[doc] use MkDocs collapsible blocks - supplement (#19973)

Signed-off-by: reidliu41 <reid201711@gmail.com>
Co-authored-by: reidliu41 <reid201711@gmail.com>
This commit is contained in:
Reid
2025-06-23 18:54:16 +08:00
committed by GitHub
parent 5111642a6f
commit b82e0f82cb
3 changed files with 286 additions and 260 deletions

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@@ -61,23 +61,25 @@ To address the above issues, I have designed and developed a local Tensor memory
# Install vLLM
```shell
# Enter the home directory or your working directory.
cd /home
??? Commands
# Download the installation package, and I will update the commit-id in time. You can directly copy the command.
wget https://vllm-wheels.s3.us-west-2.amazonaws.com/9112b443a042d8d815880b8780633882ad32b183/vllm-1.0.0.dev-cp38-abi3-manylinux1_x86_64.whl
```shell
# Enter the home directory or your working directory.
cd /home
# Download the code repository.
git clone -b xpyd-v1 https://github.com/Abatom/vllm.git
cd vllm
# Download the installation package, and I will update the commit-id in time. You can directly copy the command.
wget https://vllm-wheels.s3.us-west-2.amazonaws.com/9112b443a042d8d815880b8780633882ad32b183/vllm-1.0.0.dev-cp38-abi3-manylinux1_x86_64.whl
# Set the installation package path.
export VLLM_PRECOMPILED_WHEEL_LOCATION=/home/vllm-1.0.0.dev-cp38-abi3-manylinux1_x86_64.whl
# Download the code repository.
git clone -b xpyd-v1 https://github.com/Abatom/vllm.git
cd vllm
# installation
pip install -e . -v
```
# Set the installation package path.
export VLLM_PRECOMPILED_WHEEL_LOCATION=/home/vllm-1.0.0.dev-cp38-abi3-manylinux1_x86_64.whl
# installation
pip install -e . -v
```
# Run xPyD
@@ -104,83 +106,91 @@ python3 disagg_prefill_proxy_xpyd.py &
### Prefill1 (e.g. 10.0.1.2 or 10.0.1.1)
```shell
VLLM_USE_V1=1 CUDA_VISIBLE_DEVICES=0 vllm serve {your model directory} \
--host 0.0.0.0 \
--port 20005 \
--tensor-parallel-size 1 \
--seed 1024 \
--served-model-name base_model \
--dtype float16 \
--max-model-len 10000 \
--max-num-batched-tokens 10000 \
--max-num-seqs 256 \
--trust-remote-code \
--gpu-memory-utilization 0.9 \
--disable-log-request \
--kv-transfer-config \
'{"kv_connector":"P2pNcclConnector","kv_role":"kv_producer","kv_buffer_size":"1e1","kv_port":"21001","kv_connector_extra_config":{"proxy_ip":"10.0.1.1","proxy_port":"30001","http_port":"20005","send_type":"PUT_ASYNC","nccl_num_channels":"16"}}' > /var/vllm.log 2>&1 &
```
??? Command
```shell
VLLM_USE_V1=1 CUDA_VISIBLE_DEVICES=0 vllm serve {your model directory} \
--host 0.0.0.0 \
--port 20005 \
--tensor-parallel-size 1 \
--seed 1024 \
--served-model-name base_model \
--dtype float16 \
--max-model-len 10000 \
--max-num-batched-tokens 10000 \
--max-num-seqs 256 \
--trust-remote-code \
--gpu-memory-utilization 0.9 \
--disable-log-request \
--kv-transfer-config \
'{"kv_connector":"P2pNcclConnector","kv_role":"kv_producer","kv_buffer_size":"1e1","kv_port":"21001","kv_connector_extra_config":{"proxy_ip":"10.0.1.1","proxy_port":"30001","http_port":"20005","send_type":"PUT_ASYNC","nccl_num_channels":"16"}}' > /var/vllm.log 2>&1 &
```
### Decode1 (e.g. 10.0.1.3 or 10.0.1.1)
```shell
VLLM_USE_V1=1 CUDA_VISIBLE_DEVICES=1 vllm serve {your model directory} \
--host 0.0.0.0 \
--port 20009 \
--tensor-parallel-size 1 \
--seed 1024 \
--served-model-name base_model \
--dtype float16 \
--max-model-len 10000 \
--max-num-batched-tokens 10000 \
