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sglang/python/sglang/srt/disaggregation/mooncake/conn.py
leavelet b34e7cb932 Add SGLANG_CP_TRANSFER_LOG: decouple CP shared-KV transfer-partition dumps from debug flag 
SGLANG_DEBUG_CP_SHARED_KV also disables tai IPC materialize -> NSA index fail-fast at
warmup (unusable in this config). Add a logging-only flag that emits the sender/worker
transfer-partition dumps (main-KV pages/positions vs NSA-state pages/positions) without
that side effect, and lift the 64-log cap, so we can diff the state-vs-main-KV partition
for a cache-hit vs cache-miss.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-17 16:29:31 +00:00

2086 lines
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from __future__ import annotations
import concurrent.futures
import ctypes
import dataclasses
import logging
import os
import struct
import threading
import time
from collections import defaultdict
from typing import List, Optional, Tuple
import numpy as np
import numpy.typing as npt
from sglang.srt.disaggregation.base.conn import KVArgs, KVPoll
from sglang.srt.disaggregation.common.conn import (
CommonKVBootstrapServer,
CommonKVManager,
CommonKVReceiver,
CommonKVSender,
)
from sglang.srt.disaggregation.common.utils import (
FastQueue,
contiguous_group_stats,
group_concurrent_contiguous,
)
from sglang.srt.disaggregation.mooncake.utils import (
check_mooncake_custom_mem_pool_enabled,
)
from sglang.srt.disaggregation.utils import (
DisaggregationMode,
filter_kv_indices_for_cp_rank,
validate_transfer_page_count_or_raise,
)
from sglang.srt.distributed.parallel_state import get_mooncake_transfer_engine
from sglang.srt.environ import envs
from sglang.srt.server_args import ServerArgs
from sglang.srt.utils.network import NetworkAddress
logger = logging.getLogger(__name__)
_CP_SHARED_DEBUG_COUNTS: dict[str, int] = {}
def _cp_shared_debug_log(key: str, message: str, *args, limit: int = 1_000_000) -> None:
if not (envs.SGLANG_DEBUG_CP_SHARED_KV.get() or envs.SGLANG_CP_TRANSFER_LOG.get()):
return
count = _CP_SHARED_DEBUG_COUNTS.get(key, 0)
if count >= limit:
return
_CP_SHARED_DEBUG_COUNTS[key] = count + 1
logger.info("[CP_SHARED_KV_DEBUG] " + message, *args)
def _cp_draft_shared_kv_debug(message: str, *args, limit: int = 64) -> None:
if not envs.SGLANG_CP_DRAFT_SHARED_KV_DEBUG.get():
return
key = "draft:" + message.split(" ", 1)[0]
count = _CP_SHARED_DEBUG_COUNTS.get(key, 0)
if count >= limit:
return
_CP_SHARED_DEBUG_COUNTS[key] = count + 1
logger.info("[CP_DRAFT_SHARED_KV] " + message, *args)
def _mooncake_transfer_stats_enabled() -> bool:
return envs.SGLANG_DISAGGREGATION_TRANSFER_STATS.get()
def _mooncake_transfer_stats_log(message: str, *args) -> None:
if not _mooncake_transfer_stats_enabled():
return
limit = envs.SGLANG_DISAGGREGATION_TRANSFER_STATS_LIMIT.get()
if limit is not None and limit <= 0:
return
key = "mooncake_transfer_stats"
count = _CP_SHARED_DEBUG_COUNTS.get(key, 0)
if limit is not None and count >= limit:
return
_CP_SHARED_DEBUG_COUNTS[key] = count + 1
logger.info("[Mooncake-transfer-stats] " + message, *args)
def _np_summary(arr) -> str:
if arr is None:
return "None"
arr = np.asarray(arr)
if arr.size == 0:
return f"shape={arr.shape} dtype={arr.dtype} size=0"
head = arr.reshape(-1)[: min(8, arr.size)].tolist()
return (
f"shape={arr.shape} dtype={arr.dtype} size={arr.size} "
f"min={int(arr.min())} max={int(arr.max())} head={head}"
)
class KVTransferError(Exception):
def __init__(self, bootstrap_room: int, failure_reason: str):
super().__init__(failure_reason)
self.bootstrap_room = bootstrap_room
self.failure_reason = failure_reason
def __str__(self):
return f"KVTransferError(bootstrap_room={self.bootstrap_room}): {self.failure_reason}"
# prefill
@dataclasses.dataclass
class TransferKVChunk:
room: int
prefill_kv_indices: npt.NDArray[np.int32]
index_slice: Optional[slice]
logical_page_positions: Optional[npt.NDArray[np.int32]]
state_logical_page_positions: Optional[npt.NDArray[np.int32]]
is_last_chunk: bool
prefill_aux_index: Optional[int]
state_indices: Optional[List[int]]
# decode
@dataclasses.dataclass
class TransferInfo:
room: int
endpoint: str
dst_port: int
mooncake_session_id: str
dst_kv_indices: npt.NDArray[np.int32]
dst_aux_index: int
dst_state_indices: List[int]
required_dst_info_num: int
is_dummy: bool
@classmethod
def from_zmq(cls, msg: List[bytes]):
if msg[4] == b"" and msg[5] == b"":
is_dummy = True
dst_kv_indices = np.array([], dtype=np.int32)
dst_aux_index = None
dst_state_indices = []
else:
dst_kv_indices = np.frombuffer(msg[4], dtype=np.int32)
dst_aux_index = int(msg[5].decode("ascii"))
if msg[6] == b"":
dst_state_indices = []
else:
dst_state_indices = list(np.frombuffer(msg[6], dtype=np.int32))
is_dummy = False
return cls(
room=int(msg[0].decode("ascii")),
endpoint=msg[1].decode("ascii"),
dst_port=int(msg[2].decode("ascii")),
mooncake_session_id=msg[3].decode("ascii"),
dst_kv_indices=dst_kv_indices,
dst_aux_index=dst_aux_index,
dst_state_indices=dst_state_indices,
required_dst_info_num=int(msg[7].decode("ascii")),
is_dummy=is_dummy,
)
# decode
@dataclasses.dataclass
class KVArgsRegisterInfo:
room: str
endpoint: str
dst_port: int
mooncake_session_id: str
dst_kv_ptrs: list[int]
dst_aux_ptrs: list[int]
dst_state_data_ptrs: list[int]
dst_tp_rank: int
dst_attn_tp_size: int
dst_kv_item_len: int
# for mamba state different tp slice transfer
dst_state_item_lens: list[int]
dst_state_dim_per_tensor: list[int]
dst_state_layer_ids: list[int]
@classmethod
def from_zmq(cls, msg: List[bytes]):
return cls(
room=str(msg[0].decode("ascii")),
endpoint=msg[1].decode("ascii"),
dst_port=int(msg[2].decode("ascii")),
mooncake_session_id=msg[3].decode("ascii"),
dst_kv_ptrs=list(struct.unpack(f"{len(msg[4])//8}Q", msg[4])),
dst_aux_ptrs=list(struct.unpack(f"{len(msg[5])//8}Q", msg[5])),
dst_state_data_ptrs=list(struct.unpack(f"{len(msg[6])//8}Q", msg[6])),
dst_tp_rank=int(msg[7].decode("ascii")),
dst_attn_tp_size=int(msg[8].decode("ascii")),
dst_kv_item_len=int(msg[9].decode("ascii")),
dst_state_item_lens=(
list(struct.unpack(f"{len(msg[10])//4}I", msg[10]))
if len(msg) > 10 and len(msg[10]) > 0
else []
),
dst_state_dim_per_tensor=(
list(struct.unpack(f"{len(msg[11])//4}I", msg[11]))
if len(msg) > 11 and len(msg[11]) > 0
else []
),
dst_state_layer_ids=(
list(struct.unpack(f"{len(msg[12])//4}i", msg[12]))
if len(msg) > 12 and len(msg[12]) > 0
else []
),
)
class AuxDataCodec:
"""Handles serialization and deserialization of auxiliary data buffers"""
@staticmethod
def serialize_data_from_buffer(src_addr, data_length):
"""Serialize data from memory buffer to bytes"""
buffer = (ctypes.c_byte * data_length).from_address(src_addr)
return bytes(buffer)
@staticmethod
def deserialize_data_to_buffer(kv_args, buffer_index, aux_index, data):
"""Deserialize bytes into target memory buffer"""
dst_aux_ptr = kv_args.aux_data_ptrs[buffer_index]
item_len = kv_args.aux_item_lens[buffer_index]
dst_addr = dst_aux_ptr + item_len * aux_index
buffer = (ctypes.c_byte * len(data)).from_address(dst_addr)
buffer[:] = data
return
class MooncakeKVManager(CommonKVManager):
AUX_DATA_HEADER = b"AUX_DATA"
def __init__(
self,
args: KVArgs,
disaggregation_mode: DisaggregationMode,
server_args: ServerArgs,
is_mla_backend: Optional[bool] = False,
):
super().__init__(args, disaggregation_mode, server_args, is_mla_backend)
self.init_engine()
self.register_buffer_to_engine()
if self.disaggregation_mode == DisaggregationMode.PREFILL:
self.start_prefill_thread()
self.session_failures = defaultdict(int)
self.failed_sessions = set()
self.session_lock = threading.Lock()
# Determine the number of threads to use for kv sender
cpu_count = os.cpu_count()
transfer_thread_pool_size = (
envs.SGLANG_DISAGGREGATION_THREAD_POOL_SIZE.get()
)
if transfer_thread_pool_size is None:
transfer_thread_pool_size = min(max(4, int(0.5 * cpu_count) // 8), 12)
transfer_queue_size = envs.SGLANG_DISAGGREGATION_QUEUE_SIZE.get()
self.transfer_queues: List[FastQueue] = [
FastQueue() for _ in range(transfer_queue_size)
]
assert transfer_thread_pool_size >= transfer_queue_size, (
f"The environment variable SGLANG_DISAGGREGATION_THREAD_POOL_SIZE={transfer_thread_pool_size} must be "
f"greater than or equal to SGLANG_DISAGGREGATION_QUEUE_SIZE={transfer_queue_size}."
