[Doc] Add deepseek multi node doc

docs/source/tutorials/hybrid_node.md

@@ -0,0 +1,211 @@
+# Hybrid-Node (DeepSeek)
+
+## Verify Multi-Node Communication Environment
+
+### Physical Layer Requirements:
+
+- The physical machines must be located on the same WLAN, with network connectivity.
+- All NPUs are connected with optical modules, and the connection status must be normal.
+
+### Verification Process:
+
+Execute the following commands on each node in sequence. The results must all be `success` and the status must be `UP`:
+
+```bash
+ # Check the remote switch ports
+ for i in {0..15}; 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..15}; do hccn_tool -i $i -link -g ; done
+ # Check the network health status
+ for i in {0..15}; do hccn_tool -i $i -net_health -g ; done
+ # View the network detected IP configuration
+ for i in {0..15}; do hccn_tool -i $i -netdetect -g ; done
+ # View gateway configuration
+ for i in {0..15}; do hccn_tool -i $i -gateway -g ; done
+ # View NPU network configuration
+ cat /etc/hccn.conf
+```
+
+### NPU Interconnect Verification:
+#### 1. Get NPU IP Addresses
+
+```bash
+for i in {0..15}; do hccn_tool -i $i -ip -g | grep ipaddr; done
+```
+
+#### 2. Cross-Node PING Test
+
+```bash
+# Execute on the target node (replace with actual IP)
+hccn_tool -i 0 -ping -g address 10.20.0.20
+```
+
+## Run with docker
+Assume you have two Atlas 800 A3(64G*16) nodes, and want to deploy the `deepseek-v3.1-w8a8` quantitative model across multi-node.
+
+```{code-block} bash
+   :substitutions:
+# Update the vllm-ascend image
+export IMAGE=m.daocloud.io/quay.io/ascend/vllm-ascend:|vllm_ascend_version|
+export NAME=vllm-ascend
+
+# Run the container using the defined variables
+# Note if you are running bridge network with docker, Please expose available ports for multiple nodes communication in advance
+docker run --rm \
+--name $NAME \
+--net=host \
+--device /dev/davinci0 \
+--device /dev/davinci1 \
+--device /dev/davinci2 \
+--device /dev/davinci3 \
+--device /dev/davinci4 \
+--device /dev/davinci5 \
+--device /dev/davinci6 \
+--device /dev/davinci7 \
+--device /dev/davinci8 \
+--device /dev/davinci9 \
+--device /dev/davinci10 \
+--device /dev/davinci11 \
+--device /dev/davinci12 \
+--device /dev/davinci13 \
+--device /dev/davinci14 \
+--device /dev/davinci15 \
+--device /dev/davinci_manager \
+--device /dev/devmm_svm \
+--device /dev/hisi_hdc \
+-v /usr/local/dcmi:/usr/local/dcmi \
+-v /usr/local/Ascend/driver/tools/hccn_tool:/usr/local/Ascend/driver/tools/hccn_tool \
+-v /usr/local/bin/npu-smi:/usr/local/bin/npu-smi \
+-v /usr/local/Ascend/driver/lib64/:/usr/local/Ascend/driver/lib64/ \
+-v /usr/local/Ascend/driver/version.info:/usr/local/Ascend/driver/version.info \
+-v /etc/ascend_install.info:/etc/ascend_install.info \
+-v /mnt/sfs_turbo/.cache:/root/.cache \
+-it $IMAGE bash
+```
+
+:::::{tab-set}
+::::{tab-item} DeepSeek-V3.1-BF16
+
+Run the following scripts on two nodes respectively
+
+:::{note}
+Before launch the inference server, ensure the following environment variables are set for multi node communication
+:::
