[V1][PP] Optimization: continue scheduling prefill chunks (vllm-project#17080)

Signed-off-by: Rui Qiao <[email protected]>

Author: ruisearch42

tests/v1/core/test_scheduler.py

@@ -437,7 +437,6 @@ def test_stop_via_update_from_output():
         req.num_computed_tokens = req.num_tokens
         scheduler.requests[req.request_id] = req
         scheduler.running.append(req)
-        scheduler.scheduled_req_ids.add(req.request_id)
 
     scheduler_output = SchedulerOutput(scheduled_new_reqs=[],
                                        scheduled_cached_reqs=[],
@@ -489,7 +488,6 @@ def test_stop_via_update_from_output():
         req.num_computed_tokens = req.num_tokens
         scheduler.requests[req.request_id] = req
         scheduler.running.append(req)
-        scheduler.scheduled_req_ids.add(req.request_id)
 
     scheduler_output = SchedulerOutput(scheduled_new_reqs=[],
                                        scheduled_cached_reqs=[],
@@ -539,7 +537,6 @@ def test_stop_via_update_from_output():
         req.num_computed_tokens = req.num_tokens
         scheduler.requests[req.request_id] = req
         scheduler.running.append(req)
-        scheduler.scheduled_req_ids.add(req.request_id)
 
     scheduler_output = SchedulerOutput(scheduled_new_reqs=[],
                                        scheduled_cached_reqs=[],
@@ -589,7 +586,6 @@ def test_stop_via_update_from_output():
     requests[0].num_computed_tokens = requests[0].num_tokens
     scheduler.requests[requests[0].request_id] = requests[0]
     scheduler.running.append(requests[0])
-    scheduler.scheduled_req_ids.add(requests[0].request_id)
 
     scheduler_output = SchedulerOutput(
         scheduled_new_reqs=[],

tests/v1/engine/test_engine_core.py

@@ -1,10 +1,9 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import copy
-import threading
 import time
 import uuid
-from concurrent.futures import Future
+from concurrent.futures import Future, ThreadPoolExecutor
 
 import pytest
 from transformers import AutoTokenizer
@@ -244,33 +243,33 @@ def initialize_from_config(
                 self, kv_cache_configs: list[KVCacheConfig]) -> None:
             super().initialize_from_config(kv_cache_configs)
 
-            # This executor actually can only run 1 batch at a time
-            self.semaphore = threading.Semaphore(1)
+            # Create a thread pool with a single worker
+            self.thread_pool = ThreadPoolExecutor(max_workers=1)
 
         def execute_model(
             self,
             scheduler_output,
         ) -> Future[ModelRunnerOutput]:
             """Make execute_model non-blocking."""
-            future: Future[ModelRunnerOutput] = Future()
 
-            def _thread_wrapper(scheduler_output, future):
-                with self.semaphore:
-                    output = self.collective_rpc("execute_model",
-                                                 args=(scheduler_output, ))
-                    # Make a copy because output[0] may be reused
-                    # by the next batch.
-                    output = copy.deepcopy(output[0])
-                    future.set_result(output)
+            def _execute():
+                output = self.collective_rpc("execute_model",
+                                             args=(scheduler_output, ))
+                # Make a copy because output[0] may be reused
+                # by the next batch.
+                return copy.deepcopy(output[0])
 
-            threading.Thread(target=_thread_wrapper,
-                             args=(scheduler_output, future)).start()
-            return future
+            # Use the thread pool instead of creating a new thread
+            return self.thread_pool.submit(_execute)
 
         @property
         def max_concurrent_batches(self) -> int:
             return 2
 
+        def shutdown(self):
+            if hasattr(self, 'thread_pool'):
+                self.thread_pool.shutdown(wait=False)
+
     with monkeypatch.context() as m:
         m.setenv("VLLM_USE_V1", "1")
 