)
self.executors = [
concurrent.futures.ThreadPoolExecutor(
transfer_thread_pool_size // transfer_queue_size
)
for _ in range(transfer_queue_size)
]
for queue, executor in zip(self.transfer_queues, self.executors):
threading.Thread(
target=self.transfer_worker, args=(queue, executor), daemon=True
).start()
self.enable_custom_mem_pool, self.custom_mem_pool_type = (
check_mooncake_custom_mem_pool_enabled()
)
self.enable_per_layer_async_transfer = (
envs.SGLANG_CP_SHARED_KV_PER_LAYER_TRANSFER.get()
)
elif self.disaggregation_mode == DisaggregationMode.DECODE:
self.start_decode_thread()
def init_engine(self):
self.engine = get_mooncake_transfer_engine()
def register_buffer_to_engine(self):
# Batch register KV data buffers
if self.kv_args.kv_data_ptrs and self.kv_args.kv_data_lens:
_cp_draft_shared_kv_debug(
"register_buffers mode=%s cp_rank=%s total_kv_bufs=%s "
"draft_start=%s draft_count=%s kv_lens=%s kv_item_lens=%s "
"state_type=%s state_bufs=%s state_lens=%s state_item_lens=%s "
"draft_state_type=%s draft_state_bufs=%s",
self.disaggregation_mode,
self.attn_cp_rank,
len(self.kv_args.kv_data_ptrs),
getattr(self.kv_args, "draft_kv_buffer_start", None),
getattr(self.kv_args, "draft_kv_buffer_count", None),
_np_summary(self.kv_args.kv_data_lens),
_np_summary(self.kv_args.kv_item_lens),
getattr(self.kv_args, "state_type", None),
len(getattr(self.kv_args, "state_data_ptrs", []) or []),
_np_summary(getattr(self.kv_args, "state_data_lens", [])),
_np_summary(getattr(self.kv_args, "state_item_lens", [])),
getattr(self.kv_args, "draft_state_type", None),
getattr(self.kv_args, "draft_state_buffer_count", None),
)
self.engine.batch_register(
self.kv_args.kv_data_ptrs, self.kv_args.kv_data_lens
)
# Batch register auxiliary data buffers
if self.kv_args.aux_data_ptrs and self.kv_args.aux_data_lens:
self.engine.batch_register(
self.kv_args.aux_data_ptrs, self.kv_args.aux_data_lens
)
# Batch register state/extra pool data buffers
if self.kv_args.state_data_ptrs and self.kv_args.state_data_lens:
self.engine.batch_register(
self.kv_args.state_data_ptrs, self.kv_args.state_data_lens
)
def _transfer_data(self, mooncake_session_id, transfer_blocks):
if not transfer_blocks:
return 0
src_addrs, dst_addrs, lengths = zip(*transfer_blocks)
return self.engine.batch_transfer_sync(
mooncake_session_id, list(src_addrs), list(dst_addrs), list(lengths)
)
def _transfer_layers_async(
self, mooncake_session_id, layers_params, set_transfer_blocks
):
# Submit each layer's transfer non-blocking (pipelined in the RDMA engine),
# then wait for all to complete once. Removes the per-layer blocking-sync tax
# (B1a) and is the transfer mechanism for per-layer overlap (lever A). Uses the
# safe async API (G1: batch_transfer_async_submit + wait_batch_transfers),
# never the OnCuda busy-wait/_exit path.
batch_ids = []
for src_ptr, dst_ptr, item_len in layers_params:
transfer_blocks = set_transfer_blocks(src_ptr, dst_ptr, item_len)
if not transfer_blocks:
continue
src_addrs, dst_addrs, lengths = zip(*transfer_blocks)
batch_id = self.engine.batch_transfer_async_submit(
mooncake_session_id, list(src_addrs), list(dst_addrs), list(lengths)
)
if batch_id < 0:
# Submit failed: drain whatever was already submitted, then fail.
if batch_ids:
self.engine.wait_batch_transfers(batch_ids)
return -1
batch_ids.append(batch_id)
return self.engine.wait_batch_transfers(batch_ids)
def build_per_layer_context(
self,
mooncake_session_id: str,
prefill_kv_indices: npt.NDArray[np.int32],
dst_kv_indices: npt.NDArray[np.int32],
):
"""Build a PerLayerTransferContext (lever A) for one request's main-KV pages,
from the SAME CP-filtered (prefill_kv_indices, dst_kv_indices) the post-forward
transfer would use — so the bytes moved are identical to the monolithic path.
The caller supplies the indices (reusing the send() CP filter, so this does NOT
re-derive the CP owner mapping — the #1 correctness risk). Mirrors the MLA
branch of _send_kvcache_generic exactly. Returns None if not applicable
(MHA / no decode registration yet / empty owned set)."""
if not self.is_mla_backend:
return None # first lever-A impl targets MLA (the production GLM/NSA path)
reg = self.decode_kv_args_table.get(mooncake_session_id)
if reg is None or len(prefill_kv_indices) == 0:
return None
from sglang.srt.disaggregation.cp_per_layer_transfer import (
PerLayerTransferContext,
build_layer_blocks,
)
prefill_kv_blocks, dst_kv_blocks = group_concurrent_contiguous(
prefill_kv_indices, dst_kv_indices
)
src_kv_ptrs, dst_kv_ptrs, n_layers = self.get_mla_kv_ptrs_with_pp(
self.kv_args.kv_data_ptrs, reg.dst_kv_ptrs
)
item_lens = self.kv_args.kv_item_lens
def get_blocks(layer_id):
if layer_id >= n_layers:
return None
return build_layer_blocks(
src_kv_ptrs[layer_id],
dst_kv_ptrs[layer_id],
item_lens[layer_id],
prefill_kv_blocks,
dst_kv_blocks,
)
return PerLayerTransferContext(
self.engine, mooncake_session_id, get_blocks, num_layers=n_layers
)
def register_per_layer_transfer(self, room, page_indices, chunk_key=0) -> bool:
"""Lever A: before the forward, build + register a per-layer transfer context
for `room` so the per-layer notifier overlaps its main-KV transfer with the
forward. Reuses send()'s CP filter exactly (no re-derivation). Scoped to
CP-shared-KV (the target scenario). Returns True iff a context was registered;
a False just falls back to the monolithic post-forward transfer (still correct).
page_indices = the request's full new-token logical page ids (req_to_token)."""
mgr = getattr(self, "per_layer_transfer_manager", None)
if mgr is None or not self.server_args.enable_nsa_prefill_cp_shared_kv:
return False
infos = self.transfer_infos.get(room)
if not infos:
return False
# The per-layer path registers exactly ONE context per room/chunk, but the
# transfer worker iterates every non-dummy decode info for the room and calls
# finish() per info (conn.py reqs_to_be_processed loop). That is only sound
# when there is exactly one non-dummy info (required_dst_info_num == 1). For
# decode attn_tp < prefill attn_tp a single prefill rank holds >1 non-dummy
# infos; finishing once-per-info would over-pop chunk contexts and the single
# ctx only carries one info's dst_kv_indices. Fall back to the monolithic
# post-forward transfer (which fans out to all infos) in that case.
non_dummy = [
info for info in infos.values() if not getattr(info, "is_dummy", False)
]
if len(non_dummy) != 1:
return False
info = non_dummy[0]
from sglang.srt.disaggregation.utils import filter_kv_pages_for_cp_shared_kv
from sglang.srt.mem_cache.cp_shared_kv_layout import CpSharedKVLayout
layout = CpSharedKVLayout(
page_size=self.kv_args.page_size,
cp_size=self.attn_cp_size,
cp_rank=self.attn_cp_rank,
)
pages = np.asarray(page_indices, dtype=np.int32)
# chunk_key is this chunk's start_send_idx in TOKENS (page-aligned for any
# non-first chunk). The CP filter's `positions` (second return) are absolute
# full-sequence page positions built from chunk_page_start, and the transfer
# indexes the FULL-request dst_kv_indices by those absolute positions (mirrors
# send(): chunk_page_start=index_slice.start, worker: dst_kv_indices[logical_
# page_positions]). Must offset by the chunk's absolute page start, else chunk
# N>0 writes its KV onto chunk 0's decode pages. page_size divides chunk_key.
chunk_page_start = int(chunk_key) // self.kv_args.page_size
owned_pages, positions = filter_kv_pages_for_cp_shared_kv(
layout=layout, logical_pages=pages, chunk_page_start=chunk_page_start
)
dst_indices = np.asarray(info.dst_kv_indices, dtype=np.int32)[positions]
ctx = self.build_per_layer_context(
info.mooncake_session_id, owned_pages, dst_indices
)
if ctx is None:
return False
mgr.register(room, ctx, chunk_key=chunk_key)
logger.debug(
"[CP_PER_LAYER_TRANSFER] registered room=%s chunk=%s owned_pages=%d",
room,
chunk_key,
len(owned_pages),
)
return True
def _send_kvcache_generic(
self,
mooncake_session_id: str,
src_data_ptrs: list[int],
dst_data_ptrs: list[int],
item_lens: list[int],
prefill_data_indices: npt.NDArray[np.int32],
dst_data_indices: npt.NDArray[np.int32],
executor: concurrent.futures.ThreadPoolExecutor,
debug_room: Optional[int] = None,
) -> int:
"""
Generic KV cache transfer supporting both MHA and MLA architectures.
This method is used by both send_kvcache (full pool) and maybe_send_extra.
