[1/N][CI] Add multi node test (#3359)

### What this PR does / why we need it?
This pr purpose to add multi-node test, on the first step, add
`deepseek-v3` dp+tp+ep test
### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

- vLLM version: v0.11.0rc3
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.11.0

---------

Signed-off-by: wangli <wangli858794774@gmail.com>

tests/e2e/multi_node/test_multi_dp.py

@@ -0,0 +1,49 @@
+import subprocess
+
+import pytest
+
+from tests.e2e.conftest import RemoteOpenAIServer
+from tests.e2e.multi_node.config.multi_node_config import (MultiNodeConfig,
+                                                           load_configs)
+from tests.e2e.multi_node.config.utils import get_default_envs
+
+configs = load_configs()
+
+
+def get_benchmark_cmd(model: str, base_url: str, args: list[str]):
+    """vllm bench serve <model> --base-url <url> ..."""
+    return [
+        "vllm", "bench", "serve", "--model", model, "--base-url", base_url
+    ] + args
+
+
+@pytest.mark.parametrize("config", configs)
+def test_multi_dp(config: MultiNodeConfig) -> None:
+    env_dict = get_default_envs()
+
+    server_config = config.server_config
+    perf_config = config.perf_config
+    model_name = server_config.model
+    assert model_name is not None, "Model name must be specified"
+
+    server_args = server_config.to_list()
+
+    with RemoteOpenAIServer(
+            model_name,
+            config.server_host,
+            config.server_port,
+            server_args,
+            env_dict=env_dict,
+            auto_port=False,
+            seed=1024,
+            max_wait_seconds=1000,
+    ) as remote_server:
+        base_url = remote_server.url_root
+        assert perf_config is not None, "Perf config must be specified for perf tests"
+        perf_cmd = get_benchmark_cmd(server_config.model, base_url,
+                                     perf_config.to_list())
+        if server_config.headless:
+            remote_server.hang_until_terminated()
+        else:
+            # run perf benchmark
+            subprocess.run(perf_cmd, check=True)