Gahow Wang
ac6534c3ff
- Delete unreachable best_needs_push block in _handle_combined and the four orphaned helpers (_handle_cached_prefill_offload, _handle_direct_read_offload, _query_bootstrap_hit, _get_bootstrap_client). Their only caller was the retired PUSH gate; see REPORT §3.9 errata for the rejected experiments (cc6e562,4c583f2). - Extract pick_instance_unified_hybrid as a pure function returning (chosen, idx, decision_dict). The decision dict carries the review #7 breakdown fields (decision, affinity_idx/chosen_idx, cache_hit/ratio, avg_num_requests, fallback_score, tie_break_used). - Add LMetric-fallback tie-breaker (primary score, then new_uncached, num_requests, round-robin) so new sessions don't all pin to inst 0 when BS=0 across the board. - Drop the lmetric-policy affinity write so --policy lmetric stays affinity-free per review #3. - Mark --max-offload-inflight / --offload-mode / --cache-gate-ratio / --decode-iteration-s as [DEPRECATED] in --help; flags remain accepted so scripts/bench.sh and legacy launchers don't break. - Revert uncommitted overload_factor 2.0->1.5 default; H7 sweep already rejected this knob (within noise). Future sweeps should go via CLI. Tests: add 6 hybrid-policy tests in tests/test_proxy_pick.py covering affinity-hit, overload break, low-cache fallback, tie-break rotation, lmetric purity, and breakdown field shape. 19/19 pass. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
731 lines
29 KiB
Python
731 lines
29 KiB
Python
"""Unified cache-aware + token-level load-balanced global scheduler.
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Supports two modes:
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--combined URL [URL ...]: PD co-located instances (normal vLLM, no KV transfer)
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--prefill URL BP --decode URL: PD disaggregated instances (Mooncake KV transfer)
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Routing policies (--policy):
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linear (default): score = ongoing_tokens - ALPHA * cache_hit_tokens
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lmetric: score = P_tokens * BS (LMetric, OSDI'26)
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P_tokens = pending_prefill_tokens + new_uncached_tokens
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BS = num_requests (waiting + running)
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Session affinity: multi-turn sessions stick to same instance (all policies).
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"""
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import argparse
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import asyncio
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import json
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import os
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import time as _time
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import urllib.parse
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import uuid
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from collections import OrderedDict
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from contextlib import asynccontextmanager
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from dataclasses import dataclass
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import httpx
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MAX_STREAM_RETRIES = 3
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RETRY_DELAY_S = 0.5
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import uvicorn
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from fastapi import FastAPI, HTTPException, Request
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from fastapi.responses import StreamingResponse
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BLOCK_SIZE = 512
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CACHE_HIT_ALPHA = 1.0
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@dataclass
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class Settings:
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"""Runtime-tunable knobs. Populated from argparse in __main__.
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All routing/offload code reads from the SETTINGS singleton so that
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CLI overrides survive even when the module is imported as a library
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(e.g. by tests/) and __main__ does not run.
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"""
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prefill_throughput: float = 7000.0 # tokens/s per GPU (measured on H20)
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rdma_overhead_s: float = 0.1 # RDMA PUSH overhead (~10-50ms measured)
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cache_capacity_blocks: int = 200000 # per-instance LRU cap on shadow cached_blocks
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heavy_threshold: int = 20000
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overload_factor: float = 2.0
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max_offload_inflight: int = 4
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cache_gate_ratio: float = 0.0
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decode_iteration_s: float = 0.05 # per-request decode iteration cost (H20)
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SETTINGS = Settings()
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class InstanceState:
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def __init__(self, url: str, bootstrap_port: int | None = None):
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self.url = url
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self.bootstrap_port = bootstrap_port
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self.client = httpx.AsyncClient(
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timeout=None, base_url=url,
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limits=httpx.Limits(max_connections=None, max_keepalive_connections=None),
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)
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self.ongoing_tokens = 0
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self.ongoing_decode_tokens = 0 # subset: tokens in decode phase
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self.pending_prefill_tokens = 0 # tokens for requests still in prefill
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self.num_requests = 0 # total in-flight requests (waiting + running)
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self.active_p_offloads = 0 # number of HEAVY prefills this instance is doing for others
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self.engine_id: dict[int, str] = {}
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self.dp_size = 1
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# OrderedDict acts as an LRU keyed by block hash; value is unused.