"""
# Group by indices for optimization
prefill_kv_blocks, dst_kv_blocks = group_concurrent_contiguous(
prefill_data_indices, dst_data_indices
)
transfer_stats_enabled = _mooncake_transfer_stats_enabled()
grouping_stats = None
if transfer_stats_enabled:
grouping_stats = contiguous_group_stats(
prefill_data_indices,
dst_data_indices,
prefill_kv_blocks,
dst_kv_blocks,
)
layers_params = None
# Decode pp size should be equal to prefill pp size or 1
if self.is_mla_backend:
src_kv_ptrs, dst_kv_ptrs, layers_current_pp_stage = (
self.get_mla_kv_ptrs_with_pp(src_data_ptrs, dst_data_ptrs)
)
layers_params = [
(
src_kv_ptrs[layer_id],
dst_kv_ptrs[layer_id],
item_lens[layer_id],
)
for layer_id in range(layers_current_pp_stage)
]
else:
src_k_ptrs, src_v_ptrs, dst_k_ptrs, dst_v_ptrs, layers_current_pp_stage = (
self.get_mha_kv_ptrs_with_pp(src_data_ptrs, dst_data_ptrs)
)
# item_lens structure: [k_layer0, k_layer1, ..., k_layerN, v_layer0, v_layer1, ..., v_layerN]
# Use correct item lengths for K and V separately
if layers_current_pp_stage > len(dst_k_ptrs):
logger.error(
"Prefill transfer kvcache error, layers_current_pp_stage is out of range: "
f"layers_current_pp_stage={layers_current_pp_stage}, len(dst_k_ptrs)={len(dst_k_ptrs)}"
)
return -1
layers_params = [
(
src_k_ptrs[layer_id],
dst_k_ptrs[layer_id],
item_lens[layer_id], # K item length
)
for layer_id in range(layers_current_pp_stage)
] + [
(
src_v_ptrs[layer_id],
dst_v_ptrs[layer_id],
item_lens[layers_current_pp_stage + layer_id], # V item length
)
for layer_id in range(layers_current_pp_stage)
]
assert layers_params is not None
def set_transfer_blocks(
src_ptr: int, dst_ptr: int, item_len: int
) -> List[Tuple[int, int, int]]:
transfer_blocks = []
for prefill_index, decode_index in zip(prefill_kv_blocks, dst_kv_blocks):
src_addr = src_ptr + int(prefill_index[0]) * item_len
dst_addr = dst_ptr + int(decode_index[0]) * item_len
length = item_len * len(prefill_index)
transfer_blocks.append((src_addr, dst_addr, length))
return transfer_blocks
# Worker function for processing a single layer
def process_layer(src_ptr: int, dst_ptr: int, item_len: int) -> int:
transfer_blocks = set_transfer_blocks(src_ptr, dst_ptr, item_len)
return self._transfer_data(mooncake_session_id, transfer_blocks)
# Worker function for processing all layers in a batch
def process_layers(layers_params: List[Tuple[int, int, int]]) -> int:
transfer_blocks = []
for src_ptr, dst_ptr, item_len in layers_params:
transfer_blocks.extend(set_transfer_blocks(src_ptr, dst_ptr, item_len))
return self._transfer_data(mooncake_session_id, transfer_blocks)
start_time = time.perf_counter() if transfer_stats_enabled else 0.0
if self.enable_per_layer_async_transfer:
status = self._transfer_layers_async(
mooncake_session_id, layers_params, set_transfer_blocks
)
elif self.enable_custom_mem_pool:
futures = [
executor.submit(
process_layer,
src_ptr,
dst_ptr,
item_len,
)
for (src_ptr, dst_ptr, item_len) in layers_params
]
for future in concurrent.futures.as_completed(futures):
status = future.result()
if status != 0:
for f in futures:
f.cancel()
if transfer_stats_enabled:
self._log_kvcache_transfer_stats(
mooncake_session_id=mooncake_session_id,
debug_room=debug_room,
grouping_stats=grouping_stats,
layers_params=layers_params,
elapsed_ms=(time.perf_counter() - start_time) * 1000,
status=status,
custom_mem_pool=True,
)
return status
status = 0
else:
# Combining all layers' params in one batch transfer is more efficient
# compared to using multiple threads
status = process_layers(layers_params)
if transfer_stats_enabled:
self._log_kvcache_transfer_stats(
mooncake_session_id=mooncake_session_id,
debug_room=debug_room,
grouping_stats=grouping_stats,
layers_params=layers_params,
elapsed_ms=(time.perf_counter() - start_time) * 1000,
status=status,
custom_mem_pool=self.enable_custom_mem_pool,
)
return status
def _log_kvcache_transfer_stats(
self,
mooncake_session_id: str,
debug_room: Optional[int],
grouping_stats: Optional[dict[str, object]],
layers_params: List[Tuple[int, int, int]],
elapsed_ms: float,
status: int,
custom_mem_pool: bool,
) -> None:
if grouping_stats is None:
return
page_count = int(grouping_stats["pages"])
group_count = int(grouping_stats["groups"])
layer_count = len(layers_params)
item_bytes_per_page = sum(int(item_len) for _, _, item_len in layers_params)
total_bytes = page_count * item_bytes_per_page
transfer_blocks = group_count * layer_count
avg_block_bytes = (
float(total_bytes / transfer_blocks) if transfer_blocks else 0.0
)
bandwidth_gbps = (
float(total_bytes / elapsed_ms / 1e6) if elapsed_ms > 0 else 0.0
)
_mooncake_transfer_stats_log(
"cp_rank=%s room=%s session=%s status=%s custom_mem_pool=%s "
"pages=%s groups=%s avg_group_pages=%.2f max_group_pages=%s "
"layers=%s transfer_blocks=%s total_bytes=%.3fGiB "
"avg_block_bytes=%.1fKiB elapsed_ms=%.3f bandwidth=%.2fGB/s "
"src_diff_head=%s dst_diff_head=%s",
self.attn_cp_rank,
debug_room,
mooncake_session_id,
status,
custom_mem_pool,
page_count,
group_count,
float(grouping_stats["avg_group_pages"]),
grouping_stats["max_group_pages"],
layer_count,
transfer_blocks,
total_bytes / (1024**3),
avg_block_bytes / 1024,
elapsed_ms,
bandwidth_gbps,
grouping_stats["src_diff_head"],
grouping_stats["dst_diff_head"],
)
def send_kvcache(
self,
mooncake_session_id: str,
prefill_kv_indices: npt.NDArray[np.int32],
dst_kv_ptrs: list[int],
dst_kv_indices: npt.NDArray[np.int32],
executor: concurrent.futures.ThreadPoolExecutor,
debug_room: Optional[int] = None,
):
return self._send_kvcache_generic(
mooncake_session_id=mooncake_session_id,
src_data_ptrs=self.kv_args.kv_data_ptrs,
dst_data_ptrs=dst_kv_ptrs,
item_lens=self.kv_args.kv_item_lens,
prefill_data_indices=prefill_kv_indices,
dst_data_indices=dst_kv_indices,
executor=executor,
debug_room=debug_room,
)
def send_kvcache_slice(
self,
mooncake_session_id: str,
prefill_kv_indices: npt.NDArray[np.int32],
dst_kv_ptrs: list[int],
dst_kv_indices: npt.NDArray[np.int32],
dst_tp_rank: int,
dst_attn_tp_size: int,
dst_kv_item_len: int,
executor: concurrent.futures.ThreadPoolExecutor,
):
"""
Sends KV cache slices from this Prefill rank to a target Decode rank,
supporting generic M-to-N TP size configurations.
NOTE: This implementation calls the transfer engine for each token slot within
each page to ensure correctness for any page_size and head-slicing configuration.
This may introduce performance overhead (increased TTFT) for long sequences.
"""
# Extract configuration
local_tp_rank_in_group = self.kv_args.engine_rank % self.attn_tp_size
src_kv_item_len = self.kv_args.kv_item_lens[0]
dst_tp_rank_in_group = dst_tp_rank % dst_attn_tp_size
page_size = self.kv_args.page_size
# Use total KV head count (not per-rank) for correct head distribution.
# Per-rank kv_head_num is max(1, total//tp) which loses info when total < tp.
total_kv_heads = getattr(self.kv_args, "total_kv_head_num", 0)
if total_kv_heads <= 0:
total_kv_heads = self.kv_args.kv_head_num * self.attn_tp_size
src_heads_per_rank = max(1, total_kv_heads // self.attn_tp_size)
dst_heads_per_rank = max(1, total_kv_heads // dst_attn_tp_size)
bytes_per_head_slice_to_send = (
dst_kv_item_len // page_size // dst_heads_per_rank
)
# GQA replication: how many prefill ranks share the same KV head
src_replication = max(1, self.attn_tp_size // total_kv_heads)
# Determine slicing parameters based on TP configuration
if self.attn_tp_size > dst_attn_tp_size:
# Send KVCache from multiple prefill instances to 1 decode instance
src_head_start_offset = 0
num_heads_to_send = src_heads_per_rank
unique_head_idx = local_tp_rank_in_group // src_replication
dst_head_start_offset = (
unique_head_idx * src_heads_per_rank
) % dst_heads_per_rank
else:
# Send KVCache from 1 prefill instance to multiple decode instances
src_head_start_offset = (
dst_tp_rank_in_group * dst_heads_per_rank
) % src_heads_per_rank
num_heads_to_send = dst_heads_per_rank
dst_head_start_offset = 0
src_k_ptrs, src_v_ptrs, dst_k_ptrs, dst_v_ptrs, layers_current_pp_stage = (
self.get_mha_kv_ptrs_with_pp(self.kv_args.kv_data_ptrs, dst_kv_ptrs)
)
