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[2/N] Upgrade nightly doc (#5534)

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### What this PR does / why we need it?
Follow up https://github.com/vllm-project/vllm-ascend/pull/5479, upgrade
the corresponding doc for developers

- vLLM version: v0.13.0
- vLLM main:
45c1ca1ca1

Signed-off-by: wangli <wangli858794774@gmail.com>
This commit is contained in:
Li Wang
2025-12-31 09:11:42 +08:00
committed by GitHub
parent 98798d80a0
commit 2ee17e50a1
4 changed files with 266 additions and 73 deletions
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332
docs/source/developer_guide/contribution/multi_node_test.md
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@@ -20,7 +20,7 @@ From the workflow perspective, we can see how the final test script is executed,
2. Add config yaml
As the entrypoint script [run.sh](https://github.com/vllm-project/vllm-ascend/blob/0bf3f21a987aede366ec4629ad0ffec8e32fe90d/tests/e2e/nightly/multi_node/scripts/run.sh#L106) shows, A k8s pod startup means traversing all *.yaml files in the [directory](https://github.com/vllm-project/vllm-ascend/tree/main/tests/e2e/nightly/multi_node/config/models), reading and executing according to different configurations, so what we need to do is just add "yamls" like [DeepSeek-V3.yaml](https://github.com/vllm-project/vllm-ascend/blob/main/tests/e2e/nightly/multi_node/config/models/DeepSeek-V3.yaml).
As the entrypoint script [run.sh](https://github.com/vllm-project/vllm-ascend/blob/0bf3f21a987aede366ec4629ad0ffec8e32fe90d/tests/e2e/nightly/multi_node/scripts/run.sh#L106) shows, A k8s pod startup means traversing all *.yaml files in the [directory](https://github.com/vllm-project/vllm-ascend/tree/main/tests/e2e/nightly/multi_node/config/), reading and executing according to different configurations, so what we need to do is just add "yamls" like [DeepSeek-V3.yaml](https://github.com/vllm-project/vllm-ascend/blob/main/tests/e2e/nightly/multi_node/config/DeepSeek-V3.yaml).
Suppose you have **2 nodes** running a 1P1D setup (1 Prefillers + 1 Decoder):
@@ -48,15 +48,19 @@ From the workflow perspective, we can see how the final test script is executed,
prefiller_host_index: [0]
# node index(a list) which meet all the conditions:
# - decoder
# - no headless(have api server)
decoder_host_index: [1]
# Add each node's vllm serve cli command just like you run locally
# Add each node's individual envs like follow
deployment:
-
envs:
# fill with envs like: <key>:<value>
server_cmd: >
vllm serve ...
-
envs:
# fill with envs like: <key>:<value>
server_cmd: >
vllm serve ...
benchmarks:
@@ -65,73 +69,13 @@ From the workflow perspective, we can see how the final test script is executed,
acc:
# fill with accuracy test kwargs
```
3. Running Locally(Option)
Step 1. Add cluster_hosts to config yamls
Modify on every cluster host, commands as following:
like [DeepSeek-V3.yaml](https://github.com/vllm-project/vllm-ascend/blob/main/tests/e2e/nightly/multi_node/config/models/DeepSeek-V3.yaml) after the configure item `num_nodes` , for example:
`cluster_hosts: ["xxx.xxx.xxx.188", "xxx.xxx.xxx.212"]`
Step 2. Install develop environment
- Install vllm-ascend develop packages on every cluster host
``` bash
cd /vllm-workspace/vllm-ascend
python3 -m pip install -r requirements-dev.txt
```
- Install AISBench on the first host(leader node) in cluster_hosts
``` bash
export AIS_BENCH_TAG="v3.0-20250930-master"
export AIS_BENCH_URL="https://gitee.com/aisbench/benchmark.git"
git clone -b ${AIS_BENCH_TAG} --depth 1 ${AIS_BENCH_URL} /vllm-workspace/vllm-ascend/benchmark
cd /vllm-workspace/vllm-ascend/benchmark
pip install -e . -r requirements/api.txt -r requirements/extra.txt
```
Step 3. Running test locally
- Export environments
On leader host(the first node xxx.xxx.xxx.188)
``` bash
export LWS_WORKER_INDEX=0
export WORKSPACE=/vllm-workspace
export CONFIG_YAML_PATH=DeepSeek-V3.yaml
export FAIL_TAG=FAIL_TAG
```
On slave host(other nodes, such as xxx.xxx.xxx.212)
``` bash
export LWS_WORKER_INDEX=1
export WORKSPACE=/vllm-workspace
export CONFIG_YAML_PATH=DeepSeek-V3.yaml
export FAIL_TAG=FAIL_TAG
```
`LWS_WORKER_INDEX` is the index of this node in the `cluster_hosts` . The node with an index of 0 is the leader.
