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[bugfix][async scheduling] fix extra cuda context in device 0 with EP/DP #37449

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Merged
youkaichao merged 1 commit into from
Mar 18, 2026
Merged

[bugfix][async scheduling] fix extra cuda context in device 0 with EP/DP #37449

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34 changes: 23 additions & 11 deletions vllm/v1/executor/multiproc_executor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -597,17 +597,6 @@ def __init__(
wrapper.init_worker(all_kwargs)
self.worker = wrapper

scheduler_config = vllm_config.scheduler_config
self.use_async_scheduling = scheduler_config.async_scheduling
if self.use_async_scheduling:
self.async_output_queue: queue.Queue = queue.Queue()
self.async_output_copy_thread = Thread(
target=self.async_output_busy_loop,
daemon=True,
name="WorkerAsyncOutputCopy",
)
self.async_output_copy_thread.start()

self.setup_proc_title_and_log_prefix(
enable_ep=vllm_config.parallel_config.enable_expert_parallel
)
Expand All @@ -622,6 +611,17 @@ def __init__(
)
self.worker.load_model()

scheduler_config = vllm_config.scheduler_config
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@youkaichao youkaichao Mar 18, 2026

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move this part of code here, to be after self.worker.init_device(), so that self.worker.device is initialized properly.

self.use_async_scheduling = scheduler_config.async_scheduling
if self.use_async_scheduling:
self.async_output_queue: queue.Queue = queue.Queue()
self.async_output_copy_thread = Thread(
target=self.async_output_busy_loop,
daemon=True,
name="WorkerAsyncOutputCopy",
)
self.async_output_copy_thread.start()

# Set block size based on the attention backends
current_platform.update_block_size_for_backend(vllm_config)

Expand Down Expand Up @@ -911,6 +911,18 @@ def handle_output(self, output: Any):

def async_output_busy_loop(self):
"""Entrypoint for the thread which handles outputs asynchronously."""

# set device to the worker device for the thread.
# a thread will not inherit the context of the main thread.
# when calling any cuda runtime functions, it will implicitly
# create a new cuda context on device 0, consuming extra memory.
# here we set the device to the worker device for the thread,
# enforcing the context to be the same as the main thread.
from vllm.platforms import current_platform

if hasattr(self.worker, "device"):
current_platform.set_device(self.worker.device)

while True:
output = self.async_output_queue.get()
self.enqueue_output(output)
Expand Down
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