Files
xc-llm-ascend/tests/e2e/nightly/multi_node/config/Qwen3-235B-A22B.yaml
Nengjun Ma 297f6deb09 [CI] Align multi-node nightly test paramter with corresponding tutorials document (#5756)
### What this PR does / why we need it?
Align multi-node nightly test paramter with tutorials documents.

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

### How was this patch tested?
Test locally and nighly e2e multi-node test cases.

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

---------

Signed-off-by: leo-pony <nengjunma@outlook.com>
2026-01-12 09:00:31 +08:00

74 lines
2.0 KiB
YAML

test_name: "test Qwen3-235B-A22B multi-dp"
model: "Qwen/Qwen3-235B-A22B"
num_nodes: 2
npu_per_node: 16
env_common:
HCCL_OP_EXPANSION_MODE: AIV
TASK_QUEUE_ENABLE: 1
VLLM_USE_MODELSCOPE: true
OMP_PROC_BIND: false
OMP_NUM_THREADS: 1
PYTORCH_NPU_ALLOC_CONF: expandable_segments:True
HCCL_BUFFSIZE: 1024
SERVER_PORT: 8080
NUMEXPR_MAX_THREADS: 128
deployment:
-
server_cmd: >
vllm serve "Qwen/Qwen3-235B-A22B"
--host 0.0.0.0
--port $SERVER_PORT
--data-parallel-size 4
--data-parallel-size-local 2
--data-parallel-address $LOCAL_IP
--data-parallel-rpc-port 13389
--tensor-parallel-size 8
--seed 1024
--enable-expert-parallel
--max-num-seqs 32
--max-model-len 8192
--max-num-batched-tokens 8192
--trust-remote-code
--no-enable-prefix-caching
--gpu-memory-utilization 0.9
-
server_cmd: >
vllm serve "Qwen/Qwen3-235B-A22B"
--headless
--data-parallel-size 4
--data-parallel-size-local 2
--data-parallel-start-rank 2
--data-parallel-address $MASTER_IP
--data-parallel-rpc-port 13389
--tensor-parallel-size 8
--seed 1024
--max-num-seqs 32
--max-model-len 8192
--max-num-batched-tokens 8192
--enable-expert-parallel
--trust-remote-code
--no-enable-prefix-caching
--gpu-memory-utilization 0.9
benchmarks:
perf:
case_type: performance
dataset_path: vllm-ascend/GSM8K-in3500-bs2800
request_conf: vllm_api_stream_chat
dataset_conf: gsm8k/gsm8k_gen_0_shot_cot_str_perf
num_prompts: 2800
max_out_len: 1500
batch_size: 700
request_rate: 11.2
baseline: 1
threshold: 0.97
acc:
case_type: accuracy
dataset_path: vllm-ascend/gsm8k
request_conf: vllm_api_general_chat
dataset_conf: gsm8k/gsm8k_gen_0_shot_cot_chat_prompt
max_out_len: 7680
batch_size: 512
baseline: 95
threshold: 3