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self.cached_blocks: OrderedDict[int, None] = OrderedDict()
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def estimate_cache_hit(self, token_ids: list[int] | None) -> int:
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if not token_ids or len(token_ids) < BLOCK_SIZE:
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return 0
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hit = 0
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for i in range(0, len(token_ids) - BLOCK_SIZE + 1, BLOCK_SIZE):
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bh = hash(tuple(token_ids[i:i + BLOCK_SIZE]))
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if bh in self.cached_blocks:
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self.cached_blocks.move_to_end(bh) # LRU touch on hit
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hit += BLOCK_SIZE
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else:
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break
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return hit
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def record_prefix(self, token_ids: list[int] | None):
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if not token_ids:
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return
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for i in range(0, len(token_ids) - BLOCK_SIZE + 1, BLOCK_SIZE):
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bh = hash(tuple(token_ids[i:i + BLOCK_SIZE]))
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if bh in self.cached_blocks:
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self.cached_blocks.move_to_end(bh)
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else:
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self.cached_blocks[bh] = None
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if len(self.cached_blocks) > SETTINGS.cache_capacity_blocks:
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self.cached_blocks.popitem(last=False)
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def _p_offload_penalty(inst: InstanceState) -> int:
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"""Penalty for PD-sep mode routing (legacy)."""
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if inst.active_p_offloads <= 0:
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return 0
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return inst.active_p_offloads * SETTINGS.heavy_threshold
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def pick_instance(instances: list[InstanceState], token_ids: list[int] | None,
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session_id: str | None, input_length: int,
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affinity: dict[str, int]) -> tuple[InstanceState, int]:
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"""Session-sticky with load-aware override.
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Turn 2+: use session affinity UNLESS pinned instance is overloaded
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or busy with P-role offloads, in which case pick least-loaded.
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Turn 1: pick instance with best score (load + cache combined).
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Instances doing P-role offloads get a large penalty to steer
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WARM/MEDIUM traffic away.
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"""
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avg_load = max(sum(i.ongoing_tokens for i in instances) / len(instances), 1.0)
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if session_id and session_id in affinity:
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idx = affinity[session_id]
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if idx < len(instances):
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inst = instances[idx]
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if (inst.ongoing_tokens <= avg_load * SETTINGS.overload_factor
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and inst.active_p_offloads == 0):
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return inst, idx
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best_idx, best_score = 0, float("inf")
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for i, inst in enumerate(instances):
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cache_hit = inst.estimate_cache_hit(token_ids)
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score = (inst.ongoing_tokens + _p_offload_penalty(inst)
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- CACHE_HIT_ALPHA * cache_hit)
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if score < best_score:
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best_score = score
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best_idx = i
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if session_id:
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affinity[session_id] = best_idx
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return instances[best_idx], best_idx
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def pick_instance_lmetric(instances: list[InstanceState], token_ids: list[int] | None,
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session_id: str | None, input_length: int,
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affinity: dict[str, int]) -> tuple[InstanceState, int]:
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"""LMetric routing: score = P_tokens × BS (OSDI'26).
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Pure per-request load-based routing, no session affinity (the
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session_id/affinity args are accepted for signature compatibility
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with pick_instance/pick_instance_unified_hybrid but ignored).
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P = pending_prefill_tokens + (input_length - cache_hit)
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BS = num_requests (current batch size)
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"""
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best_idx, best_score = 0, float("inf")
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for i, inst in enumerate(instances):
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cache_hit = inst.estimate_cache_hit(token_ids)
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new_prefill = max(0, input_length - cache_hit)
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p_tokens = inst.pending_prefill_tokens + new_prefill
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bs = inst.num_requests
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score = p_tokens * bs
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if score < best_score:
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best_score = score
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best_idx = i
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return instances[best_idx], best_idx
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_unified_fallback_rr_counter = 0
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def pick_instance_unified_hybrid(
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instances: list[InstanceState],
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token_ids: list[int] | None,
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session_id: str | None,
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input_length: int,
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affinity: dict[str, int],
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) -> tuple[InstanceState, int, dict]:
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"""Hybrid routing: high-cache affinity, else LMetric with tie-breaker.
