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[BugFix] Improve internal DP load balancing

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Signed-off-by: Nick Hill <nhill@redhat.com>
This commit is contained in:
Nick Hill 2025-07-25 14:48:25 +01:00
parent 8ed01e32f7
commit 8177e2f02f
4 changed files with 85 additions and 55 deletions
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98
vllm/v1/engine/coordinator.py
View File

@ -1,5 +1,6 @@
# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import copy
import multiprocessing
import time
import weakref
@ -66,18 +67,14 @@ class DPCoordinator:
# Assume coordinator is colocated with front-end procs when not in
# either external or hybrid DP LB mode.
local_only = not (external_lb or hybrid_lb)
front_publish_address = get_engine_client_zmq_addr(
local_only=not external_lb and not hybrid_lb, host=host)
local_only=local_only, host=host)
local_only_eng = dp_size == parallel_config.data_parallel_size_local
back_publish_address = get_engine_client_zmq_addr(local_only_eng, host)
back_output_address = get_engine_client_zmq_addr(local_only_eng, host)
# When in external LB mode, load stats aren't published, only changes
# to request wave / running state, so we don't need to rate-limit the
# updates to the front-end proc(s).
min_stats_update_interval_ms = 0 if external_lb else 100
context = get_mp_context()
self.proc: multiprocessing.Process = context.Process(
target=DPCoordinatorProc.run_coordinator,
@ -87,7 +84,6 @@ class DPCoordinator:
"front_publish_address": front_publish_address,
"back_output_address": back_output_address,
"back_publish_address": back_publish_address,
"min_stats_update_interval_ms": min_stats_update_interval_ms,
},
daemon=True)
self.proc.start()
@ -126,10 +122,6 @@ class DPCoordinatorProc:
self.stats_update_interval_ms = min_stats_update_interval_ms
self.current_wave = 0
self.engines_running = False
self.stats_changed = False
@staticmethod
def run_coordinator(
engine_count: int,
@ -156,6 +148,13 @@ class DPCoordinatorProc:
decoder = MsgpackDecoder(EngineCoreOutputs)
current_wave = 0
engines_running = False
stats_changed = False
last_stats_step = -1
last_step_counts: Optional[list[list[int]]] = None
with make_zmq_socket(
path=front_publish_address, # IPC
ctx=self.ctx,
@ -180,21 +179,33 @@ class DPCoordinatorProc:
while True:
elapsed = int(time.time() * 1000) - last_publish_time
# Send at stats_update_interval_ms interval if the stats have
# changed, or otherwise every 4 seconds.
# changed, or otherwise every 5 seconds.
wait_for = (self.stats_update_interval_ms
if self.stats_changed else 4000)
events = poller.poll(timeout=max(0, wait_for - elapsed))
if stats_changed else 5000)
# Wait at least 50ms to ensure we've received all stats for
# the current step.
min_timeout = 50 if last_step_counts is None else 0
events = poller.poll(timeout=max(min_timeout, wait_for -
elapsed))
if not events:
# Poller timeout - publish current stats to front-ends.
engine_req_counts_list = self._get_engine_counts()
to_publish = (engine_req_counts_list, self.current_wave,
self.engines_running)
if last_step_counts is not None:
engine_req_counts_list = last_step_counts
last_step_counts = None
else:
engine_req_counts_list = self._get_engine_counts()
stats_changed = False
to_publish = (engine_req_counts_list, current_wave,
engines_running)
publish_front.send(msgspec.msgpack.encode(to_publish))
last_publish_time = int(time.time() * 1000)
self.stats_changed = False
continue
events = dict(events)
wave_state_changed = False
if publish_front in events:
buffer = publish_front.recv()
@ -221,7 +232,7 @@ class DPCoordinatorProc:
# current_wave
# we note that 0 is the wave number for the new
# engine
self.engines_running = False
engines_running = False
logger.info(
"DPCoordinator scaled up from %s to %s "
"engines", current_count, new_engine_count)
@ -237,15 +248,15 @@ class DPCoordinatorProc:
# engines are paused, so that we can wake the other
# engines.
engine_to_exclude, wave = decoded
if not self.engines_running:
if wave < self.current_wave:
if not engines_running:
if wave < current_wave:
# If the wave number is stale, ensure the message
# is handled by all the engines.
engine_to_exclude = None
self.engines_running = True
self.stats_changed = True
self._send_start_wave(publish_back, self.current_wave,
engines_running = True
wave_state_changed = True
self._send_start_wave(publish_back, current_wave,
engine_to_exclude)
if output_back in events:
@ -263,36 +274,47 @@ class DPCoordinatorProc:
# 1. Updated request load stats - update our local
# state with these.
stats = self.engines[eng_index].request_counts
stats_step = scheduler_stats.step_counter
if stats_changed and stats_step != last_stats_step:
last_step_counts = self._get_engine_counts(
do_copy=True)
elif stats_step < last_stats_step:
logger.warning("Received stats for out-of-order "
"step from engine {eng_index}")
stats[0] = scheduler_stats.num_waiting_reqs
stats[1] = scheduler_stats.num_running_reqs
self.stats_changed = True
last_stats_step = stats_step
stats_changed = True
if (wave := outputs.wave_complete) is not None:
# 2. Notification from rank 0 engine that we've
# moved into the global paused state
# (engines_running==False).
if self.current_wave <= wave:
if current_wave <= wave:
new_wave = wave + 1
logger.debug("Moving DP wave from %d to %d.",
self.current_wave, new_wave)
self.current_wave = new_wave
self.engines_running = False
self.stats_changed = True
current_wave, new_wave)
current_wave = new_wave
engines_running = False
wave_state_changed = True
elif (wave := outputs.start_wave) is not None and (
wave > self.current_wave or
(wave == self.current_wave
and not self.engines_running)):
wave > current_wave or
(wave == current_wave and not engines_running)):
# 3. The engine received request for a non-current wave
# so we must ensure that other engines progress to the
# next wave (race condition handling).
logger.debug(
"Starting wave %d after notification of "
"stale wave request from engine.", wave)
self.current_wave = wave
self.engines_running = True
self.stats_changed = True
current_wave = wave
engines_running = True
wave_state_changed = True
self._send_start_wave(publish_back, wave, eng_index)
if wave_state_changed:
message = (None, current_wave, engines_running)
publish_front.send(msgspec.msgpack.encode(message))
@staticmethod
def _send_start_wave(socket: zmq.Socket, wave: int,
exclude_engine_index: Optional[int]):
@ -305,6 +327,8 @@ class DPCoordinatorProc:
socket.send_multipart(
(EngineCoreRequestType.START_DP_WAVE.value, wave_encoded))
def _get_engine_counts(self) -> list[list[int]]:
def _get_engine_counts(self, do_copy=False) -> list[list[int]]:
"""Return list of [waiting, running] count lists for each engine."""
if do_copy:
return [copy.copy(e.request_counts) for e in self.engines]
return [e.request_counts for e in self.engines]