# Calculate precise byte offset and length for the sub-slice within the token
src_head_slice_offset = src_head_start_offset * bytes_per_head_slice_to_send
dst_head_slice_offset = dst_head_start_offset * bytes_per_head_slice_to_send
heads_bytes_per_token_to_send = num_heads_to_send * bytes_per_head_slice_to_send
# Sanity check: The data sub-slice to be sent should fit into the dst buffer.
# This means heads_bytes_per_token_to_send <= (dst_kv_item_len // page_size)
if heads_bytes_per_token_to_send > (dst_kv_item_len // page_size):
logger.error(
f"[{mooncake_session_id}] slice size ({heads_bytes_per_token_to_send}) exceeds "
f"target token slot size ({dst_kv_item_len // page_size})"
)
return -1
prefill_page_indices = prefill_kv_indices.reshape(-1, 1).astype(np.int64)
decode_page_indices = dst_kv_indices.reshape(-1, 1).astype(np.int64)
tokens_per_page = np.arange(page_size, dtype=np.int64).reshape(1, -1)
bytes_per_token_on_prefill = src_kv_item_len // page_size
bytes_per_token_on_decode = dst_kv_item_len // page_size
src_token_slot_offsets = (
tokens_per_page * bytes_per_token_on_prefill + src_head_slice_offset
)
dst_token_slot_offsets = (
tokens_per_page * bytes_per_token_on_decode + dst_head_slice_offset
)
def process_layer_tp_aware(src_layer_ptr, dst_layer_ptr):
src_page_base_addrs = src_layer_ptr + prefill_page_indices * src_kv_item_len
dst_page_base_addrs = dst_layer_ptr + decode_page_indices * dst_kv_item_len
src_slice_addrs = src_page_base_addrs + src_token_slot_offsets
dst_slice_addrs = dst_page_base_addrs + dst_token_slot_offsets
src_addr_list = src_slice_addrs.reshape(-1).tolist()
if not src_addr_list:
# Nothing to transfer for this layer.
return 0
dst_addr_list = dst_slice_addrs.reshape(-1).tolist()
total_slices = len(src_addr_list)
length_list = [heads_bytes_per_token_to_send] * total_slices
return self.engine.batch_transfer_sync(
mooncake_session_id, src_addr_list, dst_addr_list, length_list
)
futures = []
for i in range(layers_current_pp_stage):
futures.append(
executor.submit(process_layer_tp_aware, src_k_ptrs[i], dst_k_ptrs[i])
)
for i in range(layers_current_pp_stage):
futures.append(
executor.submit(process_layer_tp_aware, src_v_ptrs[i], dst_v_ptrs[i])
)
for future in concurrent.futures.as_completed(futures):
status = future.result()
if status != 0:
for f in futures:
f.cancel()
return status
return 0
def send_aux(
self,
req: TransferInfo,
prefill_aux_index: int,
dst_aux_ptrs: list[int],
):
# TODO(shangming): Fix me when nvlink_transport of Mooncake is bug-free
if (
self.enable_custom_mem_pool and self.custom_mem_pool_type == "NVLINK"
) or envs.SGLANG_MOONCAKE_SEND_AUX_TCP.get():
return self.send_aux_tcp(req, prefill_aux_index, dst_aux_ptrs)
transfer_blocks = []
prefill_aux_ptrs = self.kv_args.aux_data_ptrs
prefill_aux_item_lens = self.kv_args.aux_item_lens
for i, dst_aux_ptr in enumerate(dst_aux_ptrs):
length = prefill_aux_item_lens[i]
src_addr = prefill_aux_ptrs[i] + length * prefill_aux_index
dst_addr = dst_aux_ptrs[i] + length * req.dst_aux_index
transfer_blocks.append((src_addr, dst_addr, length))
return self._transfer_data(req.mooncake_session_id, transfer_blocks)
def send_aux_tcp(
self,
req: TransferInfo,
prefill_aux_index: int,
dst_aux_ptrs: list[int],
):
prefill_aux_ptrs = self.kv_args.aux_data_ptrs
prefill_aux_item_lens = self.kv_args.aux_item_lens
for i in range(len(prefill_aux_ptrs)):
length = prefill_aux_item_lens[i]
src_addr = prefill_aux_ptrs[i] + length * prefill_aux_index
data = AuxDataCodec.serialize_data_from_buffer(src_addr, length)
self.send_aux_data_to_endpoint(
remote=req.endpoint,
dst_port=req.dst_port,
room=req.room,
buffer_index=i,
aux_index=req.dst_aux_index,
data=data,
)
return 0
def send_aux_data_to_endpoint(
self,
remote: str,
dst_port: int,
room: int,
buffer_index: int,
aux_index: int,
data: bytes,
):
na = NetworkAddress(remote, dst_port)
socket = self._connect(na.to_tcp(), is_ipv6=na.is_ipv6)
socket.send_multipart(
[
MooncakeKVManager.AUX_DATA_HEADER,
str(room).encode("ascii"),
str(buffer_index).encode("ascii"),
str(aux_index).encode("ascii"),
struct.pack(">I", len(data)),
data,
]
)
def _handle_aux_data(self, msg: List[bytes]):
"""Handle AUX_DATA messages received by the decode thread."""
room = int(msg[1].decode("ascii"))
buffer_index = int(msg[2].decode("ascii"))
aux_index = int(msg[3].decode("ascii"))
data_length = struct.unpack(">I", msg[4])[0]
data = msg[5]
if len(data) != data_length:
logger.error(f"AUX_DATA length mismatch for bootstrap_room {room}")
return
AuxDataCodec.deserialize_data_to_buffer(
self.kv_args, buffer_index, aux_index, data
)
logger.debug(
f"Received AUX_DATA for bootstrap_room {room} with length:{len(data)}"
)
def maybe_send_extra(
self,
req: TransferInfo,
prefill_state_indices: list[int],
dst_state_data_ptrs: list[int],
executor: concurrent.futures.ThreadPoolExecutor,
target_rank_registration_info: Optional[KVArgsRegisterInfo] = None,
dst_state_indices: Optional[npt.NDArray[np.int32]] = None,
):
"""Send state or extra pool data with type-specific handling."""
state_type = getattr(self.kv_args, "state_type", "none")
_cp_draft_shared_kv_debug(
"maybe_send_extra_state cp_rank=%s room=%s session=%s state_type=%s "
"src_state_bufs=%s dst_state_bufs=%s src_state_lens=%s src_state_item_lens=%s "
"prefill_state_indices=%s dst_state_indices=%s draft_state_type=%s "
"draft_state_bufs=%s target_registration_state_bufs=%s",
self.attn_cp_rank,
req.room,
req.mooncake_session_id,
state_type,
len(getattr(self.kv_args, "state_data_ptrs", []) or []),
len(dst_state_data_ptrs or []),
_np_summary(getattr(self.kv_args, "state_data_lens", [])),
_np_summary(getattr(self.kv_args, "state_item_lens", [])),
_np_summary(prefill_state_indices),
_np_summary(
dst_state_indices
if dst_state_indices is not None
else getattr(req, "dst_state_indices", [])
),
getattr(self.kv_args, "draft_state_type", None),
getattr(self.kv_args, "draft_state_buffer_count", None),
(
len(target_rank_registration_info.dst_state_data_ptrs)
if target_rank_registration_info is not None
else None
),
)
if state_type == "mamba":
# Check if we need slice transfer for different TP sizes
if (
target_rank_registration_info is not None
and self.attn_tp_size != target_rank_registration_info.dst_attn_tp_size
):
return self._send_mamba_state_slice(
req,
prefill_state_indices,
dst_state_data_ptrs,
target_rank_registration_info.dst_state_item_lens,
target_rank_registration_info.dst_state_dim_per_tensor,
target_rank_registration_info.dst_tp_rank,
target_rank_registration_info.dst_attn_tp_size,
)
else:
return self._send_mamba_state(
req,
prefill_state_indices,
dst_state_data_ptrs,
)
elif state_type in ["swa", "nsa"]:
# SWA and NSA hybrid models do not support different TP sizes yet
if (
target_rank_registration_info is not None
and not self.is_mla_backend
and self.attn_tp_size != target_rank_registration_info.dst_attn_tp_size
):
raise RuntimeError(
f"PD Disaggregation does NOT support PD different TP sizes for non-MLA {state_type.upper()} hybrid models yet."
)
src_state_layer_ids = list(
getattr(self.kv_args, "state_layer_ids", []) or []
)
dst_state_layer_ids = (
list(getattr(target_rank_registration_info, "dst_state_layer_ids", []) or [])
if target_rank_registration_info is not None
else []
)
if src_state_layer_ids or dst_state_layer_ids:
if src_state_layer_ids != dst_state_layer_ids:
raise RuntimeError(
"[CP_SHARED_KV_FAIL_FAST][state_layer_ids] "
f"prefill={src_state_layer_ids} decode={dst_state_layer_ids} "
f"state_type={state_type} room={req.room} "
f"session={req.mooncake_session_id}"
)
effective_dst_state_indices = (
np.asarray(dst_state_indices, dtype=np.int32)
if dst_state_indices is not None
else np.asarray(req.dst_state_indices, dtype=np.int32)
)