--max-num-seqs 256 \
--trust-remote-code \
--gpu-memory-utilization 0.7 \
--disable-log-request \
--kv-transfer-config \
'{"kv_connector":"P2pNcclConnector","kv_role":"kv_consumer","kv_buffer_size":"8e9","kv_port":"22001","kv_connector_extra_config":{"proxy_ip":"10.0.1.1","proxy_port":"30001","http_port":"20009","send_type":"PUT_ASYNC","nccl_num_channels":"16"}}' > /var/vllm.log 2>&1 &
```
??? Command
```shell
VLLM_USE_V1=1 CUDA_VISIBLE_DEVICES=1 vllm serve {your model directory} \
--host 0.0.0.0 \
--port 20009 \
--tensor-parallel-size 1 \
--seed 1024 \
--served-model-name base_model \
--dtype float16 \
--max-model-len 10000 \
--max-num-batched-tokens 10000 \
--max-num-seqs 256 \
--trust-remote-code \
--gpu-memory-utilization 0.7 \
--disable-log-request \
--kv-transfer-config \
'{"kv_connector":"P2pNcclConnector","kv_role":"kv_consumer","kv_buffer_size":"8e9","kv_port":"22001","kv_connector_extra_config":{"proxy_ip":"10.0.1.1","proxy_port":"30001","http_port":"20009","send_type":"PUT_ASYNC","nccl_num_channels":"16"}}' > /var/vllm.log 2>&1 &
```
### Decode2 (e.g. 10.0.1.4 or 10.0.1.1)
```shell
VLLM_USE_V1=1 CUDA_VISIBLE_DEVICES=2 vllm serve {your model directory} \
--host 0.0.0.0 \
--port 20003 \
--tensor-parallel-size 1 \
--seed 1024 \
--served-model-name base_model \
--dtype float16 \
--max-model-len 10000 \
--max-num-batched-tokens 10000 \
--max-num-seqs 256 \
--trust-remote-code \
--gpu-memory-utilization 0.7 \
--disable-log-request \
--kv-transfer-config \
'{"kv_connector":"P2pNcclConnector","kv_role":"kv_consumer","kv_buffer_size":"8e9","kv_port":"23001","kv_connector_extra_config":{"proxy_ip":"10.0.1.1","proxy_port":"30001","http_port":"20003","send_type":"PUT_ASYNC","nccl_num_channels":"16"}}' > /var/vllm.log 2>&1 &
```
??? Command
```shell
VLLM_USE_V1=1 CUDA_VISIBLE_DEVICES=2 vllm serve {your model directory} \
--host 0.0.0.0 \
--port 20003 \
--tensor-parallel-size 1 \
--seed 1024 \
--served-model-name base_model \
--dtype float16 \
--max-model-len 10000 \
--max-num-batched-tokens 10000 \
--max-num-seqs 256 \
--trust-remote-code \
--gpu-memory-utilization 0.7 \
--disable-log-request \
--kv-transfer-config \
'{"kv_connector":"P2pNcclConnector","kv_role":"kv_consumer","kv_buffer_size":"8e9","kv_port":"23001","kv_connector_extra_config":{"proxy_ip":"10.0.1.1","proxy_port":"30001","http_port":"20003","send_type":"PUT_ASYNC","nccl_num_channels":"16"}}' > /var/vllm.log 2>&1 &
```
### Decode3 (e.g. 10.0.1.5 or 10.0.1.1)
```shell
VLLM_USE_V1=1 CUDA_VISIBLE_DEVICES=3 vllm serve {your model directory} \
--host 0.0.0.0 \
--port 20008 \
--tensor-parallel-size 1 \
--seed 1024 \
--served-model-name base_model \
--dtype float16 \
--max-model-len 10000 \
--max-num-batched-tokens 10000 \
--max-num-seqs 256 \
--trust-remote-code \
--gpu-memory-utilization 0.7 \
--disable-log-request \
--kv-transfer-config \
'{"kv_connector":"P2pNcclConnector","kv_role":"kv_consumer","kv_buffer_size":"8e9","kv_port":"24001","kv_connector_extra_config":{"proxy_ip":"10.0.1.1","proxy_port":"30001","http_port":"20008","send_type":"PUT_ASYNC","nccl_num_channels":"16"}}' > /var/vllm.log 2>&1 &
```
??? Command
```shell
VLLM_USE_V1=1 CUDA_VISIBLE_DEVICES=3 vllm serve {your model directory} \
--host 0.0.0.0 \
--port 20008 \
--tensor-parallel-size 1 \
--seed 1024 \
--served-model-name base_model \
--dtype float16 \
--max-model-len 10000 \
--max-num-batched-tokens 10000 \
--max-num-seqs 256 \
--trust-remote-code \
