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enginex-ascend-910-vllm/tests/e2e/nightly/multi_node/external_dp/config/template.md
Sun Ruoxi 7f8a1b1f7a init v0.23.0 
Signed-off-by: Sun Ruoxi <sunruoxi@4paradigm.com>
2026-08-27 15:11:51 +08:00

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External DP Config Template

This document shows how to write YAML configs consumed by tests/e2e/nightly/multi_node/external_dp/scripts/test_external_dp.py.

server_cmd_template contains only the arguments after vllm serve <model>. The framework prepends vllm serve and the top-level model automatically.

Do not write proxy_node_index, proxy_host, proxy_port, proxy_script, or dp_group in YAML. The framework derives proxy metadata from routing.type, and roles are selected by routing.groups.

Generic DP Template

Use this template for generic external data parallel serving. This mode uses --data-parallel-rank, so it is intended for MoE models. For dense models, use independent vLLM instances instead of external DP rank arguments.

test_name: "test Qwen3-30B-A3B generic external dp"
model: "Qwen/Qwen3-30B-A3B"
num_nodes: 2
npu_per_node: 16

# Optional for local debugging. In CI, cluster IPs are resolved from LWS DNS.
# cluster_hosts:
#   - "172.22.0.xxx"
#   - "172.22.0.xxx"

routing:
  type: "generic_dp"
  groups:
    worker: [0, 1]

config:
  - node_index: 0
    port_start: 7100
    dp_rpc_port: 12321
    dp_size: 4
    dp_size_local: 2
    dp_rank_start: 0
    tp_size: 1
    dp_address: "${NODE_0_IP}"

  - node_index: 1
    port_start: 7100
    dp_rpc_port: 12321
    dp_size: 4
    dp_size_local: 2
    dp_rank_start: 2
    tp_size: 1
    dp_address: "${NODE_0_IP}"

templates:
  - node_index: 0
    envs: &generic_env
      VLLM_USE_MODELSCOPE: "true"
      OMP_PROC_BIND: "false"
      OMP_NUM_THREADS: "10"
      PYTORCH_NPU_ALLOC_CONF: "expandable_segments:True"
      ASCEND_RT_VISIBLE_DEVICES: "${VISIBLE_DEVICES}"
      HCCL_BUFFSIZE: "1024"
      SERVER_PORT: "${PORT}"
    server_cmd_template: &generic_server_cmd
      - --host
      - "0.0.0.0"
      - --port
      - $SERVER_PORT
      - --data-parallel-size
      - ${DP_SIZE}
      - --data-parallel-rank
      - ${DP_RANK}
      - --data-parallel-address
      - ${DP_ADDRESS}
      - --data-parallel-rpc-port
      - ${DP_RPC_PORT}
      - --tensor-parallel-size
      - ${TP_SIZE}
      - --max-model-len
      - "4096"
      - --trust-remote-code
      - --enable-expert-parallel

  - node_index: 1
    envs:
      <<: *generic_env
    server_cmd_template: *generic_server_cmd

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: 4
    max_out_len: 16
    batch_size: 1
    request_rate: 1
    baseline: 1
    threshold: 0.1

  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
    num_prompts: 4
    max_out_len: 16
    batch_size: 1
    baseline: 0
    threshold: 100

Disaggregated Prefill Template

Use this template for PD disaggregation. routing.groups decides which config entries run as prefillers or decoders. The framework derives the PD proxy script from routing.type, so do not write proxy_* fields in YAML.

test_name: "test DeepSeek-V2-Lite-W8A8 external dp disaggregated_prefill"
model: "vllm-ascend/DeepSeek-V2-Lite-W8A8"
num_nodes: 2
npu_per_node: 16

# Optional for local debugging. In CI, cluster IPs are resolved from LWS DNS.
# cluster_hosts:
#   - "172.22.0.xxx"
#   - "172.22.0.xxx"

routing:
  type: "disaggregated_prefill"
  groups:
    prefiller: [0]
    decoder: [1]

config:
  - node_index: 0
    port_start: 7100
    dp_rpc_port: 12321
    dp_size: 2
    dp_size_local: 2
    dp_rank_start: 0
    tp_size: 1
    dp_address: "${NODE_0_IP}"

  - node_index: 1
    port_start: 7100
    dp_rpc_port: 12321
    dp_size: 2
    dp_size_local: 2
    dp_rank_start: 0
    tp_size: 1
    dp_address: "${NODE_1_IP}"

env_common: &env_common
  HCCL_OP_
  VLLM_USE_MODELSCOPE: "true"
  OMP_PROC_BIND: "false"
  OMP_NUM_THREADS: "10"
  PYTORCH_NPU_ALLOC_CONF: "expandable_segments:True"
  ASCEND_RT_VISIBLE_DEVICES: "${VISIBLE_DEVICES}"
  HCCL_BUFFSIZE: "256"
  SERVER_PORT: "${PORT}"
  VLLM_ASCEND_ENABLE_FLASHCOMM1: "0"