# Clip src/dst state indices to the shorter side so the transfer never
# reads past prefill_state_indices or writes past dst_state_indices.
# Ported from upstream sgl-project/sglang #23323 (the prior logic only
# handled prefill<dst and clipped the wrong array, a no-op).
if len(prefill_state_indices) > len(effective_dst_state_indices):
logger.warning(
f"len(prefill_state_indices) = {len(prefill_state_indices)}, len(dst_state_indices) = {len(effective_dst_state_indices)}"
)
prefill_state_indices = prefill_state_indices[
: len(effective_dst_state_indices)
]
elif len(prefill_state_indices) < len(effective_dst_state_indices):
logger.warning(
f"len(prefill_state_indices) = {len(prefill_state_indices)}, len(dst_state_indices) = {len(effective_dst_state_indices)}"
)
effective_dst_state_indices = effective_dst_state_indices[
: len(prefill_state_indices)
]
src_state_data_ptrs = self.kv_args.state_data_ptrs
dst_state_ptrs = dst_state_data_ptrs
state_item_lens = self.kv_args.state_item_lens
if len(src_state_data_ptrs) != len(dst_state_ptrs):
if src_state_layer_ids or dst_state_layer_ids:
raise RuntimeError(
"[CP_SHARED_KV_FAIL_FAST][state_buffer_count] "
f"src={len(src_state_data_ptrs)} dst={len(dst_state_ptrs)} "
f"src_layers={src_state_layer_ids} "
f"dst_layers={dst_state_layer_ids} state_type={state_type} "
f"room={req.room} session={req.mooncake_session_id}"
)
transfer_buf_count = min(len(src_state_data_ptrs), len(dst_state_ptrs))
logger.warning(
"State buffer count mismatch during PD transfer: src=%s dst=%s "
"state_type=%s draft_state_type=%s draft_state_bufs=%s room=%s "
"session=%s; transferring first %s buffers only",
len(src_state_data_ptrs),
len(dst_state_ptrs),
state_type,
getattr(self.kv_args, "draft_state_type", None),
getattr(self.kv_args, "draft_state_buffer_count", None),
req.room,
req.mooncake_session_id,
transfer_buf_count,
)
src_state_data_ptrs = src_state_data_ptrs[:transfer_buf_count]
dst_state_ptrs = dst_state_ptrs[:transfer_buf_count]
state_item_lens = state_item_lens[:transfer_buf_count]
# Reuse _send_kvcache_generic interface to send extra pool data
prefill_state_indices = np.array(prefill_state_indices, dtype=np.int32)
return self._send_kvcache_generic(
mooncake_session_id=req.mooncake_session_id,
src_data_ptrs=src_state_data_ptrs,
dst_data_ptrs=dst_state_ptrs,
item_lens=state_item_lens,
prefill_data_indices=prefill_state_indices,
dst_data_indices=effective_dst_state_indices,
executor=executor,
)
else:
return 0
def _send_mamba_state(
self,
req: TransferInfo,
prefill_mamba_index: list[int],
dst_state_data_ptrs: list[int],
):
"""Transfer Mamba states."""
assert len(prefill_mamba_index) == 1, "Mamba should have single state index"
transfer_blocks = []
prefill_state_data_ptrs = self.kv_args.state_data_ptrs
prefill_state_item_lens = self.kv_args.state_item_lens
for i, dst_state_ptr in enumerate(dst_state_data_ptrs):
length = prefill_state_item_lens[i]
src_addr = prefill_state_data_ptrs[i] + length * int(prefill_mamba_index[0])
dst_addr = dst_state_ptr + length * int(req.dst_state_indices[0])
transfer_blocks.append((src_addr, dst_addr, length))
return self._transfer_data(req.mooncake_session_id, transfer_blocks)
def _send_mamba_state_slice(
self,
req: TransferInfo,
prefill_mamba_index: list[int],
dst_state_data_ptrs: list[int],
dst_state_item_lens: list[int],
dst_state_dim_per_tensor: list[int],
dst_tp_rank: int,
dst_attn_tp_size: int,
):
"""Transfer Mamba states with TP slice support.
Mamba state layout:
- conv_state: [num_layers, size+1, conv_dim/tp, conv_kernel-1]
- temporal_state: [num_layers, size+1, num_heads/tp, head_dim, state_size]
The 3rd dimension is sliced by TP. When prefill and decode have different
attn_tp_size, we need to slice the state accordingly.
"""
logger.warning_once(
"Using Mamba state slice transfer for different TP sizes between prefill and decode. "
f"Prefill attn_tp_size={self.attn_tp_size}, Decode attn_tp_size={dst_attn_tp_size}. "
"Performance may be affected."
)
assert len(prefill_mamba_index) == 1, "Mamba should have single state index"
transfer_blocks = []
prefill_state_data_ptrs = self.kv_args.state_data_ptrs
prefill_state_item_lens = self.kv_args.state_item_lens
src_state_dim_per_tensor = getattr(self.kv_args, "state_dim_per_tensor", [])
# If no dimension info available, fall back to regular transfer
if not src_state_dim_per_tensor or not dst_state_dim_per_tensor:
return self._send_mamba_state(req, prefill_mamba_index, dst_state_data_ptrs)
local_tp_rank_in_group = self.kv_args.engine_rank % self.attn_tp_size
dst_tp_rank_in_group = dst_tp_rank % dst_attn_tp_size
for i, dst_state_ptr in enumerate(dst_state_data_ptrs):
src_item_len = prefill_state_item_lens[i]
dst_item_len = dst_state_item_lens[i]
src_dim = src_state_dim_per_tensor[i]
dst_dim = dst_state_dim_per_tensor[i]
# Calculate bytes per dimension slice
# item_len = dim * trailing_dims_size, so trailing_dims_size = item_len / dim
src_bytes_per_dim = src_item_len // src_dim
dst_bytes_per_dim = dst_item_len // dst_dim
# Determine slicing parameters based on TP configuration
if self.attn_tp_size > dst_attn_tp_size:
# Multiple prefill ranks send to 1 decode rank
# Each prefill sends all its dims to the appropriate offset in decode
src_dim_start = 0
num_dims_to_send = src_dim
writers_per_decode = self.attn_tp_size // dst_attn_tp_size
local_writer_idx = local_tp_rank_in_group % writers_per_decode
dst_dim_start = local_writer_idx * src_dim
else:
# 1 prefill rank sends to multiple decode ranks
# Prefill sends a slice of its dims to each decode rank
src_dim_start = (dst_tp_rank_in_group * dst_dim) % src_dim
num_dims_to_send = dst_dim
dst_dim_start = 0
# Calculate byte offsets
src_dim_offset = src_dim_start * src_bytes_per_dim
dst_dim_offset = dst_dim_start * dst_bytes_per_dim
bytes_to_send = num_dims_to_send * src_bytes_per_dim
# Calculate addresses for this state tensor
src_addr = (
prefill_state_data_ptrs[i]
+ src_item_len * int(prefill_mamba_index[0])
+ src_dim_offset
)
dst_addr = (
dst_state_ptr
+ dst_item_len * int(req.dst_state_indices[0])
+ dst_dim_offset
)
transfer_blocks.append((src_addr, dst_addr, bytes_to_send))
return self._transfer_data(req.mooncake_session_id, transfer_blocks)
def sync_status_to_decode_endpoint(
self, remote: str, dst_port: int, room: int, status: int, prefill_rank: int
):
na = NetworkAddress(remote, dst_port)
self._connect(na.to_tcp(), is_ipv6=na.is_ipv6).send_multipart(
[
str(room).encode("ascii"),
str(status).encode("ascii"),
str(prefill_rank).encode("ascii"),
]
)
def transfer_worker(
self, queue: FastQueue, executor: concurrent.futures.ThreadPoolExecutor
):
while True:
try:
kv_chunk: TransferKVChunk = queue.get()
# Skip a chunk whose room has already failed or been aborted, so we never
# transfer into KV pages that may have been reclaimed. Port of upstream
# sgl-project/sglang #27372 (abort KV-cache corruption guard). The
# decode->prefill ABORT/ABORT_ACK notification half of that PR is deferred
# until the PD test harness exists (it interleaves with staging/tracing
# infra this branch does not carry).
if (
kv_chunk.room not in self.request_status
or self.check_status(kv_chunk.room) == KVPoll.Failed
):
logger.debug(
"Skipping chunk for room %s because it has already failed or been aborted",
kv_chunk.room,
)
# Lever A: drain + drop any per-layer context for this room so an
# outstanding RDMA completes before its KV pages can be reclaimed.
per_layer_mgr = getattr(self, "per_layer_transfer_manager", None)
if per_layer_mgr is not None:
per_layer_mgr.drop(kv_chunk.room)
continue
reqs_to_be_processed = (
self.transfer_infos[kv_chunk.room].values()
if kv_chunk.room in self.transfer_infos
else []
)
polls = []
dst_ranks_infos = []
# Unique id per prefill sender so decode's response set size matches expected_response_num.
prefill_unique_rank = (
self.attn_tp_rank * (self.pp_size * self.attn_cp_size)
+ self.pp_rank * self.attn_cp_size
+ self.attn_cp_rank
)
for req in reqs_to_be_processed:
if not req.is_dummy:
# Early exit if the request has failed
with self.session_lock:
if req.mooncake_session_id in self.failed_sessions:
self.record_failure(
kv_chunk.room,
f"Decode instance could be dead, remote mooncake session {req.mooncake_session_id} is not alive",
)
self.update_status(kv_chunk.room, KVPoll.Failed)
self.sync_status_to_decode_endpoint(
req.endpoint,
req.dst_port,
req.room,
KVPoll.Failed,
prefill_unique_rank,
)
break
if kv_chunk.logical_page_positions is not None:
chunked_dst_kv_indice = req.dst_kv_indices[
kv_chunk.logical_page_positions
]
else:
assert kv_chunk.index_slice is not None
chunked_dst_kv_indice = req.dst_kv_indices[
kv_chunk.index_slice
]
_cp_draft_shared_kv_debug(
"transfer_pages cp_rank=%s room=%s prefill_pages=%s "
"logical_positions=%s dst_pages=%s is_last=%s",
self.attn_cp_rank,
kv_chunk.room,
_np_summary(kv_chunk.prefill_kv_indices),
_np_summary(kv_chunk.logical_page_positions),
_np_summary(chunked_dst_kv_indice),
kv_chunk.is_last_chunk,
)
if envs.SGLANG_DEBUG_CP_SHARED_KV.get() or envs.SGLANG_CP_TRANSFER_LOG.get():
_cp_shared_debug_log(
"transfer_worker_kv",
"transfer worker cp_rank=%s room=%s prefill_pages=%s "
"logical_positions=%s dst_pages=%s is_last=%s",
self.attn_cp_rank,
kv_chunk.room,
_np_summary(kv_chunk.prefill_kv_indices),
_np_summary(kv_chunk.logical_page_positions),
_np_summary(chunked_dst_kv_indice),
kv_chunk.is_last_chunk,
)
validate_transfer_page_count_or_raise(
prefill_indices=kv_chunk.prefill_kv_indices,
dst_indices=chunked_dst_kv_indice,
room=kv_chunk.room,
cp_rank=self.attn_cp_rank,
logical_page_positions=kv_chunk.logical_page_positions,
index_slice=kv_chunk.index_slice,
is_cp_shared_kv=(
kv_chunk.logical_page_positions is not None
),
path="mooncake_kv",
)
target_rank_registration_info: KVArgsRegisterInfo = (
self.decode_kv_args_table[req.mooncake_session_id]
)
per_layer_mgr = getattr(
self, "per_layer_transfer_manager", None
)
if per_layer_mgr is not None and per_layer_mgr.has_room(
kv_chunk.room
):