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Affinity gate (both must hold to stick):
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- affinity instance cache_hit / input_length > 0.5
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- affinity.num_requests <= avg_num_requests * SETTINGS.overload_factor
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Fallback ordering (when affinity not used):
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primary: score = P_tokens * BS (LMetric)
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secondary: new_uncached_tokens (prefer instance with most cache)
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tertiary: num_requests (prefer least-loaded)
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quaternary: round-robin (avoid degenerate inst-0 pinning
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when BS=0 across the board)
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Returns (chosen, idx, decision_dict). decision_dict carries the
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review #7 breakdown fields so the caller can merge them verbatim.
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"""
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global _unified_fallback_rr_counter
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n = len(instances)
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avg_reqs = max(sum(i.num_requests for i in instances) / n, 1.0)
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decision: dict = {
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"decision": "lmetric_fallback",
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"affinity_idx": None,
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"chosen_idx": None,
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"affinity_cache_hit": None,
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"affinity_cache_ratio": None,
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"affinity_num_requests": None,
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"avg_num_requests": avg_reqs,
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"fallback_score": None,
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"tie_break_used": False,
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}
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if session_id and session_id in affinity:
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a_idx = affinity[session_id]
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if a_idx < n:
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a_inst = instances[a_idx]
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a_hit = a_inst.estimate_cache_hit(token_ids)
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a_ratio = a_hit / max(input_length, 1)
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decision["affinity_idx"] = a_idx
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decision["affinity_cache_hit"] = a_hit
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decision["affinity_cache_ratio"] = a_ratio
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decision["affinity_num_requests"] = a_inst.num_requests
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if (a_ratio > 0.5
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and a_inst.num_requests <= avg_reqs * SETTINGS.overload_factor):
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decision["decision"] = "affinity"
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decision["chosen_idx"] = a_idx
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return a_inst, a_idx, decision
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keys: list[tuple[int, int, int, int]] = []
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for i, inst in enumerate(instances):
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cache_hit = inst.estimate_cache_hit(token_ids)
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new_prefill = max(0, input_length - cache_hit)
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p_tokens = inst.pending_prefill_tokens + new_prefill
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bs = inst.num_requests
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score = p_tokens * bs
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keys.append((score, new_prefill, bs, i))
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best_triple = min(k[:3] for k in keys)
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tied = [k for k in keys if k[:3] == best_triple]
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if len(tied) > 1:
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decision["tie_break_used"] = True
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_unified_fallback_rr_counter += 1
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winner = tied[_unified_fallback_rr_counter % len(tied)]
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else:
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winner = tied[0]
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chosen_idx = winner[3]
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decision["fallback_score"] = winner[0]
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decision["chosen_idx"] = chosen_idx
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return instances[chosen_idx], chosen_idx, decision
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|
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def _extract_output_token_ids_from_sse(
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buffer: str,
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chunk: bytes,
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) -> tuple[str, list[int]]:
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"""Extract vLLM streaming token_ids while preserving the raw stream."""
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buffer += chunk.decode("utf-8", errors="ignore")
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complete = buffer.endswith("\n") or buffer.endswith("\r")
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lines = buffer.splitlines()
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if complete:
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buffer = ""
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elif lines:
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buffer = lines.pop()
|
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else:
|
||
return buffer, []
|
||
|
||
output_ids: list[int] = []
|
||
for line in lines:
|
||
line = line.strip()
|
||
if not line.startswith("data:"):
|
||
continue
|
||
data = line[5:].strip()
|
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if not data or data == "[DONE]":
|
||
continue
|
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try:
|
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payload = json.loads(data)
|
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except json.JSONDecodeError:
|
||
continue
|
||
choices = payload.get("choices", [])
|
||
for choice in choices:
|
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token_ids = choice.get("token_ids")
|
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if isinstance(token_ids, list):
|
||
output_ids.extend(
|
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int(t) for t in token_ids if isinstance(t, int)
|
||
)
|
||
return buffer, output_ids
|
||
|
||
|
||
def _realized_tokens(
|
||
prompt_token_ids: list[int] | None,
|
||
output_token_ids: list[int],
|
||
) -> list[int] | None:
|
||
if prompt_token_ids is None:
|
||
return None
|
||
if not output_token_ids:
|
||
return prompt_token_ids
|
||
return prompt_token_ids + output_token_ids
|
||
|
||
|
||
global_args = None
|
||
combined_instances: list[InstanceState] = []
|
||
prefill_instances: list[InstanceState] = []
|
||
decode_instances: list[InstanceState] = []
