sglang0.4.5.post1/python/sglang/srt/mem_cache/hiradix_cache.py

443 lines
16 KiB
Python

import heapq
import logging
import threading
import time
from typing import List, Optional
import torch
from sglang.srt.managers.cache_controller import HiCacheController
from sglang.srt.mem_cache.memory_pool import (
MHATokenToKVPool,
MHATokenToKVPoolHost,
MLATokenToKVPool,
MLATokenToKVPoolHost,
ReqToTokenPool,
TokenToKVPoolAllocator,
)
from sglang.srt.mem_cache.radix_cache import RadixCache, TreeNode
from sglang.srt.mem_cache.radix_cache import _key_match_page_size1 as _key_match
logger = logging.getLogger(__name__)
class HiRadixCache(RadixCache):
def __init__(
self,
req_to_token_pool: ReqToTokenPool,
token_to_kv_pool_allocator: TokenToKVPoolAllocator,
tp_cache_group: torch.distributed.ProcessGroup,
page_size: int,
hicache_ratio: float,
):
if page_size != 1:
raise ValueError(
"Page size larger than 1 is not yet supported in HiRadixCache."
)
self.kv_cache = token_to_kv_pool_allocator.get_kvcache()
if isinstance(self.kv_cache, MHATokenToKVPool):
self.token_to_kv_pool_host = MHATokenToKVPoolHost(
self.kv_cache, hicache_ratio
)
elif isinstance(self.kv_cache, MLATokenToKVPool):
self.token_to_kv_pool_host = MLATokenToKVPoolHost(
self.kv_cache, hicache_ratio
)
else:
raise ValueError(f"Only MHA and MLA supports swap kv_cache to host.")
self.tp_group = tp_cache_group
self.page_size = page_size
self.load_cache_event = threading.Event()
self.cache_controller = HiCacheController(
token_to_kv_pool_allocator,
self.token_to_kv_pool_host,
load_cache_event=self.load_cache_event,
)
# record the nodes with ongoing write through
self.ongoing_write_through = {}
# record the node segments with ongoing load back
self.ongoing_load_back = {}
# todo: dynamically adjust the threshold
self.write_through_threshold = 1
self.load_back_threshold = 10
super().__init__(
req_to_token_pool, token_to_kv_pool_allocator, self.page_size, disable=False
)
def reset(self):
TreeNode.counter = 0
self.cache_controller.reset()
self.token_to_kv_pool_host.clear()
super().reset()
def get_height(self, node: TreeNode):
height = 0
while node != self.root_node:
node = node.parent
height += 1
return height
def write_backup(self, node: TreeNode):
host_indices = self.cache_controller.write(
device_indices=node.value,
node_id=node.id,
)
if host_indices is None:
self.evict_host(len(node.value))
host_indices = self.cache_controller.write(
device_indices=node.value,
node_id=node.id,
)
if host_indices is not None:
node.host_value = host_indices
self.ongoing_write_through[node.id] = node
self.inc_lock_ref(node)
else:
return None
return len(host_indices)
def inc_hit_count(self, node: TreeNode):
if self.cache_controller.write_policy != "write_through_selective":
return
node.hit_count += 1
if node.host_value is None and node.hit_count > self.write_through_threshold:
self.write_backup(node)
node.hit_count = 0
def writing_check(self):
queue_size = torch.tensor(
self.cache_controller.ack_write_queue.qsize(), dtype=torch.int
)
if torch.distributed.get_world_size(group=self.tp_group) > 1:
# synchrnoize TP workers to make the same update to radix cache
torch.distributed.all_reduce(
queue_size,
op=torch.distributed.ReduceOp.MIN,
group=self.tp_group,
)
for _ in range(queue_size.item()):
ack_id = self.cache_controller.ack_write_queue.get()
self.dec_lock_ref(self.ongoing_write_through[ack_id])
del self.ongoing_write_through[ack_id]
def loading_check(self):
while not self.cache_controller.ack_load_queue.empty():
try:
ack_id = self.cache_controller.ack_load_queue.get_nowait()
start_node, end_node = self.ongoing_load_back[ack_id]
self.dec_lock_ref(end_node)
while end_node != start_node:
assert end_node.loading
end_node.loading = False
end_node = end_node.parent
# clear the reference
del self.ongoing_load_back[ack_id]
except Exception:
break
def evictable_size(self):
return self.evictable_size_