@@ -299,14 +298,77 @@ def max_concurrent_batches(self) -> int:
         # Schedule Batch 1: (10, req0)
         assert engine_core.step_with_batch_queue() is None
         assert engine_core.batch_queue.qsize() == 1
+        scheduler_output = engine_core.batch_queue.queue[-1][1]
+        assert scheduler_output.num_scheduled_tokens[0] == 10
+        # num_computed_tokens should have been updated immediately.
+        assert engine_core.scheduler.requests[
+            req0.request_id].num_computed_tokens == 10
+
+        # Schedule Batch 2: (2, req0), (8, req1)
         assert engine_core.step_with_batch_queue() is None
         assert engine_core.batch_queue.qsize() == 2
+        scheduler_output = engine_core.batch_queue.queue[-1][1]
+        assert scheduler_output.num_scheduled_tokens[0] == 2
+        assert scheduler_output.num_scheduled_tokens[1] == 8
+        # num_computed_tokens should have been updated immediately.
+        assert engine_core.scheduler.requests[0].num_computed_tokens == 12
+        assert engine_core.scheduler.requests[1].num_computed_tokens == 8
+
         assert engine_core.scheduler.get_num_unfinished_requests() == 2
 
-        # Loop through both requests.
-        while engine_core.scheduler.get_num_unfinished_requests() == 2:
-            engine_core.step_with_batch_queue()
+        # Batch queue is full. Finish Batch 1.
+        engine_core.step_with_batch_queue()
+
+        # Schedule Batch 3: (4, req1). Note that req0 cannot be scheduled
+        # because it is in the decoding stage now.
+        engine_core.step_with_batch_queue()
+        assert engine_core.batch_queue.qsize() == 2
+        scheduler_output = engine_core.batch_queue.queue[-1][1]
+        assert scheduler_output.num_scheduled_tokens[1] == 4
 
-        # Reaching here when got the result of the first request.
-        while engine_core.scheduler.get_num_unfinished_requests() == 1:
-            engine_core.step_with_batch_queue()
+        # Batch queue is full. Finish Batch 2. Get first token of req0.
+        output = engine_core.step_with_batch_queue()
+        assert output is not None
+        assert len(output.outputs) == 1
+        assert engine_core.scheduler.requests[req0.request_id].num_tokens == 13
+
+        # Schedule Batch 4: (1, req0).
+        engine_core.step_with_batch_queue()
+        assert engine_core.batch_queue.qsize() == 2
+        scheduler_output = engine_core.batch_queue.queue[-1][1]
+        assert scheduler_output.num_scheduled_tokens[0] == 1
+
+        # Batch queue is full. Finish Batch 3. Get first token of req1.
+        output = engine_core.step_with_batch_queue()
+        assert output is not None
+        assert len(output.outputs) == 1
+        assert engine_core.scheduler.requests[req1.request_id].num_tokens == 13
+
+        # Schedule Batch 5: (1, req1).
+        engine_core.step_with_batch_queue()
+        assert engine_core.batch_queue.qsize() == 2
+        scheduler_output = engine_core.batch_queue.queue[-1][1]
+        assert scheduler_output.num_scheduled_tokens[1] == 1
+
+        # Loop until req0 is finished.
+        step = 0
+        req_id = 0
+        expected_num_tokens = [
+            engine_core.scheduler.requests[0].num_tokens + 1,
+            engine_core.scheduler.requests[1].num_tokens + 1,
+        ]
+        while engine_core.scheduler.get_num_unfinished_requests() == 2:
+            output = engine_core.step_with_batch_queue()
+            if step % 2 == 0:
+                # Even steps consumes an output.
+                assert output is not None
+                assert len(output.outputs) == 1
+                if req_id in engine_core.scheduler.requests:
+                    assert engine_core.scheduler.requests[
+                        req_id].num_tokens == expected_num_tokens[req_id]
+                expected_num_tokens[req_id] += 1
+                req_id = (req_id + 1) % 2
+            else:
+                # Odd steps schedules a new batch.
+                assert output is None
+            step += 1

vllm/v1/core/sched/interface.py

@@ -117,11 +117,6 @@ def has_requests(self) -> bool:
         not yet returned in SchedulerOutputs."""
         return self.has_unfinished_requests() or self.has_finished_requests()
 