# Lever A: the main KV was transferred per-layer, overlapped
# with the forward; wait those transfers here instead of the
# monolithic send (no double-send). aux/state below unchanged.
ret = per_layer_mgr.finish(kv_chunk.room)
if ret != 0:
logger.warning(
"[CP_PER_LAYER_TRANSFER] finished room=%s ret=%s",
kv_chunk.room,
ret,
)
else:
logger.debug(
"[CP_PER_LAYER_TRANSFER] finished room=%s ret=%s",
kv_chunk.room,
ret,
)
elif self.is_mla_backend or (
self.attn_tp_size
== target_rank_registration_info.dst_attn_tp_size
):
ret = self.send_kvcache(
req.mooncake_session_id,
kv_chunk.prefill_kv_indices,
target_rank_registration_info.dst_kv_ptrs,
chunked_dst_kv_indice,
executor,
debug_room=kv_chunk.room,
)
else:
ret = self.send_kvcache_slice(
req.mooncake_session_id,
kv_chunk.prefill_kv_indices,
target_rank_registration_info.dst_kv_ptrs,
chunked_dst_kv_indice,
target_rank_registration_info.dst_tp_rank,
target_rank_registration_info.dst_attn_tp_size,
target_rank_registration_info.dst_kv_item_len,
executor,
)
if ret != 0:
with self.session_lock:
self.session_failures[req.mooncake_session_id] += 1
# Failures should never happen if the session is not dead, if the session fails once, mark it as failed
if self.session_failures[req.mooncake_session_id] >= 1:
self.failed_sessions.add(req.mooncake_session_id)
logger.error(
f"Session {req.mooncake_session_id} failed."
)
self.record_failure(
kv_chunk.room,
f"Failed to send kv chunk of {kv_chunk.room} to {req.endpoint}:{req.dst_port}",
)
self.update_status(kv_chunk.room, KVPoll.Failed)
self.sync_status_to_decode_endpoint(
req.endpoint,
req.dst_port,
req.room,
KVPoll.Failed,
prefill_unique_rank,
)
break
if kv_chunk.is_last_chunk:
if kv_chunk.state_indices is not None:
dst_state_indices = None
if kv_chunk.state_logical_page_positions is not None:
from sglang.srt.disaggregation.utils import (
select_pages_by_request_positions,
)
dst_state_indices = select_pages_by_request_positions(
req.dst_state_indices,
kv_chunk.state_logical_page_positions,
)
if envs.SGLANG_DEBUG_CP_SHARED_KV.get() or envs.SGLANG_CP_TRANSFER_LOG.get():
_cp_shared_debug_log(
"transfer_worker_state",
"transfer worker state cp_rank=%s room=%s prefill_state_pages=%s "
"state_positions=%s dst_state_pages=%s",
self.attn_cp_rank,
kv_chunk.room,
_np_summary(kv_chunk.state_indices),
_np_summary(
kv_chunk.state_logical_page_positions
),
_np_summary(dst_state_indices),
)
self.maybe_send_extra(
req,
kv_chunk.state_indices,
target_rank_registration_info.dst_state_data_ptrs,
executor,
target_rank_registration_info,
dst_state_indices,
)
# Only the last chunk we need to send the aux data
ret = self.send_aux(
req,
kv_chunk.prefill_aux_index,
target_rank_registration_info.dst_aux_ptrs,
)
polls.append(True if ret == 0 else False)
dst_ranks_infos.append(
(req.endpoint, req.dst_port, req.room)
)
# Only sync status when all the dst ranks have received the kvcache
if len(polls) == req.required_dst_info_num:
status = KVPoll.Success if all(polls) else KVPoll.Failed
self.update_status(req.room, status)
for endpoint, dst_port, room in dst_ranks_infos:
self.sync_status_to_decode_endpoint(
endpoint,
dst_port,
room,
status,
prefill_unique_rank,
)
else:
# Dummy request means the decode instance is not used, so its status can be marked as success directly
# Dummy request does not need to sync status to decode endpoint
if kv_chunk.is_last_chunk and req.room in self.request_status:
self.update_status(req.room, KVPoll.Success)
if (
kv_chunk.room not in self.request_status
or self.check_status(kv_chunk.room) == KVPoll.Success
):
if kv_chunk.room in self.transfer_infos:
self.transfer_infos.pop(kv_chunk.room)
except Exception as e:
# NOTE(shangming): Remove this when we make sure the transfer thread is bug-free
raise RuntimeError(
f"Transfer thread failed because of {e}. Prefill instance with bootstrap_port={self.bootstrap_port} is dead."
)
def start_prefill_thread(self):
def bootstrap_thread():
"""This thread recvs pre-alloc notification from the decode engine"""
# KVPoll.Bootstrapping -> KVPoll.WaitingForInput
while True:
waiting_req_bytes = self.server_socket.recv_multipart()
room = waiting_req_bytes[0].decode("ascii")
# Decode-side abort notification: mark the room Failed and ACK, so the
# transfer worker (which skips Failed rooms) stops RDMA-writing into KV
# pages the decode has freed/reused. Port of upstream sgl-project/sglang
# #27372 (decode->prefill half). MUST be handled here, before the
# UNCONDITIONAL waiting_req_bytes[3] decode below: a 4-field ABORT
# message [ABORT, room, ip, port] would otherwise fall through into the
# else branch and crash on waiting_req_bytes[7].
if room == "ABORT":
room_to_be_aborted = int(waiting_req_bytes[1].decode("ascii"))
decode_ip = waiting_req_bytes[2].decode("ascii")
decode_port = int(waiting_req_bytes[3].decode("ascii"))
if (
room_to_be_aborted in self.request_status
and self.check_status(room_to_be_aborted) != KVPoll.Success
):
self.update_status(room_to_be_aborted, KVPoll.Failed)
try:
na = NetworkAddress(decode_ip, decode_port)
self._connect(
na.to_tcp(), is_ipv6=na.is_ipv6
).send_multipart(
[b"ABORT_ACK", str(room_to_be_aborted).encode("ascii")]
)
except Exception as e:
logger.debug(
f"Failed to send ABORT_ACK for room {room_to_be_aborted}: {e}"
)
continue
mooncake_session_id = waiting_req_bytes[3].decode("ascii")
if room == "None":
self.decode_kv_args_table[mooncake_session_id] = (
KVArgsRegisterInfo.from_zmq(waiting_req_bytes)
)
with self.session_lock:
if mooncake_session_id in self.failed_sessions:
self.failed_sessions.remove(mooncake_session_id)
if mooncake_session_id in self.session_failures:
del self.session_failures[mooncake_session_id]
logger.debug(
f"Register KVArgs from {mooncake_session_id} successfully"
)
continue
else:
required_dst_info_num = int(waiting_req_bytes[7].decode("ascii"))
room = int(room)
if room not in self.transfer_infos:
self.transfer_infos[room] = {}
self.transfer_infos[room][mooncake_session_id] = (
TransferInfo.from_zmq(waiting_req_bytes)
)
# NOTE: after bootstrapping we can mark the req as waiting for input
if len(self.transfer_infos[room]) == required_dst_info_num:
self.update_status(room, KVPoll.WaitingForInput)
threading.Thread(target=bootstrap_thread).start()
def start_decode_thread(self):
def decode_thread():
while True:
msg = self.server_socket.recv_multipart()
if msg[0] == MooncakeKVManager.AUX_DATA_HEADER:
self._handle_aux_data(msg)
continue
if msg[0] == b"ABORT_ACK":
# Prefill acknowledged our abort; the room is already Failed locally,
# so nothing more to do. Port of upstream #27372. Must precede the
# 3-tuple unpack below (a 2-field ACK would otherwise raise).
continue
bootstrap_room, status, prefill_rank = msg
status = int(status.decode("ascii"))
bootstrap_room = int(bootstrap_room.decode("ascii"))
prefill_rank = int(prefill_rank.decode("ascii"))
if status == KVPoll.Success:
if bootstrap_room in self.request_status:
self.prefill_response_tracker[bootstrap_room].add(prefill_rank)
expected_response_num = (
self.required_prefill_response_num_table[bootstrap_room]
)
arrived_response_num = len(
self.prefill_response_tracker[bootstrap_room]
)
if arrived_response_num == expected_response_num:
self.update_status(bootstrap_room, KVPoll.Success)
elif status == KVPoll.Failed:
self.record_failure(
bootstrap_room,
"Failed to get kvcache from prefill instance, it might be dead",
)
self.update_status(bootstrap_room, status)
def heartbeat_checker():
while True:
time.sleep(self.heartbeat_interval)
with self.connection_lock:
addresses = list(self.prefill_info_table.keys())
for bootstrap_addr in addresses:
session = None
try:
with self.session_pool_lock:
session = self.session_pool[bootstrap_addr]
response = session.get(
f"http://{bootstrap_addr}/health",
timeout=(2, 3),
headers={"Connection": "keep-alive"},
)
if response.status_code == 200:
self.heartbeat_failures[bootstrap_addr] = 0
current_rooms = self.addr_to_rooms_tracker[
bootstrap_addr
].copy()
for bootstrap_room in current_rooms:
# Remove KVPoll.Success requests from the tracker
if bootstrap_room not in self.request_status:
self.addr_to_rooms_tracker[bootstrap_addr].discard(
bootstrap_room
)
else:
logger.info(
f"Attempting to reconnect to {bootstrap_addr}..."
