fix: cap SWA/chunked-local runtime admission to startup pool-sizing bound

aphrodite/v1/core/kv_cache_coordinator.py

@@ -34,6 +34,7 @@ def __init__(
         self,
         kv_cache_config: KVCacheConfig,
         max_model_len: int,
+        max_num_batched_tokens: int,
         use_eagle: bool,
         enable_caching: bool,
         enable_kv_cache_events: bool,
@@ -62,6 +63,8 @@ def __init__(
         self.single_type_managers = tuple(
             get_manager_for_kv_cache_spec(
                 kv_cache_spec=kv_cache_group.kv_cache_spec,
+                max_num_batched_tokens=max_num_batched_tokens,
+                max_model_len=max_model_len,
                 block_pool=self.block_pool,
                 enable_caching=enable_caching,
                 kv_cache_group_id=i,
@@ -258,6 +261,7 @@ def __init__(
         self,
         kv_cache_config: KVCacheConfig,
         max_model_len: int,
+        max_num_batched_tokens: int,
         use_eagle: bool,
         enable_kv_cache_events: bool,
         dcp_world_size: int,
@@ -268,6 +272,7 @@ def __init__(
         super().__init__(
             kv_cache_config,
             max_model_len,
+            max_num_batched_tokens,
             use_eagle,
             False,
             enable_kv_cache_events,
@@ -301,6 +306,7 @@ def __init__(
         self,
         kv_cache_config: KVCacheConfig,
         max_model_len: int,
+        max_num_batched_tokens: int,
         use_eagle: bool,
         enable_caching: bool,
         enable_kv_cache_events: bool,
@@ -312,6 +318,7 @@ def __init__(
         super().__init__(
             kv_cache_config,
             max_model_len,
+            max_num_batched_tokens,
             use_eagle,
             enable_caching,
             enable_kv_cache_events,
@@ -366,6 +373,7 @@ def __init__(
         self,
         kv_cache_config: KVCacheConfig,
         max_model_len: int,
+        max_num_batched_tokens: int,
         use_eagle: bool,
         enable_caching: bool,
         enable_kv_cache_events: bool,
@@ -377,6 +385,7 @@ def __init__(
         super().__init__(
             kv_cache_config,
             max_model_len,
+            max_num_batched_tokens,
             use_eagle,
             enable_caching,
             enable_kv_cache_events,
@@ -542,6 +551,7 @@ def _get_block_hashes(kv_cache_spec: KVCacheSpec) -> BlockHashList:
 def get_kv_cache_coordinator(
     kv_cache_config: KVCacheConfig,
     max_model_len: int,
+    max_num_batched_tokens: int,
     use_eagle: bool,
     enable_caching: bool,
     enable_kv_cache_events: bool,
@@ -554,6 +564,7 @@ def get_kv_cache_coordinator(
         return KVCacheCoordinatorNoPrefixCache(
             kv_cache_config,
             max_model_len,
+            max_num_batched_tokens,
             use_eagle,
             enable_kv_cache_events,
             dcp_world_size=dcp_world_size,
@@ -565,6 +576,7 @@ def get_kv_cache_coordinator(
         return UnitaryKVCacheCoordinator(
             kv_cache_config,
             max_model_len,
+            max_num_batched_tokens,
             use_eagle,
             enable_caching,
             enable_kv_cache_events,
@@ -576,6 +588,7 @@ def get_kv_cache_coordinator(
     return HybridKVCacheCoordinator(
         kv_cache_config,
         max_model_len,
+        max_num_batched_tokens,
         use_eagle,
         enable_caching,
         enable_kv_cache_events,

aphrodite/v1/core/kv_cache_manager.py

@@ -100,6 +100,7 @@ def __init__(
         kv_cache_config: KVCacheConfig,
         max_model_len: int,
         hash_block_size: int,
+        max_num_batched_tokens: int | None = None,
         enable_caching: bool = True,
         use_eagle: bool = False,
         log_stats: bool = False,
@@ -109,6 +110,11 @@ def __init__(
         metrics_collector: KVCacheMetricsCollector | None = None,
     ) -> None:
         self.max_model_len = max_model_len
+        # When unset, fall back to `max_model_len` so the recycling-aware cap
+        # collapses to the prior (uncapped) admission behavior. The scheduler
+        # always supplies the real value at runtime.
+        if max_num_batched_tokens is None:
+            max_num_batched_tokens = max_model_len
 
         self.enable_caching = enable_caching
         self.use_eagle = use_eagle
@@ -122,6 +128,7 @@ def __init__(
         self.coordinator = get_kv_cache_coordinator(
             kv_cache_config=kv_cache_config,
             max_model_len=self.max_model_len,
+            max_num_batched_tokens=max_num_batched_tokens,
             use_eagle=self.use_eagle,
             enable_caching=self.enable_caching,
             enable_kv_cache_events=enable_kv_cache_events,