-    @abstractmethod
-    def get_num_unscheduled_requests(self) -> int:
-        """Number of requests that are not being processed by the executor."""
-        raise NotImplementedError
-
     @abstractmethod
     def reset_prefix_cache(self) -> bool:
         """Reset the prefix cache for KV cache.

vllm/v1/core/sched/scheduler.py

@@ -3,7 +3,7 @@
 from __future__ import annotations
 
 import time
-from collections import deque
+from collections import defaultdict, deque
 from collections.abc import Iterable
 from typing import Optional, Union
 
@@ -88,9 +88,6 @@ def __init__(
         # Priority queues for requests.
         self.waiting: deque[Request] = deque()
         self.running: list[Request] = []
-        # The requests that have been scheduled and are being executed
-        # by the executor.
-        self.scheduled_req_ids: set[str] = set()
 
         # The request IDs that are finished in between the previous and the
         # current steps. This is used to notify the workers about the finished
@@ -100,8 +97,9 @@ def __init__(
 
         # OPTIMIZATION: Cache the CachedRequestData objects to avoid creating
         # them at each scheduling step.
-        # Request id -> CachedRequestData
-        self._cached_reqs_data: dict[str, CachedRequestData] = {}
+        # Request id -> deque of CachedRequestData
+        self._cached_reqs_data: dict[
+            str, deque[CachedRequestData]] = defaultdict(deque)
 
         # Encoder-related.
         # Calculate encoder cache size if applicable
@@ -171,10 +169,6 @@ def schedule(self) -> SchedulerOutput:
         req_index = 0
         while req_index < len(self.running) and token_budget > 0:
             request = self.running[req_index]
-            if request.request_id in self.scheduled_req_ids:
-                # This request has already been scheduled.
-                req_index += 1
-                continue
 
             num_new_tokens = (request.num_tokens_with_spec -
                               request.num_computed_tokens)
@@ -183,33 +177,35 @@ def schedule(self) -> SchedulerOutput:
                 num_new_tokens = (
                     self.scheduler_config.long_prefill_token_threshold)
             num_new_tokens = min(num_new_tokens, token_budget)
-            assert num_new_tokens > 0
 
             # Make sure the input position does not exceed the max model len.
             # This is necessary when using spec decoding.
             num_new_tokens = min(
                 num_new_tokens,
                 self.max_model_len - request.num_computed_tokens)
-            assert num_new_tokens > 0
 
             # Schedule encoder inputs.
+            encoder_inputs_to_schedule = None
+            new_encoder_budget = encoder_budget
             if request.has_encoder_inputs:
                 (encoder_inputs_to_schedule, num_new_tokens,
                  new_encoder_budget) = self._try_schedule_encoder_inputs(
                      request, request.num_computed_tokens, num_new_tokens,
                      encoder_budget)
-                if num_new_tokens == 0:
-                    # The request cannot be scheduled because the encoder budget
-                    # or the encoder cache is exhausted.
-                    # NOTE(woosuk): By using `continue` instead of `break` here,
-                    # we intentionally relax the strict FCFS scheduling policy
-                    # to allow lower-priority requests to be scheduled when a
-                    # higher-priority request is blocked by encoder constraints.
-                    req_index += 1
-                    continue
-            else:
-                encoder_inputs_to_schedule = None
-                new_encoder_budget = encoder_budget
+
+            if num_new_tokens == 0:
+                # The request cannot be scheduled because one of the following
+                # reasons:
+                # 1. No new tokens to schedule. This may happen when PP>1 and
+                #    we have already scheduled all prompt tokens but they are
+                #    not finished yet.
+                # 2. The encoder budget is exhausted.
+                # 3. The encoder cache is exhausted.
+                # NOTE(woosuk): Here, by doing `continue` instead of `break`,
+                # we do not strictly follow the FCFS scheduling policy and
+                # allow the lower-priority requests to be scheduled.
+                req_index += 1
+                continue
 
             while True:
                 new_blocks = self.kv_cache_manager.allocate_slots(
@@ -243,7 +239,6 @@ def schedule(self) -> SchedulerOutput:
 