)
self.heartbeat_failures[bootstrap_addr] = (
self.heartbeat_failures.get(bootstrap_addr, 0) + 1
)
with self.session_pool_lock:
if bootstrap_addr in self.session_pool:
del self.session_pool[bootstrap_addr]
except Exception:
logger.info(f"Attempting to reconnect to {bootstrap_addr}...")
self.heartbeat_failures[bootstrap_addr] = (
self.heartbeat_failures.get(bootstrap_addr, 0) + 1
)
if (
self.heartbeat_failures.get(bootstrap_addr, 0)
>= self.max_failures
):
self._handle_node_failure(bootstrap_addr)
with self.session_pool_lock:
if bootstrap_addr in self.session_pool:
del self.session_pool[bootstrap_addr]
threading.Thread(target=decode_thread).start()
threading.Thread(target=heartbeat_checker).start()
def add_transfer_request(
self,
bootstrap_room: int,
kv_indices: npt.NDArray[np.int32],
index_slice: Optional[slice],
is_last_chunk: bool,
aux_index: Optional[int] = None,
state_indices: Optional[List[int]] = None,
logical_page_positions: Optional[npt.NDArray[np.int32]] = None,
state_logical_page_positions: Optional[npt.NDArray[np.int32]] = None,
):
assert self.disaggregation_mode == DisaggregationMode.PREFILL
assert not is_last_chunk or (is_last_chunk and aux_index is not None)
if (
bootstrap_room not in self.request_status
or self.check_status(bootstrap_room) == KVPoll.Failed
):
logger.debug(
"Request with bootstrap_room=%s already failed", bootstrap_room
)
return
if bootstrap_room not in self.transfer_infos:
if self.check_status(bootstrap_room) == KVPoll.Success:
# Dummy rank for this request: it was already marked Success
# at handshake time, so there is nothing left to transfer.
return
# Non-Success room with no transfer destinations is an anomaly
# (decode peer torn down between handshake and this send, abort
# notification lost). Silently dropping the chunk used to wedge
# the request in WaitingForInput FOREVER — Success can never be
# set without the last chunk, and nothing else fails the room.
# Conclude it loudly instead; the scheduler's poll consensus
# (MIN-reduce, Failed=0) reaps it on every rank.
logger.warning(
"KV chunk for bootstrap_room=%s has no transfer destinations "
"(status=%s); failing the request instead of dropping the "
"chunk silently.",
bootstrap_room,
self.check_status(bootstrap_room),
)
self.record_failure(
bootstrap_room,
f"Request {bootstrap_room} lost its transfer destinations "
"before the KV chunk was submitted (decode peer gone?)",
)
self.update_status(bootstrap_room, KVPoll.Failed)
return
# NOTE(shangming): sharding according to the dst_infos to make sure
# requests with the same dst_sessions will be added into the same
# queue, which enables early abort with failed sessions.
dst_infos = self.transfer_infos[bootstrap_room].keys()
session_port_sum = sum(int(session.rsplit(":", 1)[1]) for session in dst_infos)
shard_idx = session_port_sum % len(self.transfer_queues)
self.transfer_queues[shard_idx].put(
TransferKVChunk(
room=bootstrap_room,
prefill_kv_indices=kv_indices,
index_slice=index_slice,
logical_page_positions=logical_page_positions,
state_logical_page_positions=state_logical_page_positions,
is_last_chunk=is_last_chunk,
prefill_aux_index=aux_index,
state_indices=state_indices,
)
)
def get_session_id(self):
return self.engine.get_session_id()
def _handle_node_failure(self, failed_bootstrap_addr):
with self.connection_lock:
keys_to_remove = [
k for k in self.connection_pool if k.startswith(failed_bootstrap_addr)
]
for k in keys_to_remove:
del self.connection_pool[k]
possible_affected_rooms = self.addr_to_rooms_tracker.get(
failed_bootstrap_addr, []
)
self.prefill_info_table.pop(failed_bootstrap_addr, None)
self.addr_to_rooms_tracker.pop(failed_bootstrap_addr, None)
# Report the requests associated with the failed bootstrap addr and mark their status as KVPoll.Failed
affected_rooms = []
for room in possible_affected_rooms:
if (
room in self.request_status
and self.check_status(room) != KVPoll.Success
):
self.record_failure(
room,
f"Losing connection with prefill instance (bootstrap_addr: {failed_bootstrap_addr})",
)
self.update_status(room, KVPoll.Failed)
affected_rooms.append(room)
logger.error(
f"Losing connection with prefill instance (bootstrap_addr: {failed_bootstrap_addr}), {len(affected_rooms)} requests affected"
)
class MooncakeKVSender(CommonKVSender):
def __init__(
self,
mgr: MooncakeKVManager,
bootstrap_addr: str,
bootstrap_room: int,
dest_tp_ranks: List[int],
pp_rank: int,
):
super().__init__(mgr, bootstrap_addr, bootstrap_room, dest_tp_ranks, pp_rank)
self.conclude_state = None
self.init_time = time.time()
def send(
self,
kv_indices: npt.NDArray[np.int32],
state_indices: Optional[List[int]] = None,
):
index_slice = slice(self.curr_idx, self.curr_idx + len(kv_indices))
self.curr_idx += len(kv_indices)
is_last_chunk = self.curr_idx == self.num_kv_indices
logical_page_positions = None
state_logical_page_positions = None
orig_kv_indices = None
orig_state_indices = None
if self.kv_mgr.server_args.enable_nsa_prefill_cp_shared_kv:
from sglang.srt.disaggregation.utils import filter_kv_pages_for_cp_shared_kv
from sglang.srt.mem_cache.cp_shared_kv_layout import CpSharedKVLayout
chunk_page_start = index_slice.start
orig_kv_indices = np.asarray(kv_indices, dtype=np.int32).copy()
if state_indices is not None:
orig_state_indices = np.asarray(state_indices, dtype=np.int32).copy()
layout = CpSharedKVLayout(
page_size=self.kv_mgr.kv_args.page_size,
cp_size=self.kv_mgr.attn_cp_size,
cp_rank=self.kv_mgr.attn_cp_rank,
)
kv_indices, logical_page_positions = filter_kv_pages_for_cp_shared_kv(
layout=layout,
logical_pages=kv_indices,
chunk_page_start=index_slice.start,
)
if state_indices is not None:
state_indices, state_logical_page_positions = (
filter_kv_pages_for_cp_shared_kv(
layout=layout,
logical_pages=state_indices,
chunk_page_start=0,
)
)
index_slice = None
if envs.SGLANG_DEBUG_CP_SHARED_KV.get() or envs.SGLANG_CP_TRANSFER_LOG.get():
_cp_shared_debug_log(
"sender_filter",
"sender filter cp_rank=%s room=%s page_start=%s orig_kv_pages=%s "
"filtered_kv_pages=%s kv_positions=%s orig_state_pages=%s "
"filtered_state_pages=%s state_positions=%s is_last=%s",
self.kv_mgr.attn_cp_rank,
self.bootstrap_room,
chunk_page_start,
_np_summary(orig_kv_indices),
_np_summary(kv_indices),
_np_summary(logical_page_positions),
_np_summary(orig_state_indices),
_np_summary(state_indices),
_np_summary(state_logical_page_positions),
is_last_chunk,
)
_cp_draft_shared_kv_debug(
"sender_filter cp_rank=%s room=%s page_start=%s orig_kv_pages=%s "
"filtered_kv_pages=%s kv_positions=%s orig_state_pages=%s "
"filtered_state_pages=%s state_positions=%s is_last=%s draft_bufs=%s",
self.kv_mgr.attn_cp_rank,
self.bootstrap_room,
chunk_page_start,
_np_summary(orig_kv_indices),
_np_summary(kv_indices),
_np_summary(logical_page_positions),
_np_summary(orig_state_indices),
_np_summary(state_indices),
_np_summary(state_logical_page_positions),
is_last_chunk,
getattr(self.kv_mgr.kv_args, "draft_kv_buffer_count", None),
)
# Special handling for cp
elif self.kv_mgr.enable_all_cp_ranks_for_transfer:
kv_indices, index_slice = filter_kv_indices_for_cp_rank(
self.kv_mgr,
kv_indices,
index_slice,
)
elif self.kv_mgr.is_dummy_cp_rank:
if not is_last_chunk:
return
else:
self.kv_mgr.update_status(self.bootstrap_room, KVPoll.Success)
return
if not is_last_chunk:
self.kv_mgr.add_transfer_request(
self.bootstrap_room,
kv_indices,
index_slice,
False,
logical_page_positions=logical_page_positions,
state_logical_page_positions=state_logical_page_positions,
)
else:
self.kv_mgr.add_transfer_request(
self.bootstrap_room,
kv_indices,
index_slice,
True,
aux_index=self.aux_index,
state_indices=state_indices,
logical_page_positions=logical_page_positions,
state_logical_page_positions=state_logical_page_positions,
)