Slave node index value range is [1, num_nodes-1].
- Run vllm serve instances
Copy and Run run.sh on every cluster host, to start vllm, commands as following:
``` bash
cp /vllm-workspace/vllm-ascend/tests/e2e/nightly/multi_node/scripts/run.sh /vllm-workspace/
cd /vllm-workspace/
bash -x run.sh
```
4. Add the case to nightly workflow
currently, the multi-node test workflow defined in the [vllm_ascend_test_nightly_a2/a3.yaml](https://github.com/vllm-project/vllm-ascend/blob/main/.github/workflows/vllm_ascend_test_nightly_a3.yaml)
3. Add the case to nightly workflow
currently, the multi-node test workflow defined in the [nightly_test_a3.yaml](https://github.com/vllm-project/vllm-ascend/blob/main/.github/workflows/nightly_test_a3.yaml)
```yaml
multi-node-tests:
needs: single-node-tests
name: multi-node
if: always() && (github.event_name == 'schedule' || github.event_name == 'workflow_dispatch')
strategy:
fail-fast: false
@@ -139,21 +83,267 @@ currently, the multi-node test workflow defined in the [vllm_ascend_test_nightly
matrix:
test_config:
- name: multi-node-deepseek-pd
config_file_path: tests/e2e/nightly/multi_node/config/models/DeepSeek-V3.yaml
config_file_path: DeepSeek-V3.yaml
size: 2
- name: multi-node-qwen3-dp
config_file_path: tests/e2e/nightly/multi_node/config/models/Qwen3-235B-A22B.yaml
config_file_path: Qwen3-235B-A22B.yaml
size: 2
- name: multi-node-qwenw8a8-2node
config_file_path: Qwen3-235B-W8A8.yaml
size: 2
- name: multi-node-qwenw8a8-2node-eplb
config_file_path: Qwen3-235B-W8A8-EPLB.yaml
size: 2
- name: multi-node-dpsk-4node-pd
config_file_path: tests/e2e/nightly/multi_node/config/models/DeepSeek-R1-W8A8.yaml
size: 4
uses: ./.github/workflows/_e2e_nightly_multi_node.yaml
with:
soc_version: a3
image: m.daocloud.io/quay.io/ascend/cann:8.3.rc2-a3-ubuntu22.04-py3.11
runner: linux-aarch64-a3-0
image: 'swr.cn-southwest-2.myhuaweicloud.com/base_image/ascend-ci/vllm-ascend:nightly-a3'
replicas: 1
size: ${{ matrix.test_config.size }}
config_file_path: ${{ matrix.test_config.config_file_path }}
secrets:
KUBECONFIG_B64: ${{ secrets.KUBECONFIG_B64 }}
```
The matrix above defines all the parameters required to add a multi-machine use case, The parameters worth paying attention to (I mean if you are adding a new use case) are size and the path to the yaml configuration file. The former defines the number of nodes required for your use case, and the latter defines the path to the configuration file you have completed in step 2.
## Run Multi-Node tests locally
### 1. Use kubernetes
This section assumes that you already have a [Kubernetes](https://kubernetes.io/docs/setup/) NPU cluster environment locally. then you can easily start our test with one click.
