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enable multi-node in external launcher mode #29833

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Merged
zhuohan123 merged 1 commit into from
Dec 4, 2025
Merged

enable multi-node in external launcher mode #29833

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8 changes: 6 additions & 2 deletions vllm/config/parallel.py
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Original file line number Diff line number Diff line change
Expand Up @@ -593,10 +593,14 @@ def __post_init__(self) -> None:
"max_parallel_loading_workers is currently "
"not supported and will be ignored."
)
if self.distributed_executor_backend not in ("mp", "uni") and self.nnodes > 1:
allowed_backends = ("mp", "uni", "external_launcher")
if (
self.distributed_executor_backend not in allowed_backends
and self.nnodes > 1
):
raise ValueError(
"nnodes > 1 can only be set when distributed executor "
"backend is mp or uni."
"backend is mp, uni or external_launcher."
)

@property
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39 changes: 21 additions & 18 deletions vllm/distributed/parallel_state.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1169,33 +1169,36 @@ def init_distributed_environment(
from vllm.config import get_current_vllm_config

config = get_current_vllm_config()
if config is not None and config.parallel_config.nnodes > 1:
parallel_config = config.parallel_config
ip = parallel_config.master_addr
rank = parallel_config.data_parallel_rank * world_size + rank
world_size = parallel_config.world_size_across_dp
port = parallel_config.master_port
distributed_init_method = get_distributed_init_method(ip, port)
elif (
if (
config is not None
and config.parallel_config.data_parallel_size > 1
and config.parallel_config.distributed_executor_backend != "external_launcher"
and (
config.parallel_config.nnodes > 1
or config.parallel_config.data_parallel_size > 1
)
):
parallel_config = config.parallel_config
# adjust to take into account data parallelism
# offset the rank by the data parallel rank
rank = parallel_config.data_parallel_rank * world_size + rank
# adjust the world size to take into account data parallelism
world_size = parallel_config.world_size_across_dp
ip = parallel_config.data_parallel_master_ip
port = parallel_config.get_next_dp_init_port()
distributed_init_method = get_distributed_init_method(ip, port)
logger.debug(
"Adjusting world_size=%d rank=%d distributed_init_method=%s for DP",
world_size,
rank,
distributed_init_method,
)

# Use appropriate IP and port based on configuration
if parallel_config.nnodes > 1:
ip = parallel_config.master_addr
port = parallel_config.master_port
distributed_init_method = get_distributed_init_method(ip, port)
else:
ip = parallel_config.data_parallel_master_ip
port = parallel_config.get_next_dp_init_port()
distributed_init_method = get_distributed_init_method(ip, port)
logger.debug(
"Adjusting world_size=%d rank=%d distributed_init_method=%s for DP",
world_size,
rank,
distributed_init_method,
)
if not torch.distributed.is_initialized():
logger.info(
"world_size=%d rank=%d local_rank=%d distributed_init_method=%s backend=%s",
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