# Record the actually-sent (post CP shared-KV filter) indices for accurate
# transfer metrics. Ported from upstream sgl-project/sglang #24416.
self._record_transfer_indices(kv_indices, state_indices)
def poll(self) -> KVPoll:
if self.conclude_state is None:
status = self.kv_mgr.check_status(self.bootstrap_room)
if status in (KVPoll.Success, KVPoll.Failed):
self.conclude_state = status
elif status == KVPoll.Bootstrapping:
if self.init_time is not None:
now = time.time()
elapsed = now - self.init_time
if elapsed >= self.kv_mgr.bootstrap_timeout:
logger.warning_once(
"Some requests timed out when bootstrapping, "
"which means prefill instances fail to receive the KV indices from the decode instance of this request. "
"If a greater mean TTFT is acceptable, you can 'export SGLANG_DISAGGREGATION_BOOTSTRAP_TIMEOUT=600' (10 minutes) to relax the timeout condition. "
)
self.kv_mgr.record_failure(
self.bootstrap_room,
f"Request {self.bootstrap_room} timed out after {elapsed:.1f}s in KVPoll.Bootstrapping",
)
self.conclude_state = KVPoll.Failed
return KVPoll.Failed
return status
else:
return self.conclude_state
def clear(self) -> None:
if self.bootstrap_room in self.kv_mgr.request_status:
self.kv_mgr.request_status.pop(self.bootstrap_room)
def failure_exception(self):
# Explicitly set the status to failure since this request has failed in another rank
if self.conclude_state is None:
self.conclude_state = KVPoll.Failed
self.clear()
with self.kv_mgr.failure_lock:
failure_reason = self.kv_mgr.failure_records.pop(
self.bootstrap_room, "Failed due to an unknown reason from another rank"
)
raise KVTransferError(self.bootstrap_room, failure_reason)
def abort(self):
self.kv_mgr.record_failure(
self.bootstrap_room,
"Aborted by AbortReq.",
)
# Mark the manager status Failed (not only the local conclude_state) so the
# transfer worker and other pollers observe the abort. Port of upstream
# sgl-project/sglang #24522.
self.kv_mgr.update_status(self.bootstrap_room, KVPoll.Failed)
# Explicitly set the status to failure since this request has been aborted
self.conclude_state = KVPoll.Failed
class MooncakeKVReceiver(CommonKVReceiver):
def __init__(
self,
mgr: MooncakeKVManager,
bootstrap_addr: str,
bootstrap_room: Optional[int] = None,
prefill_dp_rank: Optional[int] = None,
):
self.session_id = mgr.get_session_id()
self.conclude_state = None
self.init_time = None
self.abort_notified = False
super().__init__(mgr, bootstrap_addr, bootstrap_room, prefill_dp_rank)
self.kv_mgr.addr_to_rooms_tracker[self.bootstrap_addr].add(self.bootstrap_room)
self.kv_mgr.update_status(self.bootstrap_room, KVPoll.WaitingForInput)
def _register_kv_args(self):
for bootstrap_info in self.bootstrap_infos:
packed_kv_data_ptrs = b"".join(
struct.pack("Q", ptr) for ptr in self.kv_mgr.kv_args.kv_data_ptrs
)
packed_aux_data_ptrs = b"".join(
struct.pack("Q", ptr) for ptr in self.kv_mgr.kv_args.aux_data_ptrs
)
packed_state_data_ptrs = b"".join(
struct.pack("Q", ptr) for ptr in self.kv_mgr.kv_args.state_data_ptrs
)
# Pack state_item_lens and state_dim_per_tensor for mamba state slice transfer
packed_state_item_lens = b"".join(
struct.pack("I", item_len)
for item_len in self.kv_mgr.kv_args.state_item_lens
)
state_dim_per_tensor = getattr(
self.kv_mgr.kv_args, "state_dim_per_tensor", []
)
packed_state_dim_per_tensor = b"".join(
struct.pack("I", dim) for dim in state_dim_per_tensor
)
packed_state_layer_ids = b"".join(
struct.pack("i", int(layer_id))
for layer_id in getattr(self.kv_mgr.kv_args, "state_layer_ids", [])
)
# Note(shangming): No need to add pp rank here since decode pp size should be equal to prefill pp size or 1
tp_rank = self.kv_mgr.kv_args.engine_rank
kv_item_len = self.kv_mgr.kv_args.kv_item_lens[0]
dst_tp_rank = str(tp_rank).encode("ascii")
dst_attn_tp_size = str(self.kv_mgr.attn_tp_size).encode("ascii")
dst_kv_item_len = str(kv_item_len).encode("ascii")
_cp_draft_shared_kv_debug(
"decode_register_kv_args cp_rank=%s room=%s session=%s "
"kv_bufs=%s aux_bufs=%s state_type=%s state_bufs=%s "
"state_item_lens=%s draft_start=%s draft_count=%s "
"draft_state_type=%s draft_state_bufs=%s",
self.kv_mgr.attn_cp_rank,
self.bootstrap_room,
self.session_id,
len(self.kv_mgr.kv_args.kv_data_ptrs),
len(self.kv_mgr.kv_args.aux_data_ptrs),
getattr(self.kv_mgr.kv_args, "state_type", None),
len(self.kv_mgr.kv_args.state_data_ptrs),
_np_summary(self.kv_mgr.kv_args.state_item_lens),
getattr(self.kv_mgr.kv_args, "draft_kv_buffer_start", None),
getattr(self.kv_mgr.kv_args, "draft_kv_buffer_count", None),
getattr(self.kv_mgr.kv_args, "draft_state_type", None),
getattr(self.kv_mgr.kv_args, "draft_state_buffer_count", None),
)
sock, lock = self._connect_to_bootstrap_server(bootstrap_info)
with lock:
sock.send_multipart(
[
"None".encode("ascii"),
self.kv_mgr.local_ip.encode("ascii"),
str(self.kv_mgr.rank_port).encode("ascii"),
self.session_id.encode("ascii"),
packed_kv_data_ptrs,
packed_aux_data_ptrs,
packed_state_data_ptrs,
dst_tp_rank,
dst_attn_tp_size,
dst_kv_item_len,
packed_state_item_lens,
packed_state_dim_per_tensor,
packed_state_layer_ids,
]
)
def init(
self,
kv_indices: npt.NDArray[np.int32],
aux_index: Optional[int] = None,
state_indices: Optional[List[int]] = None,
):
if self.bootstrap_infos is None:
self.kv_mgr.record_failure(
self.bootstrap_room,
f"Could not fetch prefill parallel info from bootstrap_addr: {self.bootstrap_addr}",
)
self.kv_mgr.update_status(self.bootstrap_room, KVPoll.Failed)
return
for bootstrap_info in self.bootstrap_infos:
sock, lock = self._connect_to_bootstrap_server(bootstrap_info)
is_dummy = bootstrap_info["is_dummy"]
with lock:
sock.send_multipart(
[
str(self.bootstrap_room).encode("ascii"),
self.kv_mgr.local_ip.encode("ascii"),
str(self.kv_mgr.rank_port).encode("ascii"),
self.session_id.encode("ascii"),
kv_indices.tobytes() if not is_dummy else b"",
str(aux_index).encode("ascii") if not is_dummy else b"",
(
np.array(
state_indices,
dtype=np.int32,
).tobytes()
if not is_dummy and state_indices is not None
else b""
),
str(self.required_dst_info_num).encode("ascii"),
]
)
self.init_time = time.time()
def poll(self) -> KVPoll:
if self.conclude_state is None:
status = self.kv_mgr.check_status(self.bootstrap_room)
if status in (KVPoll.Success, KVPoll.Failed):
self.conclude_state = status
elif status == KVPoll.WaitingForInput:
if self.init_time is not None:
now = time.time()
elapsed = now - self.init_time
if elapsed >= self.kv_mgr.waiting_timeout:
logger.warning_once(
"Some requests fail to receive KV Cache transfer done signal after bootstrapping. "
"If a greater mean TTFT is acceptable, you can 'export SGLANG_DISAGGREGATION_WAITING_TIMEOUT=600' (10 minutes) to relax the timeout condition. "
)
self.kv_mgr.record_failure(
self.bootstrap_room,
f"Request {self.bootstrap_room} timed out after {elapsed:.1f}s in KVPoll.WaitingForInput",
)
# Tell prefill peers to stop transferring into our pages.
self._send_abort_notification()
self.conclude_state = KVPoll.Failed
return KVPoll.Failed
return status
else:
return self.conclude_state
def clear(self) -> None:
if self.bootstrap_room in self.kv_mgr.request_status:
self.kv_mgr.request_status.pop(self.bootstrap_room)
if self.bootstrap_room in self.kv_mgr.required_prefill_response_num_table:
self.kv_mgr.required_prefill_response_num_table.pop(self.bootstrap_room)
if self.bootstrap_room in self.kv_mgr.prefill_response_tracker:
self.kv_mgr.prefill_response_tracker.pop(self.bootstrap_room)
def failure_exception(self):
# Explicitly set the status to failure since this request has failed in another rank
if self.conclude_state is None:
self.conclude_state = KVPoll.Failed
self.clear()
with self.kv_mgr.failure_lock:
failure_reason = self.kv_mgr.failure_records.pop(
self.bootstrap_room, "Failed due to an unknown reason from another rank"
)
raise KVTransferError(self.bootstrap_room, failure_reason)
def _send_abort_notification(self):
# Notify every prefill peer that this room is aborting, so the prefill stops
# RDMA-writing into KV pages this decode is about to free/reuse. Without this,
# the prefill never learns of a decode-initiated abort (its request_status is
# per-process) and the worker's skip-Failed guard never fires. Port of upstream
# sgl-project/sglang #27372 (decode->prefill half). Sent at most once.
if self.abort_notified:
return
bootstrap_infos = getattr(self, "bootstrap_infos", None)
if not bootstrap_infos:
return
self.abort_notified = True
for bootstrap_info in bootstrap_infos:
try:
sock, lock = self._connect_to_bootstrap_server(bootstrap_info)
with lock:
sock.send_multipart(
[
b"ABORT",
str(self.bootstrap_room).encode("ascii"),
self.kv_mgr.local_ip.encode("ascii"),
str(self.kv_mgr.rank_port).encode("ascii"),
]
)
except Exception as e:
logger.debug(
f"Failed to send ABORT for room {self.bootstrap_room}: {e}"
)
def abort(self):
self.kv_mgr.record_failure(
self.bootstrap_room,
"Aborted by AbortReq.",
)
# Mark the manager status Failed (not only the local conclude_state) so the
# transfer worker and other pollers observe the abort. Port of upstream
# sgl-project/sglang #24522.
self.kv_mgr.update_status(self.bootstrap_room, KVPoll.Failed)
# Tell the prefill peers to stop transferring into our (soon-freed) pages.
self._send_abort_notification()
# Explicitly set the status to failure since this request has been aborted
self.conclude_state = KVPoll.Failed
class MooncakeKVBootstrapServer(CommonKVBootstrapServer):
pass
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