- Step 1. Install LWS CRD resources
See https://lws.sigs.k8s.io/docs/installation/ Which can be used as a reference
- Step 2. Deploy the following yaml file `lws.yaml` as what you want
```yaml
apiVersion: leaderworkerset.x-k8s.io/v1
kind: LeaderWorkerSet
metadata:
name: test-server
namespace: vllm-project
spec:
replicas: 1
leaderWorkerTemplate:
size: 2
restartPolicy: None
leaderTemplate:
metadata:
labels:
role: leader
spec:
containers:
- name: vllm-leader
imagePullPolicy: Always
image: swr.cn-southwest-2.myhuaweicloud.com/base_image/ascend-ci/vllm-ascend:nightly-a3
env:
- name: CONFIG_YAML_PATH
value: DeepSeek-V3.yaml
- name: WORKSPACE
value: "/vllm-workspace"
- name: FAIL_TAG
value: FAIL_TAG
command:
- sh
- -c
- |
bash /vllm-workspace/vllm-ascend/tests/e2e/nightly/multi_node/scripts/run.sh
resources:
limits:
huawei.com/ascend-1980: 16
memory: 512Gi
ephemeral-storage: 100Gi
requests:
huawei.com/ascend-1980: 16
memory: 512Gi
ephemeral-storage: 100Gi
cpu: 125
ports:
- containerPort: 8080
# readinessProbe:
# tcpSocket:
# port: 8080
# initialDelaySeconds: 15
# periodSeconds: 10
volumeMounts:
- mountPath: /root/.cache
name: shared-volume
- mountPath: /usr/local/Ascend/driver/tools
name: driver-tools
- mountPath: /dev/shm
name: dshm
volumes:
- name: dshm
emptyDir:
medium: Memory
sizeLimit: 15Gi
- name: shared-volume
persistentVolumeClaim:
claimName: nv-action-vllm-benchmarks-v2
- name: driver-tools
hostPath:
path: /usr/local/Ascend/driver/tools
workerTemplate:
spec:
containers:
- name: vllm-worker
imagePullPolicy: Always
image: swr.cn-southwest-2.myhuaweicloud.com/base_image/ascend-ci/vllm-ascend:nightly-a3
env:
- name: CONFIG_YAML_PATH
value: DeepSeek-V3.yaml
- name: WORKSPACE
value: "/vllm-workspace"
- name: FAIL_TAG
value: FAIL_TAG
command:
- sh
- -c
- |
bash /vllm-workspace/vllm-ascend/tests/e2e/nightly/multi_node/scripts/run.sh
resources:
limits:
huawei.com/ascend-1980: 16
memory: 512Gi
ephemeral-storage: 100Gi
requests:
huawei.com/ascend-1980: 16
ephemeral-storage: 100Gi
cpu: 125
volumeMounts:
- mountPath: /root/.cache
name: shared-volume
- mountPath: /usr/local/Ascend/driver/tools
name: driver-tools
- mountPath: /dev/shm
name: dshm
volumes:
- name: dshm
emptyDir:
medium: Memory
sizeLimit: 15Gi
- name: shared-volume
persistentVolumeClaim:
claimName: nv-action-vllm-benchmarks-v2
- name: driver-tools
hostPath:
path: /usr/local/Ascend/driver/tools
---
apiVersion: v1
kind: Service
metadata:
name: vllm-leader
namespace: vllm-project
spec:
ports:
- name: http
port: 8080
protocol: TCP
targetPort: 8080
selector:
leaderworkerset.sigs.k8s.io/name: vllm
role: leader
type: ClusterIP
```
```bash
kubectl apply -f lws.yaml
```
Verify the status of the pods:
```bash
kubectl get pods -n vllm-project
```
Should get an output similar to this:
```bash
NAME READY STATUS RESTARTS AGE
vllm-0 1/1 Running 0 2s
vllm-0-1 1/1 Running 0 2s
```
Verify that the distributed inference works:
```bash
kubectl logs -f vllm-0 -n vllm-project
```
Should get something similar to this:
```shell
INFO 12-30 11:00:57 [__init__.py:43] Available plugins for group vllm.platform_plugins:
INFO 12-30 11:00:57 [__init__.py:45] - ascend -> vllm_ascend:register
INFO 12-30 11:00:57 [__init__.py:48] All plugins in this group will be loaded. Set `VLLM_PLUGINS` to control which plugins to load.
INFO 12-30 11:00:57 [__init__.py:217] Platform plugin ascend is activated
INFO 12-30 11:00:57 [importing.py:68] Triton not installed or not compatible; certain GPU-related functions will not be available.
================================================================================================== test session starts ===================================================================================================
platform linux -- Python 3.11.13, pytest-8.4.2, pluggy-1.6.0 -- /usr/local/python3.11.13/bin/python3
cachedir: .pytest_cache
rootdir: /vllm-workspace/vllm-ascend
configfile: pyproject.toml
plugins: cov-7.0.0, asyncio-1.3.0, mock-3.15.1, anyio-4.12.0
asyncio: mode=Mode.STRICT, debug=False, asyncio_default_fixture_loop_scope=None, asyncio_default_test_loop_scope=function
collected 1 item
tests/e2e/nightly/multi_node/scripts/test_multi_node.py::test_multi_node [2025-12-30 11:01:01] INFO multi_node_config.py:294: Loading config yaml: tests/e2e/nightly/multi_node/config/DeepSeek-V3.yaml
[2025-12-30 11:01:01] INFO multi_node_config.py:348: Resolving cluster IPs via DNS...
