from __future__ import annotations from sglang.srt.mem_cache.cache_init_params import CacheInitParams from sglang.srt.mem_cache.utils import convert_to_bigram_key """ Copyright 2023-2024 SGLang Team Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. """ """ The radix tree data structure for managing the KV cache. """ import heapq import logging import sys import time from collections import defaultdict from functools import lru_cache, partial from typing import TYPE_CHECKING, Any, Iterator, List, Optional, Tuple, Union import torch logger = logging.getLogger(__name__) from sglang.srt.disaggregation.kv_events import ( MEDIUM_GPU, AllBlocksCleared, BlockRemoved, BlockStored, ) from sglang.srt.mem_cache.base_prefix_cache import ( BasePrefixCache, EvictParams, EvictResult, InsertParams, InsertResult, MatchPrefixParams, MatchResult, ) from sglang.srt.mem_cache.evict_policy import ( EvictionStrategy, FIFOStrategy, FILOStrategy, LFUStrategy, LRUStrategy, MRUStrategy, PriorityStrategy, ) from sglang.srt.mem_cache.hicache_storage import get_hash_str, hash_str_to_int64 if TYPE_CHECKING: from sglang.srt.managers.schedule_batch import Req class RadixKey: def __init__( self, token_ids: List[int], extra_key: Optional[str] = None, is_bigram: bool = False, ): # token ids sequence self.token_ids = token_ids # extra key (e.g. lora_id, cache_salt) self.extra_key = extra_key # is bigram key self.is_bigram = is_bigram def __len__(self) -> int: return len(self.token_ids) def __iter__(self) -> Iterator[int]: return iter(self.token_ids) def __getitem__(self, idx: Union[int, slice]) -> "RadixKey": if isinstance(idx, slice): return RadixKey(self.token_ids[idx], self.extra_key) return RadixKey([self.token_ids[idx]], self.extra_key) def __repr__(self) -> str: preview = self.token_ids[:10] return f"RadixKey(extra_key={self.extra_key!r}, token_ids={preview}{'...' if len(self.token_ids) > 10 else ''})" class TreeNode: counter = 0 def __init__(self, id: Optional[int] = None, priority: int = 0): self.children = defaultdict(TreeNode) self.parent: TreeNode = None self.key: RadixKey = None self.value: Optional[torch.Tensor] = None self.lock_ref = 0 self.last_access_time = time.monotonic() self.creation_time = time.monotonic() self.hit_count = 0 # indicating the node is locked to protect from eviction # incremented when the node is referenced by a storage operation self.host_ref_counter = 0 # store the host indices of KV cache self.host_value: Optional[torch.Tensor] = None # store hash values of each pages self.hash_value: Optional[List[str]] = None # priority for priority-aware eviction self.priority = priority self.id = TreeNode.counter if id is None else id TreeNode.counter += 1 @property def evicted(self): return self.value is None @property def backuped(self): return self.host_value is not None def protect_host(self): """Protect the host value from eviction.""" self.host_ref_counter += 1 def release_host(self): """Release the host value, allowing it to be evicted.""" if self.host_ref_counter > 0: self.host_ref_counter -= 1 else: raise RuntimeError("Host reference counter is already zero.") def get_last_hash_value(self) -> Optional[str]: """Returns the hash value of the last page in this node.""" if self.hash_value is None or len(self.hash_value) == 0: return None return self.hash_value[-1] @lru_cache(maxsize=1) def get_prefix_hash_values(self, node: TreeNode) -> List[str]: if node is None or node.hash_value is None: return [] return node.get_prefix_hash_values(node.parent) + node.hash_value def __lt__(self, other: "TreeNode"): return self.last_access_time < other.last_access_time def _check_extra_key(key0: RadixKey, key1: RadixKey): if key0.extra_key != key1.extra_key: raise ValueError( f"_key_match should be run on the same extra key, but got key0.extra_key={key0.extra_key} != key1.extra_key={key1.extra_key}" ) def _key_match_page_size1(key0: RadixKey, key1: RadixKey): _check_extra_key(key0, key1) i = 0 for k0, k1 in zip(key0.token_ids, key1.token_ids): if k0 != k1: break i += 1 return i def _key_match_paged(key0: RadixKey, key1: RadixKey, page_size: int): _check_extra_key(key0, key1) min_len = min(len(key0), len(key1)) i = 0 while i < min_len: if key0.token_ids[i : i + page_size] != key1.token_ids[i : i + page_size]: break i += page_size return i def get_child_key(key: RadixKey, page_size: int = 1): if page_size == 1: plain_key = key.token_ids[0] else: plain_key = tuple(key.token_ids[:page_size]) if key.extra_key is None: return plain_key else: return (key.extra_key, plain_key) def compute_node_hash_values(node: "TreeNode", page_size: int) -> List[str]: """Compute SHA256-based hash values for position-aware identification. Args: node: The TreeNode to compute hash values for page_size: The page size for chunking tokens Returns: List of SHA256 hex strings, one per page """ hash_values = [] # Get parent's last hash value if parent exists parent_hash = None if node.parent is not None and node.parent.hash_value is not None: # Check if parent is root by checking if it has empty key if len(node.parent.key) > 0 and len(node.parent.hash_value) > 0: parent_hash = node.parent.hash_value[-1] # Iterate through node's pages for start in range(0, len(node.key), page_size): page_tokens = node.key.token_ids[start : start + page_size] if not page_tokens: continue # Use SHA256-based chaining via get_hash_str hash_val = get_hash_str(page_tokens, prior_hash=parent_hash) hash_values.append(hash_val) parent_hash = hash_val return hash_values def split_node_hash_value( child_hash_value: Optional[List[str]], split_len: int, page_size: int ) -> tuple[Optional[List[str]], Optional[List[str]]]: """Split hash_value between parent and child nodes during node splitting. Args: child_hash_value: The hash_value list from the child node being split split_len: The length at which to split (in tokens) page_size: The page size for calculating number of pages Returns: Tuple of (new_node_hash_value, updated_child_hash_value) """ if child_hash_value is None: return None, None if page_size == 1: split_pages = split_len else: split_pages = split_len // page_size new_node_hash = child_hash_value[:split_pages] child_hash = child_hash_value[split_pages:] return new_node_hash, child_hash class RadixCache(BasePrefixCache): def __init__(self, params: CacheInitParams): self.disable = params.disable self.req_to_token_pool = params.req_to_token_pool self.token_to_kv_pool_allocator = params.token_to_kv_pool_allocator self.page_size = params.page_size self.enable_kv_cache_events = params.enable_kv_cache_events self.is_eagle = params.is_eagle self.disable_finished_insert = params.disable_finished_insert self.eviction_policy = params.eviction_policy.lower() self.kv_event_queue = [] if params.enable_metrics: self.init_metrics_collector() if self.token_to_kv_pool_allocator: self.device = self.token_to_kv_pool_allocator.device else: self.device = torch.device("cpu") if self.page_size == 1: self.key_match_fn = _key_match_page_size1 self.get_child_key_fn = get_child_key else: self.key_match_fn = partial(_key_match_paged, page_size=self.page_size) self.get_child_key_fn = partial(get_child_key, page_size=self.page_size) if self.eviction_policy == "lru": self.eviction_strategy: EvictionStrategy = LRUStrategy() elif self.eviction_policy == "lfu": self.eviction_strategy: EvictionStrategy = LFUStrategy() elif self.eviction_policy == "fifo": self.eviction_strategy: EvictionStrategy = FIFOStrategy() elif self.eviction_policy == "mru": self.eviction_strategy: EvictionStrategy = MRUStrategy() elif self.eviction_policy == "filo": self.eviction_strategy: EvictionStrategy = FILOStrategy() elif self.eviction_policy == "priority": self.eviction_strategy: EvictionStrategy = PriorityStrategy() else: raise ValueError( f"Unknown eviction policy: {self.eviction_policy}. Supported policies: 'lru', 'lfu', 'fifo', 'mru', 'filo', 'priority'." ) self.evictable_leaves = set() self.reset() @classmethod def create_simulated( self, disable: bool = False, mock_allocator: Optional[Any] = None, page_size: int = 1, enable_kv_cache_events: bool = False, ) -> RadixCache: """Init a radix cache without memory pools for simulation purpose.""" params = CacheInitParams( disable=disable, req_to_token_pool=None, token_to_kv_pool_allocator=mock_allocator, page_size=page_size, enable_kv_cache_events=enable_kv_cache_events, ) return RadixCache(params) ##### Public API ##### def reset(self): # Initialize root with minimum priority so any real priority overrides it self.root_node = TreeNode(priority=-sys.maxsize) self.root_node.key = RadixKey(token_ids=[], extra_key=None) self.root_node.value = [] self.root_node.host_value = [] self.root_node.lock_ref = 1 self.root_node.hash_value = [] self.evictable_size_ = 0 self.protected_size_ = 0 self.evictable_leaves.clear() self._record_all_cleared_event() def maybe_bigram_convert( self, key: RadixKey, value: Optional[torch.Tensor] = None ) -> Tuple[RadixKey, Optional[torch.Tensor]]: if self.is_eagle and not key.is_bigram: key.token_ids = convert_to_bigram_key(key.token_ids) if value is not None: value = value[: len(key)] return key, value def match_prefix(self, params: MatchPrefixParams) -> MatchResult: """Find the longest cached prefix of ``key`` in the radix tree. The logical namespace for prefix matching is determined by both the token id sequence and the optional ``extra_key`` carried by ``RadixKey``. Entries that share identical leading token ids but have *different* ``extra_key`` values are intentionally kept disjoint and never share prefix nodes. This is useful to: * Isolate KV cache lines for different LoRA / adapter IDs. * Separate requests that intentionally should not share state (e.g., different sampling salt, cache version, or retrieval augmentation context) by supplying a distinct ``extra_key``. Args: params (MatchPrefixParams): Parameters containing the lookup key with a list of token ids and an optional ``extra_key`` namespace tag. If ``page_size > 1`` the length is internally truncated to a multiple of ``page_size`` before matching. Passing an empty key returns an empty result with the root as the last node. Returns: MatchResult: ``device_indices`` is a 1-D ``torch.int64`` tensor of the concatenated KV cache indices corresponding to the longest cached prefix (may be length 0). ``last_device_node`` and ``last_host_node`` (currently the same) are the tree node objects representing the terminal node of the matched prefix. This method may mutate internal structure by splitting an existing node if the match ends inside a stored segment. Internal updates: * Refreshes access metadata (timestamps) used by the configured eviction strategy. * If the lookup ends inside a stored segment the node is split once to expose a precise boundary; this structural refinement improves subsequent match efficiency and does not duplicate data. """ key = params.key key, _ = self.maybe_bigram_convert(key) def empty_match_result(): return MatchResult( device_indices=torch.empty( (0,), dtype=torch.int64, device=self.device, ), last_device_node=self.root_node, last_host_node=self.root_node, ) if self.disable or len(key) == 0: return empty_match_result() if self.page_size != 1: page_aligned_len = len(key) // self.page_size * self.page_size key = key[:page_aligned_len] if len(key) == 0: return empty_match_result() value, last_node = self._match_prefix_helper(self.root_node, key) if value: value = torch.cat(value) else: value = torch.empty((0,), dtype=torch.int64, device=self.device) return MatchResult( device_indices=value, last_device_node=last_node, last_host_node=last_node, ) def insert(self, params: InsertParams) -> InsertResult: if self.disable: return InsertResult(prefix_len=0) key = params.key value = params.value priority = params.priority if value is None: value = torch.tensor(key.token_ids, dtype=torch.int64) key, value = self.maybe_bigram_convert(key, value) prefix_len = self._insert_helper(self.root_node, key, value, priority) return InsertResult(prefix_len=prefix_len) def _page_align_keys(self, key: list) -> list: if self.page_size == 1: return key page_aligned_len = len(key) // self.page_size * self.page_size return key[:page_aligned_len] def cache_finished_req(self, req: Req, is_insert: bool = True): """Cache request when it finishes.""" # In deterministic mode, disable finished request insertion to radix cache if self.disable_finished_insert: is_insert = False kv_committed_len = req.pop_committed_kv_cache() if self.disable: kv_indices = self.req_to_token_pool.req_to_token[ req.req_pool_idx, :kv_committed_len ] self.token_to_kv_pool_allocator.free(kv_indices) return token_ids = (req.origin_input_ids + req.output_ids)[:kv_committed_len] kv_indices = self.req_to_token_pool.req_to_token[ req.req_pool_idx, : len(token_ids) ] # Maybe convert to bigram keys for EAGLE keys = convert_to_bigram_key(token_ids) if self.is_eagle else token_ids keys = self._page_align_keys(keys) values = kv_indices[: len(keys)].to(dtype=torch.int64, copy=True) radix_key = RadixKey(keys, req.extra_key, is_bigram=self.is_eagle) # Radix Cache takes one ref in memory pool if is_insert: priority = getattr(req, "priority", 0) or 0 result = self.insert( InsertParams(key=radix_key, value=values, priority=priority) ) new_prefix_len = result.prefix_len # Free the duplicates that were already in the tree self.token_to_kv_pool_allocator.free( kv_indices[req.cache_protected_len : new_prefix_len] ) else: self.token_to_kv_pool_allocator.free( kv_indices[req.cache_protected_len : len(keys)] ) # free the unaligned tail self.token_to_kv_pool_allocator.free(kv_indices[len(keys) :]) # Remove req slot release the cache lock self.dec_lock_ref(req.last_node) def cache_unfinished_req(self, req: Req, chunked=False): """Cache request when it is unfinished.""" if self.disable: return token_ids = req.fill_ids kv_indices = self.req_to_token_pool.req_to_token[ req.req_pool_idx, : len(token_ids) ] # Maybe convert to bigram keys for EAGLE keys = convert_to_bigram_key(token_ids) if self.is_eagle else token_ids keys = self._page_align_keys(keys) values = kv_indices[: len(keys)].to(dtype=torch.int64, copy=True) radix_key = RadixKey(keys, req.extra_key, is_bigram=self.is_eagle) # Radix Cache takes one ref in memory pool result = self.insert( InsertParams( key=radix_key, value=values, chunked=chunked, priority=getattr(req, "priority", 0) or 0, ) ) new_prefix_len = result.prefix_len self.token_to_kv_pool_allocator.free( kv_indices[req.cache_protected_len : new_prefix_len] ) # The prefix indices could be updated, reuse it match_result = self.match_prefix(MatchPrefixParams(key=radix_key)) new_indices, new_last_node = ( match_result.device_indices, match_result.last_device_node, ) assert len(new_indices) == len(keys), f"{len(new_indices)=}, {len(keys)=}" self.req_to_token_pool.write( (req.req_pool_idx, slice(req.cache_protected_len, len(new_indices))), new_indices[req.cache_protected_len :], ) # The cache_protected_len is not always equal to len(req.prefix_indices) # since for page_size > 1, the partial part is added to req.prefix_indices, but that part of kv indices is not added to the tree. # It should be freed in the next cache_unfinished_req and final cache_finished_req to avoid memory leak. # So we introduce this `cache_protected_len` field to make sure the partial part can be freed correctly. req.cache_protected_len = len(new_indices) self.dec_lock_ref(req.last_node) self.inc_lock_ref(new_last_node) # `req.prefix_indices` will be used in `PrefillAdder::add_chunked_req` later # - page_size != 1: there is a partial page at the end, keep the full kv_indices # - eagle case: bigram keys will only cache len - 1 kv indices if len(new_indices) < len(kv_indices): req.prefix_indices = torch.cat( [new_indices, kv_indices[len(new_indices) :]] ) else: req.prefix_indices = new_indices req.last_node = new_last_node def pretty_print(self): self._print_helper(self.root_node, 0) print(f"#tokens: {self.total_size()}") def total_size(self): return self._total_size_helper() def evict(self, params: EvictParams) -> EvictResult: if self.disable: return EvictResult() start_time = time.perf_counter() num_tokens = params.num_tokens leaves = list(self.evictable_leaves) eviction_heap = [ (self.eviction_strategy.get_priority(node), node) for node in leaves ] heapq.heapify(eviction_heap) num_evicted = 0 while num_evicted < num_tokens and len(eviction_heap): _priority, x = heapq.heappop(eviction_heap) self.token_to_kv_pool_allocator.free(x.value) num_evicted += len(x.value) self._delete_leaf(x) if len(x.parent.children) == 0 and x.parent.lock_ref == 0: new_priority = self.eviction_strategy.get_priority(x.parent) heapq.heappush(eviction_heap, (new_priority, x.parent)) self._record_remove_event(x) self.update_eviction_metrics(num_evicted, start_time) return EvictResult(num_tokens_evicted=num_evicted) def inc_lock_ref(self, node: TreeNode): if self.disable: return 0 delta = 0 while node != self.root_node: if node.lock_ref == 0: self.evictable_size_ -= len(node.key) self.protected_size_ += len(node.key) delta -= len(node.key) node.lock_ref += 1 self._update_leaf_status(node) node = node.parent return delta def dec_lock_ref(self, node: TreeNode): if self.disable: return 0 delta = 0 while node != self.root_node: if node.lock_ref == 1: self.evictable_size_ += len(node.key) self.protected_size_ -= len(node.key) delta += len(node.key) node.lock_ref -= 1 self._update_leaf_status(node) if node.parent is None: assert ( node is self.root_node ), f"This request holds the node from another tree" node = node.parent return delta def evictable_size(self): return self.evictable_size_ def protected_size(self): # protected size refers to the size of the cache that is locked return self.protected_size_ def all_values_flatten(self): values = [] def _dfs_helper(node: TreeNode): for _, child in node.children.items(): values.append(child.value) _dfs_helper(child) _dfs_helper(self.root_node) return torch.cat(values) ##### Internal Helper Functions ##### def _match_prefix_helper(self, node: TreeNode, key: RadixKey): access_time = time.monotonic() node.last_access_time = access_time child_key = self.get_child_key_fn(key) value = [] while len(key) > 0 and child_key in node.children.keys(): child = node.children[child_key] child.last_access_time = access_time prefix_len = self.key_match_fn(child.key, key) if prefix_len < len(child.key): new_node = self._split_node(child.key, child, prefix_len) value.append(new_node.value) node = new_node break else: value.append(child.value) node = child key = key[prefix_len:] if len(key): child_key = self.get_child_key_fn(key) return value, node def _split_node(self, key: RadixKey, child: TreeNode, split_len: int): # new_node -> child # New node inherits child's priority (represents shared prefix) new_node = TreeNode(priority=child.priority) new_node.children = {self.get_child_key_fn(key[split_len:]): child} new_node.parent = child.parent new_node.lock_ref = child.lock_ref new_node.key = child.key[:split_len] new_node.value = child.value[:split_len].clone() child.parent = new_node child.key = child.key[split_len:] child.value = child.value[split_len:].clone() new_node.parent.children[self.get_child_key_fn(key)] = new_node # Split hash_value if it was already computed, otherwise leave as None new_node.hash_value, child.hash_value = split_node_hash_value( child.hash_value, split_len, self.page_size ) return new_node def _insert_helper(self, node: TreeNode, key: RadixKey, value, priority: int = 0): # Convert None priority to 0 if priority is None: priority = 0 access_time = time.monotonic() node.last_access_time = access_time # Update priority along the path (take max to propagate higher priority) node.priority = max(node.priority, priority) if len(key) == 0: return 0 child_key = self.get_child_key_fn(key) total_prefix_length = 0 while len(key) > 0 and child_key in node.children.keys(): node = node.children[child_key] node.last_access_time = access_time prefix_len = self.key_match_fn(node.key, key) total_prefix_length += prefix_len key = key[prefix_len:] value = value[prefix_len:] if prefix_len < len(node.key): new_node = self._split_node(node.key, node, prefix_len) new_node.priority = max(new_node.priority, priority) node = new_node else: node.priority = max(node.priority, priority) if len(key): child_key = self.get_child_key_fn(key) if len(key): new_node = TreeNode(priority=priority) new_node.parent = node new_node.key = key new_node.value = value.clone() node.children[child_key] = new_node self.evictable_size_ += len(key) self._update_leaf_status(node) self._update_leaf_status(new_node) # Hash will be computed