--gpu-memory-utilization 0.7 \
--disable-log-request \
--kv-transfer-config \
'{"kv_connector":"P2pNcclConnector","kv_role":"kv_consumer","kv_buffer_size":"8e9","kv_port":"24001","kv_connector_extra_config":{"proxy_ip":"10.0.1.1","proxy_port":"30001","http_port":"20008","send_type":"PUT_ASYNC","nccl_num_channels":"16"}}' > /var/vllm.log 2>&1 &
```
## Run 3P1D
@@ -193,83 +203,91 @@ python3 disagg_prefill_proxy_xpyd.py &
### Prefill1 (e.g. 10.0.1.2 or 10.0.1.1)
```shell
VLLM_USE_V1=1 CUDA_VISIBLE_DEVICES=0 vllm serve {your model directory} \
--host 0.0.0.0 \
--port 20005 \
--tensor-parallel-size 1 \
--seed 1024 \
--served-model-name base_model \
--dtype float16 \
--max-model-len 10000 \
--max-num-batched-tokens 10000 \
--max-num-seqs 256 \
--trust-remote-code \
--gpu-memory-utilization 0.9 \
--disable-log-request \
--kv-transfer-config \
'{"kv_connector":"P2pNcclConnector","kv_role":"kv_producer","kv_buffer_size":"1e1","kv_port":"21001","kv_connector_extra_config":{"proxy_ip":"10.0.1.1","proxy_port":"30001","http_port":"20005","send_type":"PUT_ASYNC","nccl_num_channels":"16"}}' > /var/vllm.log 2>&1 &
```
??? Command
```shell
VLLM_USE_V1=1 CUDA_VISIBLE_DEVICES=0 vllm serve {your model directory} \
--host 0.0.0.0 \
--port 20005 \
--tensor-parallel-size 1 \
--seed 1024 \
--served-model-name base_model \
--dtype float16 \
--max-model-len 10000 \
--max-num-batched-tokens 10000 \
--max-num-seqs 256 \
--trust-remote-code \
--gpu-memory-utilization 0.9 \
--disable-log-request \
--kv-transfer-config \
'{"kv_connector":"P2pNcclConnector","kv_role":"kv_producer","kv_buffer_size":"1e1","kv_port":"21001","kv_connector_extra_config":{"proxy_ip":"10.0.1.1","proxy_port":"30001","http_port":"20005","send_type":"PUT_ASYNC","nccl_num_channels":"16"}}' > /var/vllm.log 2>&1 &
```
### Prefill2 (e.g. 10.0.1.3 or 10.0.1.1)
```shell
VLLM_USE_V1=1 CUDA_VISIBLE_DEVICES=1 vllm serve {your model directory} \
--host 0.0.0.0 \
--port 20009 \
--tensor-parallel-size 1 \
--seed 1024 \
--served-model-name base_model \
--dtype float16 \
--max-model-len 10000 \
--max-num-batched-tokens 10000 \
--max-num-seqs 256 \
--trust-remote-code \
--gpu-memory-utilization 0.9 \
--disable-log-request \
--kv-transfer-config \
'{"kv_connector":"P2pNcclConnector","kv_role":"kv_producer","kv_buffer_size":"1e1","kv_port":"22001","kv_connector_extra_config":{"proxy_ip":"10.0.1.1","proxy_port":"30001","http_port":"20009","send_type":"PUT_ASYNC","nccl_num_channels":"16"}}' > /var/vllm.log 2>&1 &
```
??? Command
```shell
VLLM_USE_V1=1 CUDA_VISIBLE_DEVICES=1 vllm serve {your model directory} \
--host 0.0.0.0 \
--port 20009 \
--tensor-parallel-size 1 \
--seed 1024 \
--served-model-name base_model \
--dtype float16 \
--max-model-len 10000 \
--max-num-batched-tokens 10000 \
--max-num-seqs 256 \
--trust-remote-code \
--gpu-memory-utilization 0.9 \
--disable-log-request \
--kv-transfer-config \
'{"kv_connector":"P2pNcclConnector","kv_role":"kv_producer","kv_buffer_size":"1e1","kv_port":"22001","kv_connector_extra_config":{"proxy_ip":"10.0.1.1","proxy_port":"30001","http_port":"20009","send_type":"PUT_ASYNC","nccl_num_channels":"16"}}' > /var/vllm.log 2>&1 &
```
### Prefill3 (e.g. 10.0.1.4 or 10.0.1.1)
```shell
VLLM_USE_V1=1 CUDA_VISIBLE_DEVICES=2 vllm serve {your model directory} \
--host 0.0.0.0 \
--port 20003 \
--tensor-parallel-size 1 \
--seed 1024 \
--served-model-name base_model \
--dtype float16 \
--max-model-len 10000 \
--max-num-batched-tokens 10000 \