10
vllm/v1/engine/core.py
View File

@ -874,7 +874,7 @@ class DPEngineCoreProc(EngineCoreProc):
# Counts forward-passes of the model so that we can synchronize
# finished with DP peers every N steps.
self.counter = 0
self.step_counter = 0
self.current_wave = 0
self.last_counts = (0, 0)
@ -954,7 +954,7 @@ class DPEngineCoreProc(EngineCoreProc):
counts = self.scheduler.get_request_counts()
if counts != self.last_counts:
self.last_counts = counts
stats = SchedulerStats(*counts)
stats = SchedulerStats(*counts, step_counter=self.step_counter)
self.output_queue.put_nowait(
(-1, EngineCoreOutputs(scheduler_stats=stats)))
@ -1001,10 +1001,10 @@ class DPEngineCoreProc(EngineCoreProc):
def _has_global_unfinished_reqs(self, local_unfinished: bool) -> bool:
# Optimization - only perform finish-sync all-reduce every 32 steps.
self.counter += 1
if self.counter != 32:
self.step_counter += 1
if self.step_counter != 32:
return True
self.counter = 0
self.step_counter = 0
return ParallelConfig.has_unfinished_dp(self.dp_group,
local_unfinished)

30
vllm/v1/engine/core_client.py
View File

@ -970,7 +970,12 @@ class DPAsyncMPClient(AsyncMPClient):
counts, wave, running = msgspec.msgpack.decode(buf)
self.current_wave = wave
self.engines_running = running
self.lb_engines = counts[count_slice]
if counts is not None:
sliced_counts = counts[count_slice]
self.lb_engines = sliced_counts
#TODO TBD whether to keep this debug log
logger.debug("Received counts: %s (%s)",
sliced_counts, count_slice)
resources.stats_update_task = asyncio.create_task(
run_engine_stats_update_task())
@ -1019,27 +1024,26 @@ class DPLBAsyncMPClient(DPAsyncMPClient):
def get_core_engine_for_request(
self, request: EngineCoreRequest) -> EngineIdentity:
# Engines are in rank order.
current_counts = self.lb_engines
if (eng_index := request.data_parallel_rank) is None:
if not self.lb_engines:
if not current_counts:
return self.core_engine
# TODO use P2C alg for larger DP sizes
num_engines = len(self.lb_engines)
min_counts = [sys.maxsize, sys.maxsize]
num_engines = len(current_counts)
min_score = sys.maxsize
eng_index = 0
for i in range(num_engines):
# Start from client_index to help with balancing when engines
# are empty.
idx = (self.client_index + i) % num_engines
counts = self.lb_engines[idx]
if counts < min_counts:
min_counts = counts
waiting, running = current_counts[idx]
score = waiting * 4 + running
if score < min_score:
min_score = score
eng_index = idx
# Adjust local counts for better balancing between stats updates
# from the coordinator (which happen every 100ms).
if min_counts[0]:
min_counts[0] += 1
else:
min_counts[1] += 1
# Increment local waiting count for better balancing between stats
# updates from the coordinator (which happen every 100ms).
current_counts[eng_index][0] += 1
chosen_engine = self.core_engines[eng_index]
# Record which engine is chosen for this request, to handle aborts.

2
vllm/v1/metrics/stats.py
View File

@ -33,6 +33,8 @@ class SchedulerStats:
num_running_reqs: int = 0
num_waiting_reqs: int = 0
step_counter: int = 0
kv_cache_usage: float = 0.0
prefix_cache_stats: PrefixCacheStats = field(