|
||
# Session affinity is namespace-isolated: combined-mode and pd-sep mode index
|
||
# different instance lists, so a shared dict could mis-route after a mode switch.
|
||
session_affinity_combined: dict[str, int] = {}
|
||
session_affinity_prefill: dict[str, int] = {}
|
||
# Backwards-compat alias used by /stats etc.
|
||
session_affinity = session_affinity_combined
|
||
is_pd_sep = False
|
||
_breakdown_log: list[dict] = []
|
||
|
||
|
||
async def init_prefill_bootstrap(instances: list[InstanceState], ready: asyncio.Event):
|
||
for inst in instances:
|
||
if inst.bootstrap_port is None:
|
||
continue
|
||
while True:
|
||
try:
|
||
await inst.client.get("/health")
|
||
except Exception:
|
||
await asyncio.sleep(1)
|
||
continue
|
||
parsed = urllib.parse.urlparse(str(inst.client.base_url))
|
||
url = f"http://{parsed.hostname}:{inst.bootstrap_port}/query"
|
||
resp = await inst.client.get(url)
|
||
resp.raise_for_status()
|
||
data = resp.json()
|
||
for dp_rank, dp_entry in data.items():
|
||
inst.engine_id[int(dp_rank)] = dp_entry["engine_id"]
|
||
inst.dp_size = len(data)
|
||
print(f"Inited {inst.url} engine_ids={inst.engine_id}")
|
||
break
|
||
ready.set()
|
||
|
||
|
||
async def _reconcile_loop():
|
||
"""Periodic safety net for shadow state.
|
||
|
||
StreamingResponse generators decrement load counters in their finally
|
||
block, but if a client disconnects before the body is consumed the
|
||
generator is never entered and the decrement is lost. Clamp negative
|
||
drift every minute so router scores stay sane. This does not replace
|
||
proper exact-state syncing with vLLM (see TODO.md item 6).
|
||
"""
|
||
while True:
|
||
try:
|
||
await asyncio.sleep(60)
|
||
except asyncio.CancelledError:
|
||
return
|
||
for inst in combined_instances + prefill_instances + decode_instances:
|
||
if inst.ongoing_tokens < 0:
|
||
inst.ongoing_tokens = 0
|
||
if inst.ongoing_decode_tokens < 0:
|
||
inst.ongoing_decode_tokens = 0
|
||
if inst.pending_prefill_tokens < 0:
|
||
inst.pending_prefill_tokens = 0
|
||
if inst.num_requests < 0:
|
||
inst.num_requests = 0
|
||
if inst.active_p_offloads < 0:
|
||
inst.active_p_offloads = 0
|
||
|
||
|
||
def _verify_vllm_patch():
|
||
"""Startup self-check for patches/0001-fix-kv-transfer-abort-race.patch.
|
||
|
||
The patch turns an `assert req_id in self.requests` into a soft warn so
|
||
that engines do not crash on the KV-transfer abort race (see REPORT
|
||
§3.x). If somebody upgrades vLLM without re-applying the patch, the
|
||
assert returns and elastic mode dies under load. Print a loud warning
|
||
so we catch the regression before the first HEAVY request.
|
||
"""
|
||
try:
|
||
import inspect
|
||
from vllm.v1.core.sched.scheduler import Scheduler
|
||
src = inspect.getsource(Scheduler)
|
||
if "assert req_id in self.requests" in src:
|
||
print("WARNING: vLLM scheduler still contains the unpatched "
|
||
"`assert req_id in self.requests` line; expect engine "
|
||
"death on KV-transfer abort race. Apply "
|
||
"patches/0001-fix-kv-transfer-abort-race.patch.")
|
||
else:
|
||
print("vLLM patch self-check: kv-transfer-abort assert is patched.")
