraph_ex_config": {
                "enable": True,
                "enable_static_kernel": False
            }
        }
```
### How was this patch tested?
```
vllm serve /data/DeepSeek-V3.1-Terminus-w4a8 \
    --host 0.0.0.0 \
    --port 8004 \
    --data-parallel-size 4 \
    --tensor-parallel-size 4 \
    --quantization ascend \
    --seed 1024 \
    --served-model-name deepseek_v3 \
    --enable-expert-parallel \
    --max-num-seqs 48 \
    --max-model-len 40000 \
    --async-scheduling \
    --max-num-batched-tokens 9000 \
    --trust-remote-code \
    --no-enable-prefix-caching \
    --speculative-config '{"num_speculative_tokens": 3, "method":"deepseek_mtp","disable_padded_drafter_batch": false}' \
    --gpu-memory-utilization 0.9 \
    --compilation-config '{"cudagraph_capture_sizes":[4,32,64,112,160,176,192], "cudagraph_mode": "FULL_DECODE_ONLY"}' \
    --additional-config \
    '{"enable_shared_expert_dp": true,"multistream_overlap_shared_expert": true,"npugraph_ex_config":{"enable":true}}'
```

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

---------

Signed-off-by: chencangtao <chencangtao@huawei.com>
Signed-off-by: ChenCangtao <50493711+ChenCangtao@users.noreply.github.com>
Co-authored-by: chencangtao <chencangtao@huawei.com>
2026-01-20 21:31:38 +08:00

128 lines
7.8 KiB
Markdown

# Additional Configuration
Additional configuration is a mechanism provided by vLLM to allow plugins to control inner behavior by themselves. VLLM Ascend uses this mechanism to make the project more flexible.
## How to use
With either online mode or offline mode, users can use additional configuration. Take Qwen3 as an example:
**Online mode**:
```bash
vllm serve Qwen/Qwen3-8B --additional-config='{"config_key":"config_value"}'
```
**Offline mode**:
```python
from vllm import LLM
LLM(model="Qwen/Qwen3-8B", additional_config={"config_key":"config_value"})
```
### Configuration options
The following table lists additional configuration options available in vLLM Ascend:
| Name | Type | Default | Description |
|-------------------------------------|------|---------|-----------------------------------------------------------------------------------------------------------|
| `xlite_graph_config` | dict | `{}` | Configuration options for xlite graph mode |
| `weight_prefetch_config` | dict | `{}` | Configuration options for weight prefetch |
| `finegrained_tp_config` | dict | `{}` | Configuration options for module tensor parallelism |
| `ascend_compilation_config` | dict | `{}` | Configuration options for ascend compilation |
| `eplb_config` | dict | `{}` | Configuration options for ascend compilation |
| `npugraph_ex_config` | dict | `{}` | Configuration options for npugraph_ex backend |
| `refresh` | bool | `false` | Whether to refresh global Ascend configuration content. This is usually used by rlhf or ut/e2e test case. |
| `dump_config_path` | str | `None` | Configuration file path for msprobe dump(eager mode). |
| `enable_async_exponential` | bool | `False` | Whether to enable async exponential overlap. To enable async exponential, set this config to True. |
| `enable_shared_expert_dp` | bool | `False` | When the expert is shared in DP, it delivers better performance but consumes more memory. Currently only DeepSeek series models are supported. |
| `multistream_overlap_shared_expert` | bool | `False` | Whether to enable multistream shared expert. This option only takes effect on MoE models with shared experts. |
| `multistream_overlap_gate` | bool | `False` | Whether to enable multistream overlap gate. This option only takes effect on MoE models with shared experts. |
| `recompute_scheduler_enable` | bool | `False` | Whether to enable recompute scheduler. |
| `enable_cpu_binding` | bool | `False` | Whether to enable CPU binding. |