             # Schedule the request.
             scheduled_running_reqs.append(request)
-            self.scheduled_req_ids.add(request.request_id)
             if request.use_structured_output:
                 # PERF: in case of chunked prefill,
                 # request might not include any new tokens.
@@ -382,7 +377,6 @@ def schedule(self) -> SchedulerOutput:
                         request.request_id] = req_index
                 req_index += 1
                 self.running.append(request)
-                self.scheduled_req_ids.add(request.request_id)
                 if self.log_stats:
                     request.record_event(EngineCoreEventType.SCHEDULED,
                                          scheduled_timestamp)
@@ -521,18 +515,21 @@ def _make_cached_request_data(
         num_regular_tokens = num_scheduled_tokens - num_scheduled_spec_tokens
         new_token_ids = request.all_token_ids[
             num_computed_tokens:num_computed_tokens + num_regular_tokens]
-        req_data = self._cached_reqs_data.get(request.request_id)
-        if req_data is not None:
+
+        req_data_queue = self._cached_reqs_data.get(request.request_id)
+        if req_data_queue:
+            req_data = req_data_queue.popleft()
             req_data.resumed_from_preemption = resumed_from_preemption
             req_data.new_token_ids = new_token_ids
             req_data.new_block_ids = new_block_ids
             req_data.num_computed_tokens = num_computed_tokens
         else:
+            # No cached request data, or all cached request data has been
+            # used by the scheduled requests.
             req_data = CachedRequestData.from_request(request,
                                                       resumed_from_preemption,
                                                       new_token_ids,
                                                       new_block_ids)
-            self._cached_reqs_data[request.request_id] = req_data
         return req_data
 
     def _try_schedule_encoder_inputs(
@@ -561,6 +558,8 @@ def _try_schedule_encoder_inputs(
         Note that num_computed_tokens includes both locally cached
         blocks and externally cached blocks (via KVConnector).
         """
+        if num_new_tokens == 0 or not request.has_encoder_inputs:
+            return [], num_new_tokens, encoder_budget
         encoder_inputs_to_schedule: list[int] = []
         mm_positions = request.mm_positions
         assert mm_positions is not None
@@ -728,10 +727,13 @@ def update_from_output(
                 # Invariant: EngineCore returns no partial prefill outputs.
                 assert not prompt_logprobs_tensors
 
-            self.scheduled_req_ids.remove(req_id)
             if not stopped:
                 new_running.append(request)
 
+        # Return the cached request data to the queue so they can be reused.
+        for req_data in scheduler_output.scheduled_cached_reqs:
+            self._cached_reqs_data[req_data.req_id].append(req_data)
+
         self.running = new_running
         engine_core_outputs = EngineCoreOutputs(
             outputs=outputs,
@@ -774,7 +776,6 @@ def finish_requests(
 
             if request.status == RequestStatus.RUNNING:
                 self.running.remove(request)
-                self.scheduled_req_ids.discard(request.request_id)
             else:
                 self.waiting.remove(request)
             request.status = finished_status
@@ -795,10 +796,6 @@ def get_num_unfinished_requests(self) -> int:
     def has_finished_requests(self) -> bool:
         return len(self.finished_req_ids) > 0
 
-    def get_num_unscheduled_requests(self) -> int:
-        """Number of requests that are not being processed by the executor."""
-        return self.get_num_unfinished_requests() - len(self.scheduled_req_ids)
-
     def reset_prefix_cache(self) -> bool:
         return self.kv_cache_manager.reset_prefix_cache()