[Optimization] Make new_block_ids None if empty (#23262)

Signed-off-by: Woosuk Kwon <woosuk@thinkingmachines.ai>

vllm/v1/core/kv_cache_manager.py

@@ -2,7 +2,7 @@
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 from dataclasses import dataclass
-from typing import Optional
+from typing import Literal, Optional, overload
 
 from vllm.distributed.kv_events import KVCacheEvent
 from vllm.logger import init_logger
@@ -37,7 +37,24 @@ class KVCacheBlocks:
             tuple(blk1 + blk2
                   for blk1, blk2 in zip(self.blocks, other.blocks)))
 
-    def get_block_ids(self) -> tuple[list[int], ...]:
+    @overload
+    def get_block_ids(
+        self,
+        allow_none: Literal[False] = False,
+    ) -> tuple[list[int], ...]:
+        ...
+
+    @overload
+    def get_block_ids(
+        self,
+        allow_none: Literal[True] = True,
+    ) -> Optional[tuple[list[int], ...]]:
+        ...
+
+    def get_block_ids(
+        self,
+        allow_none: bool = False,
+    ):
         """
         Converts the KVCacheBlocks instance to block_ids.
         
@@ -46,6 +63,8 @@ class KVCacheBlocks:
             * the outer tuple corresponds to KV cache groups
             * each inner list contains the block_ids of the blocks in that group
         """
+        if allow_none and all(len(group) == 0 for group in self.blocks):
+            return None
         return tuple([blk.block_id for blk in group] for group in self.blocks)
 
     def get_unhashed_block_ids(self) -> list[int]:
@@ -348,10 +367,13 @@ class KVCacheManager:
         """
         return self.block_pool.take_events()
 
+    def get_blocks(self, request_id: str) -> KVCacheBlocks:
+        """Get the blocks of a request."""
+        return KVCacheBlocks(self.coordinator.get_blocks(request_id))
+
     def get_block_ids(self, request_id: str) -> tuple[list[int], ...]:
         """Get the block ids of a request."""
-        return KVCacheBlocks(
-            self.coordinator.get_blocks(request_id)).get_block_ids()
+        return self.get_blocks(request_id).get_block_ids()
 
     def cache_blocks(self, request: Request, num_computed_tokens: int) -> None:
         """Cache the blocks for the request, if enabled."""

vllm/v1/core/sched/output.py

@@ -91,7 +91,7 @@ class CachedRequestData:
     # NOTE(woosuk): new_token_ids is only used for pipeline parallelism.
     # When PP is not used, new_token_ids will be empty.
     new_token_ids: list[list[int]]
-    new_block_ids: list[tuple[list[int], ...]]
+    new_block_ids: list[Optional[tuple[list[int], ...]]]
     num_computed_tokens: list[int]
 
     @property

vllm/v1/core/sched/scheduler.py

@@ -19,7 +19,7 @@ from vllm.logger import init_logger
 from vllm.multimodal import MULTIMODAL_REGISTRY, MultiModalRegistry
 from vllm.v1.core.encoder_cache_manager import (EncoderCacheManager,
                                                 compute_encoder_budget)
-from vllm.v1.core.kv_cache_manager import KVCacheManager
+from vllm.v1.core.kv_cache_manager import KVCacheBlocks, KVCacheManager
 from vllm.v1.core.sched.interface import SchedulerInterface
 from vllm.v1.core.sched.output import (CachedRequestData, NewRequestData,
                                        SchedulerOutput)
@@ -185,7 +185,7 @@ class Scheduler(SchedulerInterface):
         # uses structured decoding.
         structured_output_request_ids: dict[str, int] = {}
 
-        req_to_new_block_ids: dict[str, tuple[list[int], ...]] = {}
+        req_to_new_blocks: dict[str, KVCacheBlocks] = {}
         num_scheduled_tokens: dict[str, int] = {}
         token_budget = self.max_num_scheduled_tokens
         # Encoder-related.
@@ -288,8 +288,7 @@ class Scheduler(SchedulerInterface):
                 # Therefore, we might introduce some additional
                 # cycle to fill in the bitmask, which could be a big no-op.
                 structured_output_request_ids[request.request_id] = req_index
-            req_to_new_block_ids[request.request_id] = (
-                new_blocks.get_block_ids())
+            req_to_new_blocks[request.request_id] = new_blocks
             num_scheduled_tokens[request.request_id] = num_new_tokens
             token_budget -= num_new_tokens
             req_index += 1
@@ -496,8 +495,8 @@ class Scheduler(SchedulerInterface):
 
