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[Doc] Update deepseek-v3.2 doc (#3319)

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### What this PR does / why we need it?
Upgrade deepseek-v3.2 doc for A2
### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

- vLLM version: v0.11.0

---------

Signed-off-by: wangli <wangli858794774@gmail.com>
This commit is contained in:
Li Wang
2025-10-10 08:55:39 +08:00
committed by GitHub
parent 579b7e5f21
commit 60b7c936c5
1 changed files with 98 additions and 12 deletions
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110
docs/source/tutorials/multi-node_dsv3.2.md
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@@ -217,12 +217,12 @@ vllm serve /root/.cache/Modelers_Park/DeepSeek-V3.2-Exp \
--served-model-name deepseek_v3.2 \
--enable-expert-parallel \
--max-num-seqs 16 \
--max-model-len 32768 \
--max-num-batched-tokens 32768 \
--max-model-len 17450 \
--max-num-batched-tokens 17450 \
--trust-remote-code \
--no-enable-prefix-caching \
--gpu-memory-utilization 0.9 \
--additional-config '{"torchair_graph_config":{"enabled":true,"graph_batch_sizes":[16]}}'
--additional-config '{"ascend_scheduler_config":{"enabled":true},"torchair_graph_config":{"enabled":true,"graph_batch_sizes":[16]}}'
```
**node1**
@@ -255,13 +255,13 @@ vllm serve /root/.cache/Modelers_Park/DeepSeek-V3.2-Exp \
--seed 1024 \
--served-model-name deepseek_v3.2 \
--max-num-seqs 16 \
--max-model-len 32768 \
--max-num-batched-tokens 32768 \
--max-model-len 17450 \
--max-num-batched-tokens 17450 \
--enable-expert-parallel \
--trust-remote-code \
--no-enable-prefix-caching \
--gpu-memory-utilization 0.92 \
--additional-config '{"torchair_graph_config":{"enabled":true,"graph_batch_sizes":[16]}}'
--additional-config '{"ascend_scheduler_config":{"enabled":true},"torchair_graph_config":{"enabled":true,"graph_batch_sizes":[16]}}'
```
::::
@@ -270,8 +270,9 @@ vllm serve /root/.cache/Modelers_Park/DeepSeek-V3.2-Exp \
```shell
#!/bin/sh
export VLLM_USE_MODELSCOPE=true
vllm serve /root/.cache/Modelers_Park/DeepSeek-V3.2-Exp-W8A8 \
vllm serve vllm-ascend/DeepSeek-V3.2-Exp-W8A8 \
--host 0.0.0.0 \
--port 8000 \
--tensor-parallel-size 16 \
@@ -279,18 +280,103 @@ vllm serve /root/.cache/Modelers_Park/DeepSeek-V3.2-Exp-W8A8 \
--quantization ascend \
--served-model-name deepseek_v3.2 \
--max-num-seqs 16 \
--max-model-len 32768 \
--max-num-batched-tokens 32768 \
--max-model-len 17450 \
--max-num-batched-tokens 17450 \
--enable-expert-parallel \
--trust-remote-code \
--no-enable-prefix-caching \
--gpu-memory-utilization 0.92 \
--additional-config '{"torchair_graph_config":{"enabled":true,"graph_batch_sizes":[16]}}'
--additional-config '{"ascend_scheduler_config":{"enabled":true},"torchair_graph_config":{"enabled":true,"graph_batch_sizes":[16]}}'
```
::::
::::{tab-item} A2 series
Just like A3 series, the only difference is to set `--data-parallel-size` to the right value on each node.
::::{tab-item} DeepSeek-V3.2-Exp-W8A8 A2 series
Run the following scripts on two nodes respectively
**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
export HCCL_OP_EXPANSION_MODE="AIV"
export PYTORCH_NPU_ALLOC_CONF="expandable_segments:True"
vllm serve vllm-ascend/DeepSeek-V3.2-Exp-W8A8 \
--host 0.0.0.0 \
--port 8000 \
--data-parallel-size 2 \
--data-parallel-size-local 1 \
--data-parallel-address $local_ip \
--data-parallel-rpc-port 13389 \
--tensor-parallel-size 8 \
--seed 1024 \
--served-model-name deepseek_v3.2 \
--enable-expert-parallel \
--max-num-seqs 16 \
--max-model-len 17450 \
--max-num-batched-tokens 17450 \
--trust-remote-code \
--quantization ascend \
--no-enable-prefix-caching \
--gpu-memory-utilization 0.9 \
--additional-config '{"ascend_scheduler_config":{"enabled":true},"torchair_graph_config":{"enabled":true,"graph_batch_sizes":[16]}}'
```
**node1**
```shell
#!/bin/sh
nic_name="xxx"
local_ip="xxx"
export VLLM_USE_MODELSCOPE=True
export HCCL_IF_IP=$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
export HCCL_OP_EXPANSION_MODE="AIV"
export PYTORCH_NPU_ALLOC_CONF="expandable_segments:True"
vllm serve vllm-ascend/DeepSeek-V3.2-Exp-W8A8 \
--host 0.0.0.0 \
--port 8000 \
--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 8 \
--seed 1024 \
--served-model-name deepseek_v3.2 \
--max-num-seqs 16 \
--max-model-len 17450 \
--max-num-batched-tokens 17450 \
--enable-expert-parallel \
--trust-remote-code \
--quantization ascend \
--no-enable-prefix-caching \
--gpu-memory-utilization 0.92 \
--additional-config '{"ascend_scheduler_config":{"enabled":true},"torchair_graph_config":{"enabled":true,"graph_batch_sizes":[16]}}'
```
::::
:::::