def evict(self, num_tokens: int):
leaves = self._collect_leaves_device()
heapq.heapify(leaves)
num_evicted = 0
pending_nodes = []
while num_evicted < num_tokens and len(leaves):
x = heapq.heappop(leaves)
if x.lock_ref > 0:
continue
if x.host_value is None:
if self.cache_controller.write_policy == "write_back":
num_evicted += self.write_backup(x)
elif self.cache_controller.write_policy == "write_through_selective":
num_evicted += self._evict_write_through_selective(x)
else:
assert (
self.cache_controller.write_policy != "write_through"
), "write_through should be inclusive"
raise NotImplementedError
else:
num_evicted += self._evict_write_through(x)
for child in x.parent.children.values():
if child in pending_nodes:
continue
if not child.evicted:
break
else:
# all children are evicted or no children
heapq.heappush(leaves, x.parent)
if self.cache_controller.write_policy == "write_back":
# blocking till all write back complete
while len(self.ongoing_write_through) > 0:
self.writing_check()
time.sleep(0.1)
def _evict_write_through(self, node: TreeNode):
# evict a node already written to host
num_evicted = self.cache_controller.evict_device(node.value, node.host_value)
assert num_evicted > 0
self.evictable_size_ -= num_evicted
node.value = None
return num_evicted
def _evict_write_through_selective(self, node: TreeNode):
# evict a node not initiated write to host
self.cache_controller.mem_pool_device_allocator.free(node.value)
num_evicted = len(node.value)
self._delete_leaf(node)
return num_evicted
def evict_host(self, num_tokens: int):
leaves = self._collect_leaves()
heapq.heapify(leaves)
num_evicted = 0
while num_evicted < num_tokens and len(leaves):
x = heapq.heappop(leaves)
if x == self.root_node:
break
# only evict the host value of evicted nodes
if not x.evicted:
continue
assert x.lock_ref == 0 and x.host_value is not None
assert self.cache_controller.evict_host(x.host_value) > 0
for k, v in x.parent.children.items():
if v == x:
break
del x.parent.children[k]
if len(x.parent.children) == 0 and x.parent.evicted:
heapq.heappush(leaves, x.parent)
def load_back(
self, node: TreeNode, mem_quota: Optional[int] = None
) -> Optional[torch.Tensor]:
# todo: more loading policies
last_hit_node = node
nodes_to_load = []
while node.evicted:
assert (
node.backuped
), "No backup available on evicted nodes, should not happen"
nodes_to_load.insert(0, node)
node = node.parent
else:
ancester_node = node
# protect the ancestor nodes from eviction
delta = self.inc_lock_ref(ancester_node)
# load it all or not at all
host_indices = torch.cat([n.host_value for n in nodes_to_load])
if len(host_indices) < self.load_back_threshold or (
len(host_indices) > mem_quota + delta if mem_quota is not None else False
):
# skip loading back if the total size is too small or exceeding the memory quota
self.dec_lock_ref(ancester_node)
return None
device_indices = self.cache_controller.load(
host_indices=host_indices, node_id=last_hit_node.id
)
if device_indices is None:
self.evict(len(host_indices))
device_indices = self.cache_controller.load(
host_indices=host_indices, node_id=last_hit_node.id
)
self.dec_lock_ref(ancester_node)
if device_indices is None:
# no sufficient GPU memory to load back KV caches
return None
self.ongoing_load_back[last_hit_node.id] = (ancester_node, last_hit_node)
offset = 0
for node in nodes_to_load:
node.value = device_indices[offset : offset + len(node.host_value)]
offset += len(node.host_value)
node.loading = True
self.evictable_size_ += len(device_indices)
self.inc_lock_ref(last_hit_node)
return device_indices
def init_load_back(
self,
last_node: TreeNode,
prefix_indices: torch.Tensor,
mem_quota: Optional[int] = None,
):
assert (
len(prefix_indices) == 0 or prefix_indices.is_cuda
), "indices of device kV caches should be on GPU"
if last_node.evicted:
loading_values = self.load_back(last_node, mem_quota)
if loading_values is not None:
prefix_indices = (
loading_values
if len(prefix_indices) == 0
else torch.cat([prefix_indices, loading_values])
)
logger.debug(
f"loading back {len(loading_values)} tokens for node {last_node.id}"
)
while last_node.evicted:
last_node = last_node.parent
return last_node, prefix_indices
def read_to_load_cache(self):
self.load_cache_event.set()
def match_prefix(self, key: List[int], include_evicted=False, **kwargs):
if self.disable:
return [], self.root_node
value, last_node = self._match_prefix_helper(self.root_node, key)
if value:
value = torch.cat(value)
else:
value = torch.tensor([], dtype=torch.int64)
last_node_global = last_node
while last_node.evicted:
last_node = last_node.parent
if include_evicted:
return value, last_node, last_node_global
else:
return value, last_node
def _match_prefix_helper(self, node: TreeNode, key: List):
node.last_access_time = time.time()
value = []
while len(key) > 0 and key[0] in node.children.keys():
child = node.children[key[0]]
child.last_access_time = time.time()
prefix_len = _key_match(child.key, key)
if prefix_len < len(child.key):
new_node = self._split_node(child.key, child, prefix_len)
if not new_node.evicted:
value.append(new_node.value)
node = new_node
break
else:
if not child.evicted:
value.append(child.value)
node = child
key = key[prefix_len:]
return value, node
def _split_node(self, key, child: TreeNode, split_len: int):
# child node split into new_node -> child
new_node = TreeNode()
new_node.children = {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.loading = child.loading
# split value and host value if exists
if child.evicted:
new_node.value = None
else:
new_node.value = child.value[:split_len]
child.value = child.value[split_len:]
if child.host_value is not None:
new_node.host_value = child.host_value[:split_len]
child.host_value = child.host_value[split_len:]
child.parent = new_node
child.key = child.key[split_len:]
new_node.parent.children[key[0]] = new_node
return new_node
def _insert_helper(self, node: TreeNode, key: List, value):
node.last_access_time = time.time()
if len(key) == 0:
return 0
if key[0] in node.children.keys():
child = node.children[key[0]]
prefix_len = _key_match(child.key, key)
if prefix_len == len(child.key):
if child.evicted:
# change the reference if the node is evicted
# this often happens in the case of KV cache recomputation
child.value = value[:prefix_len]
self.token_to_kv_pool_host.update_synced(child.host_value)
self.evictable_size_ += len(value[:prefix_len])
return self._insert_helper(
child, key[prefix_len:], value[prefix_len:]
)
else:
self.inc_hit_count(child)
return prefix_len + self._insert_helper(
child, key[prefix_len:], value[prefix_len:]
)
# partial match, split the node
new_node = self._split_node(child.key, child, prefix_len)
if new_node.evicted:
new_node.value = value[:prefix_len]
self.token_to_kv_pool_host.update_synced(new_node.host_value)
self.evictable_size_ += len(new_node.value)
return self._insert_helper(
new_node, key[prefix_len:], value[prefix_len:]
)
else:
self.inc_hit_count(new_node)
return prefix_len + self._insert_helper(
new_node, key[prefix_len:], value[prefix_len:]
)
if len(key):
new_node = TreeNode()
new_node.parent = node
new_node.key = key
new_node.value = value
node.children[key[0]] = new_node
self.evictable_size_ += len(value)
if self.cache_controller.write_policy == "write_through":
self.write_backup(new_node)
return 0
def _collect_leaves_device(self):
def is_leaf(node):
if node.evicted:
return False
if node == self.root_node:
return False
if len(node.children) == 0:
return True
for child in node.children.values():
if not child.evicted:
return False
return True
ret_list = []
stack = [self.root_node]
while stack:
cur_node = stack.pop()
if is_leaf(cur_node):
ret_list.append(cur_node)
else:
for cur_child in cur_node.children.values():
if not cur_child.evicted:
stack.append(cur_child)
return ret_list