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[Info][main] Corrected the errors in the information (#4055)

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### What this PR does / why we need it?
Corrected the errors in the information

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

### How was this patch tested?
ut

- vLLM version: v0.11.0
- vLLM main:
83f478bb19

Signed-off-by: lilinsiman <lilinsiman@gmail.com>
This commit is contained in:
lilinsiman
2025-11-08 18:48:59 +08:00
committed by GitHub
parent 1d7cb5880a
commit a3ff765c65
20 changed files with 35 additions and 35 deletions
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2
docs/source/developer_guide/contribution/multi_node_test.md
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@@ -51,7 +51,7 @@ From the workflow perspective, we can see how the final test script is executed,
# - no headless(have api server)
decoder_host_index: [1]
# Add each node's vllm serve cli command just like you runs locally
# Add each node's vllm serve cli command just like you run locally
deployment:
-
server_cmd: >

4
docs/source/developer_guide/performance/optimization_and_tuning.md
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@@ -70,7 +70,7 @@ Make sure your vLLM and vllm-ascend are installed after your python configuratio
#### 1.1. Install optimized `python`
Python supports **LTO** and **PGO** optimization starting from version `3.6` and above, which can be enabled at compile time. And we have offered optimized `python` packages directly to users for the sake of convenience. You can also reproduce the `python` built following this [tutorial](https://www.hiascend.com/document/detail/zh/Pytorch/600/ptmoddevg/trainingmigrguide/performance_tuning_0063.html) according to your specific scenarios.
Python supports **LTO** and **PGO** optimization starting from version `3.6` and above, which can be enabled at compile time. And we have offered optimized `python` packages directly to users for the sake of convenience. You can also reproduce the `python` build following this [tutorial](https://www.hiascend.com/document/detail/zh/Pytorch/600/ptmoddevg/trainingmigrguide/performance_tuning_0063.html) according to your specific scenarios.
```{code-block} bash
:substitutions:
@@ -116,7 +116,7 @@ export LD_PRELOAD=/usr/lib/"$(uname -i)"-linux-gnu/libjemalloc.so.2 $LD_PRELOAD
#### 2.2. Tcmalloc
**Tcmalloc (Thread Counting Malloc)** is a universal memory allocator that improves overall performance while ensuring low latency by introducing a multi-level cache structure, reducing mutex competition and optimizing large object processing flow. Find more details [here](https://www.hiascend.com/document/detail/zh/Pytorch/700/ptmoddevg/trainingmigrguide/performance_tuning_0068.html).
**Tcmalloc (Thread Caching Malloc)** is a universal memory allocator that improves overall performance while ensuring low latency by introducing a multi-level cache structure, reducing mutex competition and optimizing large object processing flow. Find more details [here](https://www.hiascend.com/document/detail/zh/Pytorch/700/ptmoddevg/trainingmigrguide/performance_tuning_0068.html).
```{code-block} bash
:substitutions: