Files
xc-llm-ascend/tests/e2e/nightly/multi_node/config/models/DeepSeek-V3.yaml
Li Wang 7f73c28a24 [CI][Doc] Optimize multi-node CI (#3565)
### What this PR does / why we need it?
This pull request mainly do the following things:
1. Add a doc for multi-node CI, The main content is the mechanism
principle and how to contribute
2. Simplify the config yaml for more developer-friendly
3. Optimized the mooncake installation script to prevent accidental
failures during installation
4. Fix the workflow to ensure the kubernetes can be apply correctly
5. Add Qwen3-235B-W8A8 disaggregated_prefill test
6. Add GLM-4.5 multi dp test
7. Add 2p1d 4nodes disaggregated_prefill test
8. Refactor nightly tests
### Does this PR introduce _any_ user-facing change?

### How was this patch tested?


- vLLM version: v0.11.0rc3
- vLLM main:
17c540a993

---------

Signed-off-by: wangli <wangli858794774@gmail.com>
2025-10-25 09:23:47 +08:00

119 lines
4.1 KiB
YAML

# For disaggregated mode, set is_disaggregated: true, and set the following parameters:
# Prefiller_index: the hosts index of the node running prefiller
# Decoder_index: the hosts index of the node running decoder
# Suppose we have **4 nodes** running a 2P1D setup (2 Prefillers + 1 Decoder):
# ┌───────────────┬───────────────┬───────────────┬───────────────┐
# │ node0 │ node1 │ node2 │ node3 │
# │ Prefiller #1 │ Prefiller #2 │ Decoder │ Decoder │
# └───────────────┴───────────────┴───────────────┴───────────────┘
# For the prefiller nodes. the hosts should be node0 and node1
# For the decoder nodes. we only have 1 decoder node(dp+tp+ep across node2 and node3. Where node3 is running with headless mode)
# So the prefiller_host_index is [0, 1], and the decoder_host_index is [2]
test_name: "test DeepSeek-V3 disaggregated_prefill"
model: "vllm-ascend/DeepSeek-V3-W8A8"
num_nodes: 2
npu_per_node: 16
env_common:
VLLM_USE_MODELSCOPE: true
OMP_PROC_BIND: false
OMP_NUM_THREADS: 100
HCCL_BUFFSIZE: 1024
SERVER_PORT: 8080
disaggregated_prefill:
enabled: true
prefiller_host_index: [0]
decoder_host_index: [1]
deployment:
-
server_cmd: >
vllm serve "vllm-ascend/DeepSeek-V3-W8A8"
--host 0.0.0.0
--port $SERVER_PORT
--data-parallel-size 2
--data-parallel-size-local 2
--tensor-parallel-size 8
--seed 1024
--enforce-eager
--enable-expert-parallel
--max-num-seqs 16
--max-model-len 8192
--max-num-batched-tokens 8192
--quantization ascend
--trust-remote-code
--no-enable-prefix-caching
--gpu-memory-utilization 0.9
--kv-transfer-config
'{"kv_connector": "MooncakeConnector",
"kv_role": "kv_producer",
"kv_port": "30000",
"engine_id": "0",
"kv_connector_module_path": "vllm_ascend.distributed.mooncake_connector",
"kv_connector_extra_config": {
"prefill": {
"dp_size": 2,
"tp_size": 8
},
"decode": {
"dp_size": 2,
"tp_size": 8
}
}
}'
-
server_cmd: >
vllm serve "vllm-ascend/DeepSeek-V3-W8A8"
--host 0.0.0.0
--port $SERVER_PORT
--data-parallel-size 2
--data-parallel-size-local 2
--tensor-parallel-size 8
--seed 1024
--quantization ascend
--max-num-seqs 16
--max-model-len 8192
--max-num-batched-tokens 8192
--enable-expert-parallel
--trust-remote-code
--no-enable-prefix-caching
--gpu-memory-utilization 0.9
--additional-config '{"torchair_graph_config":{"enabled":true}}'
--kv-transfer-config
'{"kv_connector": "MooncakeConnector",
"kv_role": "kv_consumer",
"kv_port": "30200",
"engine_id": "1",
"kv_connector_module_path": "vllm_ascend.distributed.mooncake_connector",
"kv_connector_extra_config": {
"prefill": {
"dp_size": 2,
"tp_size": 8
},
"decode": {
"dp_size": 2,
"tp_size": 8
}
}
}'
benchmarks:
perf:
case_type: performance
dataset_path: vllm-ascend/GSM8K-in3500-bs400
request_conf: vllm_api_stream_chat
dataset_conf: gsm8k/gsm8k_gen_0_shot_cot_str_perf
num_prompts: 1
max_out_len: 2
batch_size: 1
baseline: 5
threshold: 0.97
acc:
case_type: accuracy
dataset_path: vllm-ascend/AIME2024
request_conf: vllm_api_general_chat
dataset_conf: aime2024/aime2024_gen_0_shot_chat_prompt
max_out_len: 10
batch_size: 32
baseline: 1
threshold: 1