|
||
except Exception as exc:
|
||
print(f"vLLM patch self-check skipped: {exc!r}")
|
||
|
||
|
||
@asynccontextmanager
|
||
async def lifespan(app: FastAPI):
|
||
global is_pd_sep
|
||
app.state.ready = asyncio.Event()
|
||
|
||
_verify_vllm_patch()
|
||
|
||
reconcile_task = asyncio.create_task(_reconcile_loop())
|
||
|
||
if global_args.combined:
|
||
is_pd_sep = False
|
||
bp_list = [int(p) for p in global_args.bootstrap_ports.split(",") if p.strip()] if global_args.bootstrap_ports else []
|
||
for i, url in enumerate(global_args.combined):
|
||
bp = bp_list[i] if i < len(bp_list) else None
|
||
combined_instances.append(InstanceState(url, bp))
|
||
|
||
# Bootstrap combined instances for offload (need engine_ids for KV transfer)
|
||
if global_args.offload and bp_list:
|
||
await init_prefill_bootstrap(combined_instances, app.state.ready)
|
||
else:
|
||
app.state.ready.set()
|
||
|
||
policy = getattr(global_args, 'policy', 'linear')
|
||
print(f"Combined mode: {len(combined_instances)} instances, policy={policy}, offload={'ON' if global_args.offload else 'OFF'}")
|
||
else:
|
||
is_pd_sep = True
|
||
for url, bp in global_args.prefill:
|
||
prefill_instances.append(InstanceState(url, bp))
|
||
for url in global_args.decode:
|
||
decode_instances.append(InstanceState(url))
|
||
await init_prefill_bootstrap(prefill_instances, app.state.ready)
|
||
print(f"PD-Sep mode: {len(prefill_instances)}P + {len(decode_instances)}D")
|
||
|
||
yield
|
||
reconcile_task.cancel()
|
||
try:
|
||
await reconcile_task
|
||
except asyncio.CancelledError:
|
||
pass
|
||
for inst in combined_instances + prefill_instances + decode_instances:
|
||
await inst.client.aclose()
|
||
|
||
|
||
app = FastAPI(lifespan=lifespan)
|
||
|
||
|
||
@app.post("/v1/completions")
|
||
async def handle_completions(request: Request):
|
||
return await _handle(request, "/v1/completions")
|
||
|
||
|
||
@app.post("/v1/chat/completions")
|
||
async def handle_chat(request: Request):
|
||
return await _handle(request, "/v1/chat/completions")
|
||
|
||
|
||
async def _handle(request: Request, api: str):
|
||
if not app.state.ready.is_set():
|
||
raise HTTPException(status_code=503, detail="Service Unavailable")
|
||
|
||
req_data = await request.json()
|
||
request_id = str(uuid.uuid4())
|
||
prompt = req_data.get("prompt")
|
||
token_ids = prompt if isinstance(prompt, list) else None
|
||
input_length = len(token_ids) if token_ids else 0
|
||
session_id = request.headers.get("X-Session-Id")
|
||
|
||
headers = {"X-Request-Id": request_id}
|
||
api_key = os.environ.get("OPENAI_API_KEY")
|
||
if api_key:
|
||
headers["Authorization"] = f"Bearer {api_key}"
|
||
|
||
if is_pd_sep:
|
||
return await _handle_pd_sep(api, req_data, request_id, token_ids,
|
||
input_length, session_id, headers)
|
||
else:
|
||
return await _handle_combined(api, req_data, token_ids,
|
||
input_length, session_id, headers)
|
||
|
||
|
||
async def _handle_local_request(api, req_data, headers, token_ids, input_length,
|
||
chosen: InstanceState, estimated_new: int,
|
||
breakdown: dict):
|
||
breakdown.setdefault("route_class", "LOCAL")
|
||
breakdown.setdefault("routed_to", chosen.url)
|
||
chosen.ongoing_tokens += input_length
|
||
chosen.pending_prefill_tokens += estimated_new
|
||
chosen.num_requests += 1
|
||
|
||
async def generate():
|
||
prefill_done = False
|
||
sse_buffer = ""
|
||
output_token_ids: list[int] = []
|
||
try:
|
||
for attempt in range(MAX_STREAM_RETRIES):
|
||
try:
|
||
async with chosen.client.stream("POST", api, json=req_data, headers=headers) as resp:
|
||
resp.raise_for_status()
|
||
async for chunk in resp.aiter_bytes():
|
||
sse_buffer, new_output_ids = _extract_output_token_ids_from_sse(
|
||
sse_buffer, chunk)
|
||
output_token_ids.extend(new_output_ids)
|
||
if not prefill_done:
|
||
chosen.pending_prefill_tokens -= estimated_new
|
||
chosen.ongoing_decode_tokens += input_length
|
||
breakdown["t_first_token"] = _time.monotonic()
|
||
prefill_done = True
|
||
yield chunk
|
||
chosen.record_prefix(
|
||
_realized_tokens(token_ids, output_token_ids))
|
||
break
|
||
except (httpx.ConnectError, httpx.RemoteProtocolError):
|
||
if prefill_done or attempt >= MAX_STREAM_RETRIES - 1:
|
||
raise
|
||
await asyncio.sleep(RETRY_DELAY_S)
|
||
finally:
|
||
if not prefill_done:
|
||
chosen.pending_prefill_tokens -= estimated_new
|
||
else:
|
||
chosen.ongoing_decode_tokens -= input_length
|
||
chosen.ongoing_tokens -= input_length
|
||
chosen.num_requests -= 1
|
||
breakdown["t_done"] = _time.monotonic()
|
||
_breakdown_log.append(breakdown)
|
||
|
||
return StreamingResponse(generate(), media_type="text/event-stream")
|
||
|
||
|
||
async def _handle_combined(api, req_data, token_ids, input_length, session_id, headers):
|
||
"""Route a /v1/* request among combined (PD-colocated) instances.