+
+**node0**
+
+```shell
+#!/bin/sh
+
+# this obtained through ifconfig
+# nic_name is the network interface name corresponding to local_ip
+nic_name="xxxx"
+local_ip="xxxx"
+
+export VLLM_USE_MODELSCOPE=True
+export HCCL_IF_IP=$local_ip
+export GLOO_SOCKET_IFNAME=$nic_name
+export TP_SOCKET_IFNAME=$nic_name
+export HCCL_SOCKET_IFNAME=$nic_name
+export OMP_PROC_BIND=false
+export OMP_NUM_THREADS=100
+export HCCL_BUFFSIZE=1024
+
+vllm serve unsloth/DeepSeek-V3.1-BF16 \
+--host 0.0.0.0 \
+--port 8004 \
+--data-parallel-size 2 \
+--data-parallel-size-local 1 \
+--data-parallel-address $local_ip \
+--data-parallel-rpc-port 13389 \
+--tensor-parallel-size 16 \
+--seed 1024 \
+--served-model-name deepseek_v3.1 \
+--enable-expert-parallel \
+--max-num-seqs 16 \
+--max-model-len 32768 \
+--max-num-batched-tokens 32768 \
+--trust-remote-code \
+--no-enable-prefix-caching \
+--gpu-memory-utilization 0.9 \
+--additional-config '{"ascend_scheduler_config":{"enabled":true},"torchair_graph_config":{"enabled":true}}'
+```
+
+**node1**
+
+```shell
+#!/bin/sh
+
+nic_name="xxx"
+local_ip="xxx"
+
+export VLLM_USE_MODELSCOPE=True
+export HCCL_IF_IP=$local_ip
+export GLOO_SOCKET_IFNAME=$nic_name
+export TP_SOCKET_IFNAME=$nic_name
+export HCCL_SOCKET_IFNAME=$nic_name
+export OMP_PROC_BIND=false
+export OMP_NUM_THREADS=100
+export HCCL_BUFFSIZE=1024
+
+vllm serve unsloth/DeepSeek-V3.1-BF16 \
+--host 0.0.0.0 \
+--port 8004 \
+--headless \
+--data-parallel-size 2 \
+--data-parallel-size-local 1 \
+--data-parallel-start-rank 1 \
+--data-parallel-address <node0_ip> \
+--data-parallel-rpc-port 13389 \
+--tensor-parallel-size 16 \
+--seed 1024 \
+--served-model-name deepseek_v3.1 \
+--max-num-seqs 16 \
+--max-model-len 32768 \
+--max-num-batched-tokens 32768 \
+--enable-expert-parallel \
+--trust-remote-code \
+--no-enable-prefix-caching \
+--gpu-memory-utilization 0.92 \
+--additional-config '{"ascend_scheduler_config":{"enabled":true},"torchair_graph_config":{"enabled":true}}'
+```
+
+::::
+
+::::{tab-item} DeepSeek-V3.1-W8A8
+
+```shell
+#!/bin/sh
+
+vllm serve vllm-ascend/DeepSeek-V3.1-W8A8 \
+--host 0.0.0.0 \
+--port 8004 \
+--tensor-parallel-size 16 \
+--seed 1024 \
+--quantization ascend \
+--served-model-name deepseek_v3.1 \
+--max-num-seqs 16 \
+--max-model-len 32768 \
+--max-num-batched-tokens 32768 \
+--enable-expert-parallel \
+--trust-remote-code \
+--no-enable-prefix-caching \
+--gpu-memory-utilization 0.92 \
+--additional-config '{"ascend_scheduler_config":{"enabled":true},"torchair_graph_config":{"enabled":true}}'
+```
+
+::::
+:::::
+
+Once your server is started, you can query the model with input prompts:
+
+```shell
+curl http://<node0_ip>:<port>/v1/completions \
+    -H "Content-Type: application/json" \
+    -d '{
+        "model": "deepseek_v3.1",
+        "prompt": "The future of AI is",
+        "max_tokens": 50,
+        "temperature": 0
+    }'
+```

docs/source/tutorials/index.md

@@ -14,6 +14,7 @@ multi_npu_moge
 multi_npu_qwen3_moe
 multi_npu_quantization
 single_node_300i
+hybrid_node
 multi_node
 multi_node_kimi
 multi_node_pd_disaggregation