Files
xc-llm-ascend/docs/source/tutorials/single_node_pd_disaggregation_llmdatadist.md
mazhixin000 75452abe1e [Doc][v11.0-dev][cherry-pick]Add single node PD disaggregation instructions (#4370)
### What this PR does / why we need it?

add single node PD disaggregation instructions for Qwen 2.5VL model.


### Does this PR introduce _any_ user-facing change?
no


---------

Signed-off-by: mazhixin <mazhixin7@huawei.com>
Signed-off-by: mazhixin000 <mazhixinkorea@163.com>
Co-authored-by: mazhixin <mazhixin7@huawei.com>
2025-11-24 17:23:11 +08:00

5.9 KiB

Prefill-Decode Disaggregation Llmdatadist Verification (Qwen2.5-VL)

Getting Start

vLLM-Ascend now supports prefill-decode (PD) disaggregation. This guide takes one-by-one steps to verify these features with constrained resources.

Using the Qwen2.5-VL-7B-Instruct model as an example, use vllm-ascend v0.11.0rc1 (with vLLM v0.11.0) on 1 Atlas 800T A2 server to deploy the "1P1D" architecture. Assume the IP address is 192.0.0.1.

Verify Communication Environment

Verification Process

  1. Single Node Verification:

Execute the following commands in sequence. The results must all be success and the status must be UP:

# Check the remote switch ports
for i in {0..7}; do hccn_tool -i $i -lldp -g | grep Ifname; done
# Get the link status of the Ethernet ports (UP or DOWN)
for i in {0..7}; do hccn_tool -i $i -link -g ; done
# Check the network health status
for i in {0..7}; do hccn_tool -i $i -net_health -g ; done
# View the network detected IP configuration
for i in {0..7}; do hccn_tool -i $i -netdetect -g ; done
# View gateway configuration
for i in {0..7}; do hccn_tool -i $i -gateway -g ; done
# View NPU network configuration
cat /etc/hccn.conf
  1. Get NPU IP Addresses
for i in {0..7}; do hccn_tool -i $i -ip -g;done

Generate Ranktable

The rank table is a JSON file that specifies the mapping of Ascend NPU ranks to nodes. For more details, please refer to the vllm-ascend examples. Execute the following commands for reference.

cd vllm-ascend/examples/disaggregate_prefill_v1/
bash gen_ranktable.sh --ips 192.0.0.1 \
  --npus-per-node  2 --network-card-name eth0 --prefill-device-cnt 1 --decode-device-cnt 1

If you want to run "2P1D", please set npus-per-node to 3 and prefill-device-cnt to 2. The rank table will be generated at /vllm-workspace/vllm-ascend/examples/disaggregate_prefill_v1/ranktable.json

Parameter Meaning
--ips Each node's local IP address (prefiller nodes should be in front of decoder nodes)
--npus-per-node Each node's NPU clips
--network-card-name The physical machines' NIC
--prefill-device-cnt NPU clips used for prefill
--decode-device-cnt NPU clips used for decode

Prefiller/Decoder Deployment

We can run the following scripts to launch a server on the prefiller/decoder NPU, respectively.

:::::{tab-set}

::::{tab-item} Prefiller

export ASCEND_RT_VISIBLE_DEVICES=0
export HCCL_IF_IP=192.0.0.1 # node ip
export GLOO_SOCKET_IFNAME="eth0"  # network card name
export TP_SOCKET_IFNAME="eth0"
export HCCL_SOCKET_IFNAME="eth0"
export DISAGGREGATED_PREFILL_RANK_TABLE_PATH="/path/to/your/generated/ranktable.json"
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10
export VLLM_ASCEND_LLMDD_RPC_PORT=5959

vllm serve /model/Qwen2.5-VL-7B-Instruct  \
  --host 0.0.0.0 \
  --port 13700 \
  --tensor-parallel-size 1 \
  --no-enable-prefix-caching \
  --seed 1024 \
  --served-model-name qwen25vl \
  --max-model-len 40000  \
  --max-num-batched-tokens 40000  \
  --trust-remote-code \
  --gpu-memory-utilization 0.9  \
  --kv-transfer-config  \
  '{"kv_connector": "LLMDataDistCMgrConnector",
    "kv_buffer_device": "npu",
    "kv_role": "kv_producer",
    "kv_parallel_size": 1,
    "kv_port": "20001",
    "engine_id": "0",
    "kv_connector_module_path": "vllm_ascend.distributed.llmdatadist_c_mgr_connector"
  }'

::::

::::{tab-item} Decoder

export ASCEND_RT_VISIBLE_DEVICES=1
export HCCL_IF_IP=192.0.0.1  # node ip
export GLOO_SOCKET_IFNAME="eth0"  # network card name
export TP_SOCKET_IFNAME="eth0"
export HCCL_SOCKET_IFNAME="eth0"
export DISAGGREGATED_PREFILL_RANK_TABLE_PATH="/path/to/your/generated/ranktable.json"
export OMP_PROC_BIND=false
export OMP_NUM_THREADS=10
export VLLM_ASCEND_LLMDD_RPC_PORT=5979

vllm serve /model/Qwen2.5-VL-7B-Instruct  \
  --host 0.0.0.0 \
  --port 13701 \
  --no-enable-prefix-caching \
  --tensor-parallel-size 1 \
  --seed 1024 \
  --served-model-name qwen25vl \
  --max-model-len 40000  \
  --max-num-batched-tokens 40000  \
  --trust-remote-code \
  --gpu-memory-utilization 0.9  \
  --kv-transfer-config  \
  '{"kv_connector": "LLMDataDistCMgrConnector",
  "kv_buffer_device": "npu",
  "kv_role": "kv_consumer",
  "kv_parallel_size": 1,
  "kv_port": "20001",
  "engine_id": "0",
  "kv_connector_module_path": "vllm_ascend.distributed.llmdatadist_c_mgr_connector"
  }'

::::

:::::

If you want to run "2P1D", please set ASCEND_RT_VISIBLE_DEVICES, VLLM_ASCEND_LLMDD_RPC_PORT and port to different values for each P process.

Example Proxy for Deployment

Run a proxy server on the same node with the prefiller service instance. You can get the proxy program in the repository's examples: load_balance_proxy_server_example.py

python load_balance_proxy_server_example.py \
    --host 192.0.0.1 \
    --port 8080 \
    --prefiller-hosts 192.0.0.1 \
    --prefiller-port 13700 \
    --decoder-hosts 192.0.0.1 \
    --decoder-ports 13701
Parameter Meaning
--port Port of proxy
--prefiller-port All ports of prefill
--decoder-ports All ports of decoder

Verification

Check service health using the proxy server endpoint.

curl http://192.0.0.1:8080/v1/chat/completions \
    -H "Content-Type: application/json" \
    -d '{
        "model": "qwen25vl",
        "messages": [
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": [
                {"type": "image_url", "image_url": {"url": "https://modelscope.oss-cn-beijing.aliyuncs.com/resource/qwen.png"}},
                {"type": "text", "text": "What is the text in the illustrate?"}
            ]}
            ],
        "max_tokens": 100,
        "temperature": 0
    }'