[2025-12-30 11:01:01] INFO multi_node_config.py:212: Node 0 envs: {'VLLM_USE_MODELSCOPE': 'True', 'OMP_PROC_BIND': 'False', 'OMP_NUM_THREADS': '100', 'HCCL_BUFFSIZE': '1024', 'SERVER_PORT': '8080', 'NUMEXPR_MAX_THREADS': '128', 'DISAGGREGATED_PREFILL_PROXY_SCRIPT': 'examples/disaggregated_prefill_v1/load_balance_proxy_server_example.py', 'HCCL_IF_IP': '10.0.0.102', 'HCCL_SOCKET_IFNAME': 'eth0', 'GLOO_SOCKET_IFNAME': 'eth0', 'TP_SOCKET_IFNAME': 'eth0', 'LOCAL_IP': '10.0.0.102', 'NIC_NAME': 'eth0', 'MASTER_IP': '10.0.0.102'}
[2025-12-30 11:01:01] INFO multi_node_config.py:159: Launching proxy: python examples/disaggregated_prefill_v1/load_balance_proxy_server_example.py --host 10.0.0.102 --port 6000 --prefiller-hosts 10.0.0.102 --prefiller-ports 8080 --decoder-hosts 10.0.0.138 --decoder-ports 8080
[2025-12-30 11:01:01] INFO conftest.py:107: Starting server with command: vllm serve vllm-ascend/DeepSeek-V3-W8A8 --host 0.0.0.0 --port 8080 --data-parallel-size 2 --data-parallel-size-local 2 --tensor-parallel-size 8 --seed 1024 --enforce-eager --enable-expert-parallel --max-num-seqs 16 --max-model-len 8192 --max-num-batched-tokens 8192 --quantization ascend --trust-remote-code --no-enable-prefix-caching --gpu-memory-utilization 0.9 --kv-transfer-config {"kv_connector": "MooncakeConnectorV1", "kv_role": "kv_producer", "kv_port": "30000", "engine_id": "0", "kv_connector_module_path": "vllm_ascend.distributed.mooncake_connector", "kv_connector_extra_config": {
"prefill": {
"dp_size": 2,
"tp_size": 8
},
"decode": {
"dp_size": 2,
"tp_size": 8
}
}
}
```
### 2. Test without kubernetes
Since our script is Kubernetes-friendly, we need to actively pass in some cluster information if you don't have a Kubernetes environment.
- Step 1. Add cluster_hosts to config yamls
Modify on every cluster host, commands just like [DeepSeek-V3.yaml](https://github.com/vllm-project/vllm-ascend/blob/e760aae1df7814073a4180172385505c1ec0fd83/tests/e2e/nightly/multi_node/config/DeepSeek-V3.yaml#L25) after the configure item `num_nodes` , for example:
`cluster_hosts: ["xxx.xxx.xxx.188", "xxx.xxx.xxx.212"]`
- Step 2. Install develop environment
- Install vllm-ascend develop packages on every cluster host
``` bash
cd /vllm-workspace/vllm-ascend
python3 -m pip install -r requirements-dev.txt
```
- Install AISBench on the first host(leader node) in cluster_hosts
``` bash
export AIS_BENCH_TAG="v3.0-20250930-master"
export AIS_BENCH_URL="https://gitee.com/aisbench/benchmark.git"
export BENCHMARK_HOME=/vllm-workspace/benchmark
git clone -b ${AIS_BENCH_TAG} --depth 1 ${AIS_BENCH_URL} $BENCHMARK_HOME
cd $BENCHMARK_HOME
pip install -e . -r requirements/api.txt -r requirements/extra.txt
```
- Step 3. Running test locally
Run the script on **each node separately**
``` bash
export WORKSPACE=/vllm-workspace # Change it to your path locally
export CONFIG_YAML_PATH="DeepSeek-V3.yaml" # Replace with the config case you added
cd $WORKSPACE/vllm-ascend
bash tests/e2e/nightly/multi_node/scripts/run.sh
```