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[1.21.0 cherry-pick] Synchronize vLLM flags to support cross-node inference #1103

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Merged
merged 2 commits into from
Apr 16, 2025
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[1.21.0 cherry-pick] Synchronize vLLM flags to support cross-node inference #1103

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9e2540e
Synchronize vLLM flags to support cross-node inference (#897)
IT-Forrest Apr 15, 2025
8a78608
Merge branch 'v1.21.0_next' into dev/afierka/1.21-fix-corss-nodes-flags
michalkuligowski Apr 16, 2025
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13 changes: 13 additions & 0 deletions vllm/executor/ray_distributed_executor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -141,6 +141,14 @@ def _init_workers_ray(self, placement_group: "PlacementGroup",
**ray_remote_kwargs):
num_gpus = envs.VLLM_RAY_PER_WORKER_GPUS

def retain_envs(var_name):
retain_var_list = [
'GLOO_SOCKET_IFNAME', 'HCCL_SOCKET_IFNAME',
'NCCL_SOCKET_IFNAME'
]
return ('HPU' in var_name or 'RAY' in var_name
or 'VLLM' in var_name or var_name in retain_var_list)

# The driver dummy worker does not actually use any resources.
# It holds the resource for the driver worker.
self.driver_dummy_worker: Optional[RayWorkerWrapper] = None
Expand Down Expand Up @@ -198,11 +206,16 @@ def _init_workers_ray(self, placement_group: "PlacementGroup",
)(RayWorkerWrapper).remote(vllm_config=self.vllm_config,
rpc_rank=rank)
else:
runtime_env_vars = {
k: v
for k, v in os.environ.items() if retain_envs(k)
}
worker = ray.remote(
num_cpus=0,
num_gpus=0,
resources={current_platform.ray_device_key: num_gpus},
scheduling_strategy=scheduling_strategy,
runtime_env={"env_vars": runtime_env_vars},
**ray_remote_kwargs,
)(RayWorkerWrapper).remote(vllm_config=self.vllm_config,
rpc_rank=rank)
Expand Down