                 if self.lora_config and request.lora_request:
                     scheduled_loras.add(request.lora_request.lora_int_id)
-                req_to_new_block_ids[request.request_id] = (
-                    self.kv_cache_manager.get_block_ids(request.request_id))
+                req_to_new_blocks[request.request_id] = (
+                    self.kv_cache_manager.get_blocks(request.request_id))
                 num_scheduled_tokens[request.request_id] = num_new_tokens
                 token_budget -= num_new_tokens
                 request.status = RequestStatus.RUNNING
@@ -546,8 +545,8 @@ class Scheduler(SchedulerInterface):
         )
         # Construct the scheduler output.
         new_reqs_data = [
-            NewRequestData.from_request(req,
-                                        req_to_new_block_ids[req.request_id])
+            NewRequestData.from_request(
+                req, req_to_new_blocks[req.request_id].get_block_ids())
             for req in scheduled_new_reqs
         ]
         cached_reqs_data = self._make_cached_request_data(
@@ -555,7 +554,7 @@ class Scheduler(SchedulerInterface):
             scheduled_resumed_reqs,
             num_scheduled_tokens,
             scheduled_spec_decode_tokens,
-            req_to_new_block_ids,
+            req_to_new_blocks,
         )
         scheduler_output = SchedulerOutput(
             scheduled_new_reqs=new_reqs_data,
@@ -628,11 +627,11 @@ class Scheduler(SchedulerInterface):
         resumed_reqs: list[Request],
         num_scheduled_tokens: dict[str, int],
         spec_decode_tokens: dict[str, list[int]],
-        req_to_new_block_ids: dict[str, tuple[list[int], ...]],
+        req_to_new_blocks: dict[str, KVCacheBlocks],
     ) -> CachedRequestData:
         req_ids: list[str] = []
         new_token_ids: list[list[int]] = []
-        new_block_ids: list[tuple[list[int], ...]] = []
+        new_block_ids: list[Optional[tuple[list[int], ...]]] = []
         num_computed_tokens: list[int] = []
 
         use_connector = self.connector is not None
@@ -655,7 +654,8 @@ class Scheduler(SchedulerInterface):
                 # out of bounds errors. TODO: Remove this once the KVConnector
                 # is updated to handle token IDs properly.
                 new_token_ids.append([])
-            new_block_ids.append(req_to_new_block_ids[req_id])
+            new_block_ids.append(
+                req_to_new_blocks[req_id].get_block_ids(allow_none=True))
             num_computed_tokens.append(req.num_computed_tokens)
         # Because resumed_reqs is usually empty, it is more efficient to do
         # in-place appending so that we don't need to allocate a new list.

vllm/v1/worker/gpu_model_runner.py

@@ -574,11 +574,13 @@ class GPUModelRunner(LoRAModelRunnerMixin, KVConnectorModelRunnerMixin):
 
             # Update the block IDs.
             if not resumed_from_preemption:
-                # Append the new blocks to the existing block IDs.
-                for block_ids, new_ids in zip(req_state.block_ids,
-                                              new_block_ids):
-                    block_ids.extend(new_ids)
+                if new_block_ids is not None:
+                    # Append the new blocks to the existing block IDs.
+                    for block_ids, new_ids in zip(req_state.block_ids,
+                                                  new_block_ids):
+                        block_ids.extend(new_ids)
             else:
+                assert new_block_ids is not None
                 # The request is resumed from preemption.
                 # Replace the existing block IDs with the new ones.
                 req_state.block_ids = new_block_ids
@@ -594,7 +596,9 @@ class GPUModelRunner(LoRAModelRunnerMixin, KVConnectorModelRunnerMixin):
             # Update the persistent batch.
             self.input_batch.num_computed_tokens_cpu[req_index] = (
                 num_computed_tokens)
-            self.input_batch.block_table.append_row(new_block_ids, req_index)
+            if new_block_ids is not None:
+                self.input_batch.block_table.append_row(
+                    new_block_ids, req_index)
 
             # For the last rank, we don't need to update the token_ids_cpu
             # because the sampled tokens are already cached.

vllm/v1/worker/tpu_model_runner.py

@@ -418,11 +418,13 @@ class TPUModelRunner(LoRAModelRunnerMixin, KVConnectorModelRunnerMixin):
             # Update the cached states.
             req_state.num_computed_tokens = num_computed_tokens
             if not resumed_from_preemption:
-                # Append the new blocks to the existing block IDs.
-                for block_ids, new_ids in zip(req_state.block_ids,
-                                              new_block_ids):
-                    block_ids.extend(new_ids)
+                if new_block_ids is not None:
+                    # Append the new blocks to the existing block IDs.
+                    for block_ids, new_ids in zip(req_state.block_ids,
+                                                  new_block_ids):
+                        block_ids.extend(new_ids)
             else:
+                assert new_block_ids is not None
                 # The request is resumed from preemption.
                 # Replace the existing block IDs with the new ones.
                 req_state.block_ids = new_block_ids
@@ -438,7 +440,9 @@ class TPUModelRunner(LoRAModelRunnerMixin, KVConnectorModelRunnerMixin):
             # Update the persistent batch.
             self.input_batch.num_computed_tokens_cpu[req_index] = (
                 num_computed_tokens)
-            self.input_batch.block_table.append_row(new_block_ids, req_index)
+            if new_block_ids is not None:
+                self.input_batch.block_table.append_row(
+                    new_block_ids, req_index)
 
         # Add the new or resumed requests to the persistent batch.
         # The smaller empty indices are filled first.