aphrodite/v1/core/sched/scheduler.py

@@ -210,6 +210,7 @@ def __init__(
         self.kv_cache_manager = KVCacheManager(
             kv_cache_config=kv_cache_config,
             max_model_len=self.max_model_len,
+            max_num_batched_tokens=self.scheduler_config.max_num_batched_tokens,
             enable_caching=self.cache_config.enable_prefix_caching,
             use_eagle=self.use_eagle,
             log_stats=self.log_stats,

aphrodite/v1/core/single_type_kv_cache_manager.py

@@ -41,13 +41,20 @@ def __init__(
         kv_cache_group_id: int,
         dcp_world_size: int = 1,
         pcp_world_size: int = 1,
+        max_admission_blocks_per_request: int | None = None,
     ) -> None:
         """
         Initializes the SingleTypeKVCacheManager.
         Args:
             kv_cache_spec: The kv_cache_spec for this manager.
             block_pool: The block pool.
             kv_cache_group_id: The id of the kv cache group of this manager.
+            max_admission_blocks_per_request: Recycling-aware per-request
+                block cap used by `get_num_blocks_to_allocate`. Only set for
+                spec types that recycle blocks across chunks (SWA,
+                chunked-local); `None` (the default) means no cap, which is
+                correct for full-attention-style specs that hold every
+                block until the request finishes.
         """
         self.block_size = kv_cache_spec.block_size
         self.dcp_world_size = dcp_world_size
@@ -57,6 +64,7 @@ def __init__(
         self.kv_cache_spec = kv_cache_spec
         self.block_pool = block_pool
         self.enable_caching = enable_caching
+        self._max_admission_blocks_per_request = max_admission_blocks_per_request
         self.new_block_ids: list[int] = []
 
         # Mapping from request ID to blocks to track the blocks allocated
@@ -105,6 +113,17 @@ def get_num_blocks_to_allocate(
         """
 
         num_required_blocks = cdiv(num_tokens, self.block_size)
+        if self._max_admission_blocks_per_request is not None:
+            # Recycling-aware specs (SWA, chunked-local) cap the per-request
+            # reservation here so admission matches the startup pool sizer
+            # (`SlidingWindowSpec.max_admission_blocks_per_request` / its
+            # chunked-local counterpart). `remove_skipped_blocks` runs from
+            # `allocate_slots` before each chunk's `get_num_blocks_to_allocate`,
+            # so per-request peak real-held blocks <= this cap, which keeps
+            # `sum(reservations) <= pool` <=> `sum(peak_real_held) <= pool`.
+            # Drift between the two would re-introduce the deadlock from
+            # issue #39734 or, worse, mid-prefill OOM.
+            num_required_blocks = min(num_required_blocks, self._max_admission_blocks_per_request)
         num_req_blocks = len(self.req_to_blocks.get(request_id, ()))
 
         if request_id in self.num_cached_block:
@@ -1043,7 +1062,20 @@ def __init__(
 }
 
 
-def get_manager_for_kv_cache_spec(kv_cache_spec: KVCacheSpec, **kwargs) -> SingleTypeKVCacheManager:
+def get_manager_for_kv_cache_spec(
+    kv_cache_spec: KVCacheSpec,
+    max_num_batched_tokens: int,
+    max_model_len: int,
+    **kwargs,
+) -> SingleTypeKVCacheManager:
     manager_class = spec_manager_map[type(kv_cache_spec)]
+    # SlidingWindow / ChunkedLocalAttention managers recycle blocks across
+    # chunks; the runtime admission cap must match the recycling-aware bound
+    # the startup pool sizer uses (single source of truth: the spec method).
+    if isinstance(kv_cache_spec, (SlidingWindowSpec, ChunkedLocalAttentionSpec)):
+        kwargs["max_admission_blocks_per_request"] = kv_cache_spec.max_admission_blocks_per_request(
+            max_num_batched_tokens=max_num_batched_tokens,
+            max_model_len=max_model_len,
+        )
     manager = manager_class(kv_cache_spec, **kwargs)
     return manager

aphrodite/v1/kv_cache_interface.py

@@ -332,17 +332,24 @@ def merge(cls, specs: list[Self]) -> Self:
 class ChunkedLocalAttentionSpec(AttentionSpec):
     attention_chunk_size: int
 
-    def max_memory_usage_bytes(self, aphrodite_config: AphroditeConfig) -> int:
-        max_model_len = aphrodite_config.model_config.max_model_len
-        max_num_batched_tokens = aphrodite_config.scheduler_config.max_num_batched_tokens
+    def max_admission_blocks_per_request(self, max_num_batched_tokens: int, max_model_len: int) -> int:
+        """Per-request admission cap, in blocks.
 