| `SLO_limits_for_dynamic_batch` | int | `-1` | SLO limits for dynamic batch. This is new scheduler to support dynamic feature |
| `enable_npugraph_ex` | bool | `False` | Whether to enable npugraph ex graph mode. |
| `pa_shape_list` | list | `[]` | The custom shape list of page attention ops. |
| `enable_kv_nz` | bool | `False` | Whether to enable kvcache NZ layout. This option only takes effects on models using MLA (e.g., DeepSeek). |
| `layer_sharding` | dict | `{}` | Configuration options for layer sharding linear |
The details of each configuration option are as follows:
**xlite_graph_config**
| Name | Type | Default | Description |
| ---- | ---- | ------- | ----------- |
| `enabled` | bool | `False` | Whether to enable xlite graph mode. Currently only Llama, Qwen dense series models, and Qwen3-vl are supported. |
| `full_mode` | bool | `False` | Whether to enable xlite for both the prefill and decode stages. By default, xlite is only enabled for the decode stage. |
**weight_prefetch_config**
| Name | Type | Default | Description |
|------------------|------|-------------------------------------------------------------|------------------------------------|
| `enabled` | bool | `False` | Whether to enable weight prefetch. |
| `prefetch_ratio` | dict | `{"attn": {"qkv": 1.0, "o": 1.0}, "moe": {"gate_up": 0.8}}` | Prefetch ratio of each weight. |
**finegrained_tp_config**
| Name | Type | Default | Description |
| ---- | ---- | ------- | ----------- |
| `lmhead_tensor_parallel_size` | int | `0` | The custom tensor parallel size of lmhead. |
| `oproj_tensor_parallel_size` | int | `0` | The custom tensor parallel size of oproj. |
| `embedding_tensor_parallel_size` | int | `0` | The custom tensor parallel size of embedding. |
| `mlp_tensor_parallel_size` | int | `0` | The custom tensor parallel size of mlp. |
**ascend_compilation_config**
| Name | Type | Default | Description |
| ---- | ---- | ------- | ----------- |
| `fuse_norm_quant` | bool | `True` | Whether to enable fuse_norm_quant pass. |
| `fuse_qknorm_rope` | bool | `False` | Whether to enable fuse_qknorm_rope pass. It's set to True by default when Triton is installed. |
**eplb_config**
| Name | Type | Default | Description |
| ---- | ---- | ------- | ----------- |
| `dynamic_eplb` | bool| `False`| Whether to enable dynamic EPLB. |
| `expert_map_path` | str | `None` | When using expert load balancing for an MoE model, an expert map path needs to be passed in.|
| `expert_heat_collection_interval`| int | `400` | Forward iterations when EPLB begins. |
| `algorithm_execution_interval` | int | `30` | The forward iterations when the EPLB worker will finish CPU tasks. |
| `expert_map_record_path` | str | `None` | Save the expert load calculation results to a new expert table in the specified directory.|
| `num_redundant_experts` | int | `0` | Specify redundant experts during initialization. |
**npugraph_ex_config**
| Name | Type | Default | Description |
|------------------------| ---- |---------|----------------------------------------------------------------------------------------|
| `enable` | bool | `False` | Whether to enable npugraph_ex backend. |
| `enable_static_kernel` | bool | `False` | Whether to enable static kernel. Suitable for scenarios where shape changes are minimal and some time is available for static kernel compilation. |
### Example
An example of additional configuration is as follows:
```python
{
"weight_prefetch_config": {
"enabled": True,
"prefetch_ratio": {
"attn": {
"qkv": 1.0,
"o": 1.0,
},
"moe": {
"gate_up": 0.8
}
},
},
"finegrained_tp_config": {
"lmhead_tensor_parallel_size": 8,
"oproj_tensor_parallel_size": 8,
"embedding_tensor_parallel_size": 8,
"mlp_tensor_parallel_size": 8,
},
"enable_kv_nz": False,
"multistream_overlap_shared_expert": True,
"refresh": False
}
```