templates:
  - node_index: 0
    envs:
      <<: *env_common
    server_cmd_template:
      - --host
      - "0.0.0.0"
      - --port
      - $SERVER_PORT
      - --data-parallel-size
      - ${DP_SIZE}
      - --data-parallel-rank
      - ${DP_RANK}
      - --data-parallel-address
      - ${DP_ADDRESS}
      - --data-parallel-rpc-port
      - ${DP_RPC_PORT}
      - --tensor-parallel-size
      - ${TP_SIZE}
      - --trust-remote-code
      - --quantization
      - ascend
      - --enable-expert-parallel
      - --kv-transfer-config
      - '{"kv_connector": "MooncakeConnectorV1",
        "kv_role": "kv_producer",
        "kv_port": "30000",
        "kv_connector_extra_config": {
          "prefill": {
            "dp_size": 2,
            "tp_size": 1
          },
          "decode": {
            "dp_size": 2,
            "tp_size": 1
          }
        }}'

  - node_index: 1
    envs:
      <<: *env_common
    server_cmd_template:
      - --host
      - "0.0.0.0"
      - --port
      - $SERVER_PORT
      - --data-parallel-size
      - ${DP_SIZE}
      - --data-parallel-rank
      - ${DP_RANK}
      - --data-parallel-address
      - ${DP_ADDRESS}
      - --data-parallel-rpc-port
      - ${DP_RPC_PORT}
      - --tensor-parallel-size
      - ${TP_SIZE}
      - --trust-remote-code
      - --quantization
      - ascend
      - --enable-expert-parallel
      - --kv-transfer-config
      - '{"kv_connector": "MooncakeConnectorV1",
        "kv_role": "kv_consumer",
        "kv_port": "30200",
        "kv_connector_extra_config": {
          "prefill": {
            "dp_size": 2,
            "tp_size": 1
          },
          "decode": {
            "dp_size": 2,
            "tp_size": 1
          }
        }}'

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
    max_out_len: 128
    batch_size: 4
    request_rate: 1
    baseline: 1
    threshold: 0.1

  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: 48
    batch_size: 4
    baseline: 0
    threshold: 100

Field Notes

  • test_name: Human-readable test name. It is also used when writing benchmark result metadata.
  • model: Model passed to vllm serve <model> and AISBench requests.
  • num_nodes: Number of config entries and templates expected.
  • npu_per_node: Device capacity validation for each node.
  • cluster_hosts: Optional local-debug IP list. Omit it in CI unless a test needs fixed hosts.
  • routing.type: Supported values are generic_dp and disaggregated_prefill.
  • routing.groups: Maps config indices to roles. generic_dp requires worker; disaggregated_prefill requires prefiller and decoder.
  • For disaggregated_prefill, use kv_producer for prefiller templates and kv_consumer for decoder templates.
  • config[].dp_size: Global DP size for this DP group.
  • config[].dp_size_local: Number of vLLM ranks started on this node.
  • config[].dp_rank_start: First global DP rank owned by this node.
  • config[].dp_address: DP master address. For one global DP group, use ${NODE_0_IP} on all nodes. For PD disaggregation, use the prefiller master address for prefiller nodes and the decoder master address for decoder nodes.
  • templates: One template per config entry. The framework expands one command per local DP rank.

The framework injects distributed network envs at startup:

HCCL_IF_IP
HCCL_SOCKET_IFNAME
GLOO_SOCKET_IFNAME
TP_SOCKET_IFNAME
LOCAL_IP
NIC_NAME
MASTER_IP

The framework also derives proxy metadata from routing.type:

generic_dp -> examples/external_online_dp/dp_load_balance_proxy_server.py
disaggregated_prefill -> examples/disaggregated_prefill_v1/load_balance_proxy_server_example.py

The proxy runs on node 0, listens on ${NODE_0_IP}:1999, and is used by node 0 for benchmark requests.

Template Variables

The following variables are available in envs and server_cmd_template:

${MODEL}
${PORT_START}
${PORT}
${DP_SIZE}
${DP_SIZE_LOCAL}
${DP_RANK_START}
${DP_RANK}
${LOCAL_RANK}
${TP_SIZE}
${CP_SIZE}
${SP_SIZE}
${PP_SIZE}
${DP_ADDRESS}
${DP_RPC_PORT}
${VISIBLE_DEVICES}
${NODE_INDEX}
${CONFIG_INDEX}
${NODE_0_IP}, ${NODE_1_IP}, ...
${LOCAL_IP}
${MASTER_IP}
${LWS_WORKER_INDEX}

Command arguments can also reference rendered environment variables with shell-style $VARNAME, for example:

envs:
  SERVER_PORT: "${PORT}"
server_cmd_template:
  - --port
  - $SERVER_PORT

Checks Before Running

  • Keep len(config) == num_nodes and len(templates) == num_nodes.
  • Make sure each config index is assigned to exactly one routing group.
  • Ensure dp_rank_start + dp_size_local <= dp_size.
  • Ensure dp_size_local * tp_size * cp_size * sp_size * pp_size <= npu_per_node.
  • For generic_dp with --data-parallel-rank, use an MoE model and --enable-expert-parallel.
  • Set --max-model-len large enough for benchmark input tokens plus max_out_len.