|
||
|
||
--policy options:
|
||
linear: cache_hit-aware load score + sticky session affinity.
|
||
lmetric: P_tokens * BS (LMetric, OSDI'26). No session affinity.
|
||
unified: hybrid — stick to affinity instance when cache_ratio > 0.5
|
||
and it is not overloaded; otherwise fall back to LMetric
|
||
with a multi-key tie-breaker.
|
||
|
||
PD-sep offload / PUSH migration is retired (see REPORT.md §3.9 and
|
||
commits 4c583f2 / cc6e562: relaxed-gate and forced-migration variants
|
||
both regressed E2E tail). Re-enabling requires a new transfer mechanism.
|
||
"""
|
||
policy = getattr(global_args, 'policy', 'linear')
|
||
breakdown: dict = {
|
||
"request_id": headers.get("X-Request-Id", ""),
|
||
"input_length": input_length,
|
||
"t_proxy_recv": _time.monotonic(),
|
||
"policy": policy,
|
||
}
|
||
|
||
if policy == "lmetric":
|
||
chosen, best_idx = pick_instance_lmetric(
|
||
combined_instances, token_ids, session_id, input_length,
|
||
session_affinity_combined)
|
||
elif policy == "unified":
|
||
chosen, best_idx, decision = pick_instance_unified_hybrid(
|
||
combined_instances, token_ids, session_id, input_length,
|
||
session_affinity_combined)
|
||
breakdown.update(decision)
|
||
if session_id:
|
||
session_affinity_combined[session_id] = best_idx
|
||
else: # linear (default)
|
||
chosen, best_idx = pick_instance(
|
||
combined_instances, token_ids, session_id, input_length,
|
||
session_affinity_combined)
|
||
|
||
cache_hit = chosen.estimate_cache_hit(token_ids)
|
||
estimated_new = max(0, input_length - cache_hit)
|
||
breakdown.update({
|
||
"cache_hit": cache_hit,
|
||
"estimated_new_tokens": estimated_new,
|
||
"route_class": "LOCAL",
|
||
"routed_to": chosen.url,
|
||
})
|
||
return await _handle_local_request(
|
||
api, req_data, headers, token_ids, input_length,
|
||
chosen, estimated_new, breakdown)
|
||
|
||
|
||
async def _handle_pd_sep(api, req_data, request_id, token_ids, input_length,
|
||
session_id, headers):
|
||
"""PD-Sep mode with per-stage breakdown profiling."""
