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[UX] Replace VLLM_ALL2ALL_BACKEND with --all2all-backend (#26732)

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Signed-off-by: mgoin <mgoin64@gmail.com>
This commit is contained in:
Michael Goin
2025-10-13 21:12:52 -04:00
committed by GitHub
parent 8317f72354
commit 3e051bda82
12 changed files with 90 additions and 51 deletions
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3
vllm/distributed/device_communicators/base_device_communicator.py
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@@ -111,6 +111,7 @@ class DeviceCommunicatorBase:
self.rank_in_group = dist.get_group_rank(self.cpu_group, self.global_rank)
use_ep = False
all2all_backend = None
from vllm.config import get_current_vllm_config
config = get_current_vllm_config()
@@ -119,9 +120,11 @@ class DeviceCommunicatorBase:
# where all data parallel ranks execute forward together),
# we initialize the all2all manager used in expert parallel.
use_ep = config.parallel_config.data_parallel_size > 1
all2all_backend = config.parallel_config.all2all_backend
self.is_ep_communicator = "ep" in unique_name
self.use_all2all = self.is_ep_communicator and use_ep
self.all2all_backend = all2all_backend
self.all2all_manager: All2AllManagerBase | None = None
def all_reduce(self, input_: torch.Tensor) -> torch.Tensor:

15
vllm/distributed/device_communicators/cuda_communicator.py
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@@ -91,33 +91,32 @@ class CudaCommunicator(DeviceCommunicatorBase):
self.qr_comm = QuickAllReduce(group=self.cpu_group, device=self.device)
if self.use_all2all:
all2all_backend = envs.VLLM_ALL2ALL_BACKEND
if all2all_backend == "naive":
if self.all2all_backend == "naive":
from .all2all import NaiveAll2AllManager
self.all2all_manager = NaiveAll2AllManager(self.cpu_group)
elif all2all_backend == "allgather_reducescatter":
elif self.all2all_backend == "allgather_reducescatter":
from .all2all import AgRsAll2AllManager
self.all2all_manager = AgRsAll2AllManager(self.cpu_group)
elif all2all_backend == "pplx":
elif self.all2all_backend == "pplx":
from .all2all import PPLXAll2AllManager
self.all2all_manager = PPLXAll2AllManager(self.cpu_group)
elif all2all_backend == "deepep_high_throughput":
elif self.all2all_backend == "deepep_high_throughput":
from .all2all import DeepEPHTAll2AllManager
self.all2all_manager = DeepEPHTAll2AllManager(self.cpu_group)
elif all2all_backend == "deepep_low_latency":
elif self.all2all_backend == "deepep_low_latency":
from .all2all import DeepEPLLAll2AllManager
self.all2all_manager = DeepEPLLAll2AllManager(self.cpu_group)
elif all2all_backend == "flashinfer_all2allv":
elif self.all2all_backend == "flashinfer_all2allv":
from .all2all import FlashInferAllToAllManager
self.all2all_manager = FlashInferAllToAllManager(self.cpu_group)
else:
raise ValueError(f"Unknown all2all backend: {all2all_backend}")
raise ValueError(f"Unknown all2all backend: {self.all2all_backend}")
if is_global_first_rank():
logger.info(

12
vllm/distributed/device_communicators/xpu_communicator.py
View File

@@ -6,7 +6,6 @@ import torch
import torch.distributed as dist
from torch.distributed import ProcessGroup
import vllm.envs as envs
from vllm.logger import init_logger
from .base_device_communicator import DeviceCommunicatorBase
@@ -24,15 +23,14 @@ class XpuCommunicator(DeviceCommunicatorBase):
):
super().__init__(cpu_group, device, device_group, unique_name)
if self.use_all2all:
all2all_backend = envs.VLLM_ALL2ALL_BACKEND
if all2all_backend != "naive":
if self.all2all_backend != "naive":
logger.warning(
"`%s` all2all manager is not supported on XPU."
"`%s` all2all manager is not supported on XPU. "
"Falling back to `naive` all2all manager for XPU.",
all2all_backend,
self.all2all_backend,
)
all2all_backend = "naive"
if all2all_backend == "naive":
self.all2all_backend = "naive"
if self.all2all_backend == "naive":
from .all2all import NaiveAll2AllManager
self.all2all_manager = NaiveAll2AllManager(self.cpu_group)