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xiezhongtao
2026-01-19 10:38:50 +08:00
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vllm/v1/core/kv_cache_manager.py Normal file
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# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import itertools
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Literal, overload
from vllm.distributed.kv_events import KVCacheEvent
from vllm.logger import init_logger
from vllm.v1.core.kv_cache_coordinator import get_kv_cache_coordinator
from vllm.v1.core.kv_cache_metrics import KVCacheMetricsCollector
from vllm.v1.core.kv_cache_utils import KVCacheBlock
from vllm.v1.kv_cache_interface import KVCacheConfig
from vllm.v1.metrics.stats import PrefixCacheStats
from vllm.v1.request import Request
logger = init_logger(__name__)
@dataclass
class KVCacheBlocks:
"""
The allocation result of KVCacheManager, work as the interface between
Scheduler and KVCacheManager, to hide KVCacheManager's internal data
structure from the Scheduler.
"""
blocks: tuple[Sequence[KVCacheBlock], ...]
"""
`blocks[i][j]` refers to the i-th kv_cache_group
and the j-th block of tokens.We don't use block of
tokens as the outer dimension because it assumes all
kv_cache_groups have the same number of blocks, which is true for now but
will be broken if we want to give different block_size to different
kv_cache_groups in the future.
Each single type KVCacheBlocks could be represented as:
- list[KVCacheBlock] for more than one KVCacheBlock
- an empty tuple for requests without KVCacheBlock
(a precomputed KVCacheBlocks is in KVCacheManager to avoid GC overhead)
"""
def __add__(self, other: "KVCacheBlocks") -> "KVCacheBlocks":
"""Adds two KVCacheBlocks instances."""
return KVCacheBlocks(
tuple(
list(itertools.chain(blk1, blk2))
for blk1, blk2 in zip(self.blocks, other.blocks)
)
)
@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,
) -> tuple[list[int], ...] | None: ...
def get_block_ids(
self,
allow_none: bool = False,
) -> tuple[list[int], ...] | None:
"""
Converts the KVCacheBlocks instance to block_ids.
Returns:
tuple[list[int], ...]: A tuple of lists where:
- 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]:
"""Get block_ids of unhashed blocks from KVCacheBlocks instance."""
assert len(self.blocks) == 1, "Only one group is supported"
return [block.block_id for block in self.blocks[0] if block.block_hash is None]
def new_empty(self) -> "KVCacheBlocks":
"""
Creates a new KVCacheBlocks instance with no blocks.
"""
return KVCacheBlocks(tuple(() for _ in range(len(self.blocks))))
class KVCacheManager:
def __init__(
self,
kv_cache_config: KVCacheConfig,
max_model_len: int,
hash_block_size: int,
enable_caching: bool = True,
use_eagle: bool = False,
log_stats: bool = False,
enable_kv_cache_events: bool = False,
dcp_world_size: int = 1,
pcp_world_size: int = 1,
metrics_collector: KVCacheMetricsCollector | None = None,
) -> None:
self.max_model_len = max_model_len
self.enable_caching = enable_caching
self.use_eagle = use_eagle
self.log_stats = log_stats
self.metrics_collector = metrics_collector
# FIXME: make prefix cache stats conditional on log_stats. We still need
# this comment because when the log stats is enabled there are still
# potential configs we could expose in the future.
self.prefix_cache_stats = PrefixCacheStats() if log_stats else None
self.coordinator = get_kv_cache_coordinator(
kv_cache_config=kv_cache_config,
max_model_len=self.max_model_len,
use_eagle=self.use_eagle,
enable_caching=self.enable_caching,
enable_kv_cache_events=enable_kv_cache_events,
dcp_world_size=dcp_world_size,
pcp_world_size=pcp_world_size,
hash_block_size=hash_block_size,
metrics_collector=self.metrics_collector,
)
self.num_kv_cache_groups = len(kv_cache_config.kv_cache_groups)
self.block_pool = self.coordinator.block_pool
self.kv_cache_config = kv_cache_config
# Pre-constructed KVCacheBlocks with no blocks, callers should use this
# via create_kv_cache_blocks instead of creating new ones to avoid GC
# overhead.
#
# We use nested tuples to ensure the empty KVCacheBlocks is immutable.
self.empty_kv_cache_blocks = KVCacheBlocks(
tuple(() for _ in range(self.num_kv_cache_groups))
)
@property
def usage(self) -> float:
"""Get the KV cache usage.
Returns:
The KV cache usage (between 0.0 and 1.0).
