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[doc] Fold long code blocks to improve readability (#19926)

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Signed-off-by: reidliu41 <reid201711@gmail.com>
Co-authored-by: reidliu41 <reid201711@gmail.com>
This commit is contained in:
Reid
2025-06-23 13:24:23 +08:00
committed by GitHub
parent 493c275352
commit f17aec0d63
50 changed files with 3455 additions and 3180 deletions
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docs/getting_started/installation/cpu.md
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@@ -76,21 +76,23 @@ Currently, there are no pre-built CPU wheels.
### Build image from source
```console
$ docker build -f docker/Dockerfile.cpu --tag vllm-cpu-env --target vllm-openai .
??? Commands
# Launching OpenAI server
$ docker run --rm \
--privileged=true \
--shm-size=4g \
-p 8000:8000 \
-e VLLM_CPU_KVCACHE_SPACE=<KV cache space> \
-e VLLM_CPU_OMP_THREADS_BIND=<CPU cores for inference> \
vllm-cpu-env \
--model=meta-llama/Llama-3.2-1B-Instruct \
--dtype=bfloat16 \
other vLLM OpenAI server arguments
```
```console
$ docker build -f docker/Dockerfile.cpu --tag vllm-cpu-env --target vllm-openai .
# Launching OpenAI server
$ docker run --rm \
--privileged=true \
--shm-size=4g \
-p 8000:8000 \
-e VLLM_CPU_KVCACHE_SPACE=<KV cache space> \
-e VLLM_CPU_OMP_THREADS_BIND=<CPU cores for inference> \
vllm-cpu-env \
--model=meta-llama/Llama-3.2-1B-Instruct \
--dtype=bfloat16 \
other vLLM OpenAI server arguments
```
!!! tip
For ARM or Apple silicon, use `docker/Dockerfile.arm`
@@ -144,32 +146,34 @@ vllm serve facebook/opt-125m
- If using vLLM CPU backend on a machine with hyper-threading, it is recommended to bind only one OpenMP thread on each physical CPU core using `VLLM_CPU_OMP_THREADS_BIND` or using auto thread binding feature by default. On a hyper-threading enabled platform with 16 logical CPU cores / 8 physical CPU cores:
```console
$ lscpu -e # check the mapping between logical CPU cores and physical CPU cores
??? Commands
# The "CPU" column means the logical CPU core IDs, and the "CORE" column means the physical core IDs. On this platform, two logical cores are sharing one physical core.
CPU NODE SOCKET CORE L1d:L1i:L2:L3 ONLINE MAXMHZ MINMHZ MHZ
0 0 0 0 0:0:0:0 yes 2401.0000 800.0000 800.000
1 0 0 1 1:1:1:0 yes 2401.0000 800.0000 800.000
2 0 0 2 2:2:2:0 yes 2401.0000 800.0000 800.000
3 0 0 3 3:3:3:0 yes 2401.0000 800.0000 800.000
4 0 0 4 4:4:4:0 yes 2401.0000 800.0000 800.000
5 0 0 5 5:5:5:0 yes 2401.0000 800.0000 800.000
6 0 0 6 6:6:6:0 yes 2401.0000 800.0000 800.000
7 0 0 7 7:7:7:0 yes 2401.0000 800.0000 800.000
8 0 0 0 0:0:0:0 yes 2401.0000 800.0000 800.000
9 0 0 1 1:1:1:0 yes 2401.0000 800.0000 800.000
10 0 0 2 2:2:2:0 yes 2401.0000 800.0000 800.000
11 0 0 3 3:3:3:0 yes 2401.0000 800.0000 800.000
12 0 0 4 4:4:4:0 yes 2401.0000 800.0000 800.000
13 0 0 5 5:5:5:0 yes 2401.0000 800.0000 800.000
14 0 0 6 6:6:6:0 yes 2401.0000 800.0000 800.000
15 0 0 7 7:7:7:0 yes 2401.0000 800.0000 800.000
```console
$ lscpu -e # check the mapping between logical CPU cores and physical CPU cores
# On this platform, it is recommend to only bind openMP threads on logical CPU cores 0-7 or 8-15
$ export VLLM_CPU_OMP_THREADS_BIND=0-7
$ python examples/offline_inference/basic/basic.py
```
# The "CPU" column means the logical CPU core IDs, and the "CORE" column means the physical core IDs. On this platform, two logical cores are sharing one physical core.
CPU NODE SOCKET CORE L1d:L1i:L2:L3 ONLINE MAXMHZ MINMHZ MHZ
0 0 0 0 0:0:0:0 yes 2401.0000 800.0000 800.000
1 0 0 1 1:1:1:0 yes 2401.0000 800.0000 800.000
2 0 0 2 2:2:2:0 yes 2401.0000 800.0000 800.000
3 0 0 3 3:3:3:0 yes 2401.0000 800.0000 800.000
4 0 0 4 4:4:4:0 yes 2401.0000 800.0000 800.000
5 0 0 5 5:5:5:0 yes 2401.0000 800.0000 800.000
6 0 0 6 6:6:6:0 yes 2401.0000 800.0000 800.000
7 0 0 7 7:7:7:0 yes 2401.0000 800.0000 800.000
8 0 0 0 0:0:0:0 yes 2401.0000 800.0000 800.000
9 0 0 1 1:1:1:0 yes 2401.0000 800.0000 800.000
10 0 0 2 2:2:2:0 yes 2401.0000 800.0000 800.000
11 0 0 3 3:3:3:0 yes 2401.0000 800.0000 800.000
12 0 0 4 4:4:4:0 yes 2401.0000 800.0000 800.000
13 0 0 5 5:5:5:0 yes 2401.0000 800.0000 800.000
14 0 0 6 6:6:6:0 yes 2401.0000 800.0000 800.000
15 0 0 7 7:7:7:0 yes 2401.0000 800.0000 800.000
# On this platform, it is recommend to only bind openMP threads on logical CPU cores 0-7 or 8-15
$ export VLLM_CPU_OMP_THREADS_BIND=0-7
$ python examples/offline_inference/basic/basic.py
```
- If using vLLM CPU backend on a multi-socket machine with NUMA, be aware to set CPU cores using `VLLM_CPU_OMP_THREADS_BIND` to avoid cross NUMA node memory access.