-        # During chunked prefill, we allocate KV cache for at most
-        # `self.attention_chunk_size` computed tokens plus the newly scheduled
-        # tokens. And we won't allocate KV cache for more than `max_model_len`
-        # tokens.
+        Single source of truth for both startup pool sizing
+        (`max_memory_usage_bytes`) and the runtime admission gate, so requests
+        admitted by startup can also be admitted at runtime.
+        """
+        # During chunked prefill, we hold KV for at most one chunk window.
         num_tokens = min(self.attention_chunk_size + max_num_batched_tokens, max_model_len)
+        return cdiv(num_tokens, self.block_size)
 
-        return cdiv(num_tokens, self.block_size) * self.page_size_bytes
+    def max_memory_usage_bytes(self, aphrodite_config: AphroditeConfig) -> int:
+        max_model_len = aphrodite_config.model_config.max_model_len
+        max_num_batched_tokens = aphrodite_config.scheduler_config.max_num_batched_tokens
+        max_blocks = self.max_admission_blocks_per_request(
+            max_num_batched_tokens=max_num_batched_tokens, max_model_len=max_model_len
+        )
+        return max_blocks * self.page_size_bytes
 
 
 @dataclass(frozen=True, kw_only=True)
@@ -358,22 +365,34 @@ def __post_init__(self):
     def real_page_size_bytes(self) -> int:
         return self.block_size * self.num_kv_heads * (self.head_size + self.head_size_v) * get_dtype_size(self.dtype)
 
+    def max_admission_blocks_per_request(self, max_num_batched_tokens: int, max_model_len: int) -> int:
+        """Per-request admission cap, in blocks.
+
+        Single source of truth for both startup pool sizing
+        (`max_memory_usage_bytes`) and the runtime admission gate. Per-request
+        real-held blocks plateau at this bound because
+        `SlidingWindowManager.remove_skipped_blocks` runs from `allocate_slots`
+        before each chunk's `get_num_blocks_to_allocate`.
+        """
+        # During chunked prefill, we hold KV for the last `sliding_window-1`
+        # computed tokens plus the newly scheduled tokens, and never more
+        # than `max_model_len`.
+        num_tokens = min(self.sliding_window - 1 + max_num_batched_tokens, max_model_len)
+        # +1 because the sliding window may not start from the beginning of
+        # the block. E.g. block size 4 and num_token 4 needs two blocks
+        # [XXCD][EF] to store the 6-token window [CDEF].
+        return cdiv(num_tokens, self.block_size) + 1
+
     def max_memory_usage_bytes(self, aphrodite_config: AphroditeConfig) -> int:
         assert aphrodite_config.parallel_config.decode_context_parallel_size == 1, "DCP not support sliding window."
         max_model_len = aphrodite_config.model_config.max_model_len
         max_num_batched_tokens = aphrodite_config.scheduler_config.max_num_batched_tokens
 
-        # During chunked prefill, we allocate KV cache for the last
-        # `self.sliding_window-1` computed tokens plus the newly scheduled
-        # tokens. And we won't allocate KV cache for more than `max_model_len`
-        # tokens.
-        num_tokens = min(self.sliding_window - 1 + max_num_batched_tokens, max_model_len)
+        max_blocks = self.max_admission_blocks_per_request(
+            max_num_batched_tokens=max_num_batched_tokens, max_model_len=max_model_len
+        )
 
-        # +1 here because the sliding window may not start from the beginning
-        # of the block. For example, if the block size is 4 and num_token
-        # is 4, we need two blocks [XXCD] [EF] to store the sliding
-        # window [CDEF] of 6 tokens.
-        return (cdiv(num_tokens, self.block_size) + 1) * self.page_size_bytes
+        return max_blocks * self.page_size_bytes
 
 
 @dataclass(frozen=True, kw_only=True)

aphrodite/v1/simple_kv_offload/manager.py

@@ -107,6 +107,7 @@ def __init__(
         self.cpu_coordinator: KVCacheCoordinator = get_kv_cache_coordinator(
             kv_cache_config=self.cpu_kv_cache_config,
             max_model_len=aphrodite_config.model_config.max_model_len,
+            max_num_batched_tokens=aphrodite_config.scheduler_config.max_num_batched_tokens,
             use_eagle=False,
             enable_caching=True,
             enable_kv_cache_events=self.enable_kv_cache_events,