"""
return self.block_pool.get_usage()
def make_prefix_cache_stats(self) -> PrefixCacheStats | None:
"""Get (and reset) the prefix cache stats.
Returns:
The current prefix caching stats, or None if logging is disabled.
"""
if not self.log_stats:
return None
stats = self.prefix_cache_stats
self.prefix_cache_stats = PrefixCacheStats()
return stats
def get_computed_blocks(self, request: Request) -> tuple[KVCacheBlocks, int]:
"""Get the computed (cached) blocks for the request.
Note that the computed blocks must be full.
Args:
request: The request to get the computed blocks.
Returns:
A tuple containing:
- A list of blocks that are computed for the request.
- The number of computed tokens.
"""
# We skip finding the prefix cache hit when prefix caching is
# disabled or the request is marked as skipping kv cache read
# (which happens when the request requires prompt logprobs
# or calls a pooling model with all pooling).
if not self.enable_caching or request.skip_reading_prefix_cache:
return self.empty_kv_cache_blocks, 0
# NOTE: When all tokens hit the cache, we must recompute the last token
# to obtain logits. Thus, set max_cache_hit_length to prompt_length - 1.
# This can trigger recomputation of an entire block, rather than just
# the single last token, because allocate_slots() requires
# num_computed_tokens to be block-size aligned. Removing this limitation
# could slightly improve performance in the future.
max_cache_hit_length = request.num_tokens - 1
computed_blocks, num_new_computed_tokens = (
self.coordinator.find_longest_cache_hit(
request.block_hashes, max_cache_hit_length
)
)
if self.log_stats:
assert self.prefix_cache_stats is not None
self.prefix_cache_stats.record(
num_tokens=request.num_tokens,
num_hits=num_new_computed_tokens,
preempted=request.num_preemptions > 0,
)
return self.create_kv_cache_blocks(computed_blocks), num_new_computed_tokens
def allocate_slots(
self,
request: Request,
num_new_tokens: int,
num_new_computed_tokens: int = 0,
new_computed_blocks: KVCacheBlocks | None = None,
num_lookahead_tokens: int = 0,
delay_cache_blocks: bool = False,
num_encoder_tokens: int = 0,
) -> KVCacheBlocks | None:
"""Add slots for a request with new tokens to append.
Args:
request: The request to allocate slots.
num_new_tokens: The number of tokens to allocate, including external
tokens. Note that this does not include tokens that have
already been computed locally (i.e. new_computed_blocks).
num_new_computed_tokens: The number of new computed tokens just
hitting the prefix caching, excluding external tokens.
new_computed_blocks: The cached blocks for the above new computed
tokens.
num_lookahead_tokens: The number of speculative tokens to allocate.
This is used by spec decode proposers with kv-cache such
as eagle.
delay_cache_blocks: Whether to skip caching the blocks. This is
used by P/D when allocating blocks used in a KV transfer
which will complete in a future step.
num_encoder_tokens: The number of encoder tokens to allocate for
cross-attention in encoder-decoder models(e.g., Whisper).
For decoder-only models, this should be 0.
Blocks layout:
```
-----------------------------------------------------------------------
| < computed > | < new computed > | < new > | < pre-allocated > |
-----------------------------------------------------------------------
| < required > |
--------------------------------------------------
| < full > |
------------------------------------------------
| <new full> |
--------------
```
The following *_blocks are illustrated in this layout.
Returns:
A list of new allocated blocks.
"""
if num_new_tokens == 0:
raise ValueError("num_new_tokens must be greater than 0")
if new_computed_blocks is not None:
new_computed_block_list = new_computed_blocks.blocks
else:
new_computed_block_list = self.empty_kv_cache_blocks.blocks
# Free the blocks that are skipped during the attention computation
# (e.g., tokens outside the sliding window).
# We can do this even if we cannot schedule this request due to
# insufficient free blocks.
# Should call this function before allocating new blocks to reduce
# the number of evicted blocks.
self.coordinator.remove_skipped_blocks(
request.request_id, request.num_computed_tokens
)
# The number of computed tokens is the number of computed tokens plus
# the new prefix caching hits
num_computed_tokens = request.num_computed_tokens + num_new_computed_tokens
num_tokens_need_slot = min(
num_computed_tokens + num_new_tokens + num_lookahead_tokens,
self.max_model_len,
)
num_blocks_to_allocate = self.coordinator.get_num_blocks_to_allocate(
request_id=request.request_id,
num_tokens=num_tokens_need_slot,
new_computed_blocks=new_computed_block_list,
num_encoder_tokens=num_encoder_tokens,
)
if num_blocks_to_allocate > self.block_pool.get_num_free_blocks():
# Cannot allocate new blocks
return None
# Touch the computed blocks to make sure they won't be evicted.
if self.enable_caching:
self.block_pool.touch(new_computed_block_list)
else:
assert not any(new_computed_block_list), (
"Computed blocks should be empty when prefix caching is disabled"
)
if new_computed_block_list is not self.empty_kv_cache_blocks.blocks:
# Append the new computed blocks to the request blocks until now to
# avoid the case where the new blocks cannot be allocated.
self.coordinator.save_new_computed_blocks(
request.request_id, new_computed_block_list
)
new_blocks = self.coordinator.allocate_new_blocks(
request.request_id, num_tokens_need_slot, num_encoder_tokens
)
# P/D: delay caching blocks if we have to recv from
# remote. Update state for locally cached blocks.
if not self.enable_caching or delay_cache_blocks:
return self.create_kv_cache_blocks(new_blocks)
# NOTE(woosuk): We want to commit (cache) up to num_computed_tokens +
# num_new_tokens, but must exclude "non-committable" tokens (e.g.,
# draft tokens that could be rejected). Therefore, we cap the number
# at `request.num_tokens`, ensuring only "finalized" tokens are cached.
num_tokens_to_cache = min(
num_computed_tokens + num_new_tokens, request.num_tokens
)
self.coordinator.cache_blocks(request, num_tokens_to_cache)
return self.create_kv_cache_blocks(new_blocks)
def free(self, request: Request) -> None:
"""Free the blocks allocated for the request.
We free the blocks in reverse order so that the tail blocks are evicted
first when caching is enabled.
Args:
request: The request to free the blocks.
"""
self.coordinator.free(request.request_id)
def evict_blocks(self, block_ids: set[int]) -> None:
"""evict blocks from the prefix cache by their block IDs.
Args:
block_ids: Set of block IDs to evict from cache.
"""
self.block_pool.evict_blocks(block_ids)
def reset_prefix_cache(self) -> bool:
"""Reset prefix cache. This function may be used in RLHF
flows to invalidate prefix caching after the weights are updated,
or used for resetting prefix caching status for benchmarking.
Returns:
bool: True if the prefix cache is successfully reset,
False otherwise.
"""
if not self.block_pool.reset_prefix_cache():
return False
if self.log_stats:
assert self.prefix_cache_stats is not None
self.prefix_cache_stats.reset = True
return True
def get_num_common_prefix_blocks(self, running_request_id: str) -> list[int]:
"""Calculate the number of common prefix blocks for each kv cache group.
The function selects a running request and iterates through its blocks.
A block is considered a common prefix block if ALL requests with
allocated KV cache share it (i.e., ref_cnt equals the number of entries
in req_to_blocks).
NOTE(woosuk): The number of requests with allocated KV cache is **greater
than or equal to** the number of requests scheduled in the current step.
This is because having allocated KV cache only indicates that:
1. The request has not yet finished, and
2. The request holds its blocks unfreed.
While all scheduled requests must have allocated KV cache, the inverse
is not necessarily true. There may be requests with allocated KV cache
that are not scheduled in the current step.
This can result in an edge case where the number of common prefix blocks
is 0, even though all scheduled requests share a common prefix. This
occurs because there may be unscheduled requests that do not share the
common prefix. Currently, this case cannot be easily detected, so the
function returns 0 in such cases.
Args:
running_request_id: The request ID of any running request, used to
identify the common prefix blocks.
Returns:
list[int]: The number of common prefix blocks for each kv cache
group.
"""
return self.coordinator.get_num_common_prefix_blocks(running_request_id)
def take_events(self) -> list[KVCacheEvent]:
"""Take the KV cache events from the block pool.
Returns:
A list of KV cache events.
"""
return self.block_pool.take_events()
def get_blocks(self, request_id: str) -> KVCacheBlocks:
"""Get the blocks of a request."""
return self.create_kv_cache_blocks(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 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."""
if self.enable_caching:
self.coordinator.cache_blocks(request, num_computed_tokens)
def create_kv_cache_blocks(
self, blocks: tuple[list[KVCacheBlock], ...]
) -> KVCacheBlocks:
# Only create new KVCacheBlocks for non-empty blocks
return KVCacheBlocks(blocks) if any(blocks) else self.empty_kv_cache_blocks