lazily during event emission self._record_store_event(new_node) return total_prefix_length def _print_helper(self, node: TreeNode, indent: int): """Prints the radix tree in a human-readable format.""" stack = [(node, indent)] while stack: current_node, current_indent = stack.pop() print( " " * current_indent, len(current_node.key), current_node.key.token_ids[:10], f"r={current_node.lock_ref}", ) for key, child in current_node.children.items(): stack.append((child, current_indent + 2)) assert key == self.get_child_key_fn( child.key ), f"{key=}, {self.get_child_key_fn(child.key)=}" def _delete_leaf(self, node): key = self.get_child_key_fn(node.key) v = node.parent.children.pop(key, None) assert v == node, f"parent does not have child key, {key}" self.evictable_size_ -= len(node.key) if node in self.evictable_leaves: self.evictable_leaves.remove(node) self._update_leaf_status(node.parent) def _update_leaf_status(self, node: TreeNode): if node.evicted or node.lock_ref > 0: if node in self.evictable_leaves: self.evictable_leaves.remove(node) return for child in node.children.values(): if not child.evicted: if node in self.evictable_leaves: self.evictable_leaves.remove(node) return if node not in self.evictable_leaves: self.evictable_leaves.add(node) def _total_size_helper(self): total_size = 0 stack = [self.root_node] while stack: current_node = stack.pop() total_size += len(current_node.value) for child in current_node.children.values(): if child.evicted: continue stack.append(child) return total_size def _record_store_event(self, node: TreeNode): # One BlockStored per ``page_size`` chunk. if self.enable_kv_cache_events: # Compute hash_value lazily if not already set if node.hash_value is None: node.hash_value = compute_node_hash_values(node, self.page_size) # Get parent's last hash value for first page parent_block_hash = None if node.parent is not None and node.parent != self.root_node: if ( node.parent.hash_value is not None and len(node.parent.hash_value) > 0 ): parent_block_hash = hash_str_to_int64(node.parent.hash_value[-1]) page_index = 0 for start in range(0, len(node.key), self.page_size): page_tokens = node.key.token_ids[start : start + self.page_size] if not page_tokens: continue block_hash = hash_str_to_int64(node.hash_value[page_index]) self.kv_event_queue.append( BlockStored( block_hashes=[block_hash], parent_block_hash=parent_block_hash, token_ids=page_tokens, block_size=len(page_tokens), lora_id=None, medium=MEDIUM_GPU, ) ) parent_block_hash = block_hash page_index += 1 def _record_remove_event(self, node: TreeNode): # One BlockRemoved per chunk. if self.enable_kv_cache_events: # Compute hash_value lazily if not already set (must match what was stored) if node.hash_value is None: node.hash_value = compute_node_hash_values(node, self.page_size) page_index = 0 for start in range(0, len(node.key), self.page_size): page_tokens = node.key.token_ids[start : start + self.page_size] if not page_tokens: continue block_hash = hash_str_to_int64(node.hash_value[page_index]) self.kv_event_queue.append( BlockRemoved(block_hashes=[block_hash], medium=MEDIUM_GPU) ) page_index += 1 def _record_all_cleared_event(self): if self.enable_kv_cache_events: self.kv_event_queue.append(AllBlocksCleared()) def take_events(self): """Atomically takes all events and clears the queue. Returns: A list of KV cache events. """ if not self.enable_kv_cache_events: return [] events = self.kv_event_queue self.kv_event_queue = [] return events if __name__ == "__main__": tree = RadixCache.create_simulated() # Example token id sequences (as lists of ints) tree.insert(InsertParams(key=RadixKey(token_ids=[1, 2, 3], extra_key=None))) tree.insert(InsertParams(key=RadixKey(token_ids=[1, 2, 3], extra_key=None))) tree.insert(InsertParams(key=RadixKey(token_ids=[1, 2, 4, 5], extra_key=None))) tree.insert( InsertParams(key=RadixKey(token_ids=[1, 2, 4, 5, 6, 7], extra_key=None)) ) tree.insert( InsertParams(key=RadixKey(token_ids=[8, 9, 10, 11, 12], extra_key=None)) ) tree.pretty_print() print( tree.match_prefix( MatchPrefixParams(key=RadixKey(token_ids=[1, 2, 3, 13, 14], extra_key=None)) ) )