--max-num-seqs 256 \
--trust-remote-code \
--gpu-memory-utilization 0.9 \
--disable-log-request \
--kv-transfer-config \
'{"kv_connector":"P2pNcclConnector","kv_role":"kv_producer","kv_buffer_size":"1e1","kv_port":"23001","kv_connector_extra_config":{"proxy_ip":"10.0.1.1","proxy_port":"30001","http_port":"20003","send_type":"PUT_ASYNC","nccl_num_channels":"16"}}' > /var/vllm.log 2>&1 &
```
??? Command
```shell
VLLM_USE_V1=1 CUDA_VISIBLE_DEVICES=2 vllm serve {your model directory} \
--host 0.0.0.0 \
--port 20003 \
--tensor-parallel-size 1 \
--seed 1024 \
--served-model-name base_model \
--dtype float16 \
--max-model-len 10000 \
--max-num-batched-tokens 10000 \
--max-num-seqs 256 \
--trust-remote-code \
--gpu-memory-utilization 0.9 \
--disable-log-request \
--kv-transfer-config \
'{"kv_connector":"P2pNcclConnector","kv_role":"kv_producer","kv_buffer_size":"1e1","kv_port":"23001","kv_connector_extra_config":{"proxy_ip":"10.0.1.1","proxy_port":"30001","http_port":"20003","send_type":"PUT_ASYNC","nccl_num_channels":"16"}}' > /var/vllm.log 2>&1 &
```
### Decode1 (e.g. 10.0.1.5 or 10.0.1.1)
```shell
VLLM_USE_V1=1 CUDA_VISIBLE_DEVICES=3 vllm serve {your model directory} \
--host 0.0.0.0 \
--port 20008 \
--tensor-parallel-size 1 \
--seed 1024 \
--served-model-name base_model \
--dtype float16 \
--max-model-len 10000 \
--max-num-batched-tokens 10000 \
--max-num-seqs 256 \
--trust-remote-code \
--gpu-memory-utilization 0.7 \
--disable-log-request \
--kv-transfer-config \
'{"kv_connector":"P2pNcclConnector","kv_role":"kv_consumer","kv_buffer_size":"8e9","kv_port":"24001","kv_connector_extra_config":{"proxy_ip":"10.0.1.1","proxy_port":"30001","http_port":"20008","send_type":"PUT_ASYNC","nccl_num_channels":"16"}}' > /var/vllm.log 2>&1 &
```
??? Command
```shell
VLLM_USE_V1=1 CUDA_VISIBLE_DEVICES=3 vllm serve {your model directory} \
--host 0.0.0.0 \
--port 20008 \
--tensor-parallel-size 1 \
--seed 1024 \
--served-model-name base_model \
--dtype float16 \
--max-model-len 10000 \
--max-num-batched-tokens 10000 \
--max-num-seqs 256 \
--trust-remote-code \
--gpu-memory-utilization 0.7 \
--disable-log-request \
--kv-transfer-config \
'{"kv_connector":"P2pNcclConnector","kv_role":"kv_consumer","kv_buffer_size":"8e9","kv_port":"24001","kv_connector_extra_config":{"proxy_ip":"10.0.1.1","proxy_port":"30001","http_port":"20008","send_type":"PUT_ASYNC","nccl_num_channels":"16"}}' > /var/vllm.log 2>&1 &
```
# Single request
@@ -286,25 +304,27 @@ curl -X POST -s http://10.0.1.1:10001/v1/completions \
# Benchmark
```shell
python3 benchmark_serving.py \
--backend vllm \
--model base_model \
--tokenizer meta-llama/Llama-3.1-8B-Instruct \
--dataset-name "random" \
--host 10.0.1.1 \
--port 10001 \
--random-input-len 1024 \
--random-output-len 1024 \
--ignore-eos \
--burstiness 100 \
--percentile-metrics "ttft,tpot,itl,e2el" \
--metric-percentiles "90,95,99" \
--seed $(date +%s) \
--trust-remote-code \
--request-rate 3 \
--num-prompts 1000
```
??? Command
```shell
python3 benchmark_serving.py \
--backend vllm \
--model base_model \
--tokenizer meta-llama/Llama-3.1-8B-Instruct \
--dataset-name "random" \
--host 10.0.1.1 \
--port 10001 \
--random-input-len 1024 \
--random-output-len 1024 \
--ignore-eos \
--burstiness 100 \
--percentile-metrics "ttft,tpot,itl,e2el" \
--metric-percentiles "90,95,99" \
--seed $(date +%s) \
--trust-remote-code \
--request-rate 3 \
--num-prompts 1000
```
# Shut down