|
||
breakdown = {
|
||
"request_id": request_id,
|
||
"input_length": input_length,
|
||
"t_proxy_recv": _time.monotonic(),
|
||
}
|
||
|
||
p_inst, _ = pick_instance(prefill_instances, token_ids, session_id,
|
||
input_length, session_affinity_prefill)
|
||
d_inst = min(decode_instances, key=lambda x: x.ongoing_tokens)
|
||
breakdown["p_inst"] = p_inst.url
|
||
breakdown["d_inst"] = d_inst.url
|
||
|
||
prefill_data = req_data.copy()
|
||
prefill_data["kv_transfer_params"] = {
|
||
"do_remote_decode": True, "do_remote_prefill": False,
|
||
"transfer_id": f"xfer-{request_id}",
|
||
}
|
||
prefill_data["stream"] = False
|
||
prefill_data["max_tokens"] = 1
|
||
prefill_data["min_tokens"] = 1
|
||
prefill_data.pop("max_completion_tokens", None)
|
||
prefill_data.pop("stream_options", None)
|
||
p_headers = {**headers, "X-data-parallel-rank": "0"}
|
||
|
||
p_inst.ongoing_tokens += input_length
|
||
breakdown["t_prefill_sent"] = _time.monotonic()
|
||
|
||
try:
|
||
resp = await p_inst.client.post(api, json=prefill_data, headers=p_headers)
|
||
breakdown["t_prefill_done"] = _time.monotonic()
|
||
resp.raise_for_status()
|
||
await resp.aclose()
|
||
p_inst.record_prefix(token_ids)
|
||
except Exception as e:
|
||
breakdown["t_prefill_done"] = _time.monotonic()
|
||
breakdown["prefill_error"] = True
|
||
_breakdown_log.append(breakdown)
|
||
raise HTTPException(status_code=502, detail=f"Prefill failed: {e}")
|
||
finally:
|
||
p_inst.ongoing_tokens -= input_length
|
||
|
||
# Send decode
|
||
d_inst.ongoing_tokens += input_length
|
||
parsed = urllib.parse.urlparse(str(p_inst.client.base_url))
|
||
bootstrap_addr = f"http://{parsed.hostname}:{p_inst.bootstrap_port}"
|
||
|
||
decode_data = req_data.copy()
|
||
decode_data["kv_transfer_params"] = {
|
||
"do_remote_decode": False, "do_remote_prefill": True,
|
||
"remote_bootstrap_addr": bootstrap_addr,
|
||
"remote_engine_id": p_inst.engine_id.get(0, ""),
|
||
"transfer_id": f"xfer-{request_id}",
|
||
}
|
||
|
||
breakdown["t_decode_sent"] = _time.monotonic()
|
||
|
||
async def generate():
|
||
first_token = True
|
||
sse_buffer = ""
|
||
output_token_ids: list[int] = []
|
||
try:
|
||
async with d_inst.client.stream("POST", api, json=decode_data, headers=headers) as resp:
|
||
resp.raise_for_status()
|
||
async for chunk in resp.aiter_bytes():
|
||
sse_buffer, new_output_ids = _extract_output_token_ids_from_sse(
|
||
sse_buffer, chunk)
|
||
output_token_ids.extend(new_output_ids)
|
||
if first_token:
|
||
breakdown["t_first_token"] = _time.monotonic()
|
||
first_token = False
|
||
yield chunk
|
||
d_inst.record_prefix(_realized_tokens(token_ids, output_token_ids))
|
||
finally:
|
||
breakdown["t_done"] = _time.monotonic()
|
||
d_inst.ongoing_tokens -= input_length
|
||
_breakdown_log.append(breakdown)
|
||
|
||
return StreamingResponse(generate(), media_type="application/json")
|
||
|
||
|
||
@app.get("/breakdown")
|
||
async def get_breakdown():
|
||
"""Return per-request breakdown data for analysis."""
|
||
return _breakdown_log
|
||
|
||
|
||
@app.get("/stats")
|
||
async def get_stats():
|
||
"""Return per-instance live state for debugging."""
|
||
instances = combined_instances or prefill_instances + decode_instances
|
||
return [{
|
||
"url": inst.url,
|
||
"role": "combined",
|
||
"ongoing_tokens": inst.ongoing_tokens,
|
||
"pending_prefill_tokens": inst.pending_prefill_tokens,
|
||
"ongoing_decode_tokens": inst.ongoing_decode_tokens,
|
||
"num_requests": inst.num_requests,
|
||
"active_p_offloads": inst.active_p_offloads,
|
||
"cached_blocks": len(inst.cached_blocks),
|
||
} for inst in instances]
|
||
|
||
|
||
def parse_args():
|
||
p = argparse.ArgumentParser(description="Unified cache-aware global scheduler")
|
||
p.add_argument("--port", type=int, default=8000)
|
||
p.add_argument("--host", type=str, default="0.0.0.0")
|
||
p.add_argument("--combined", nargs="+", help="Combined mode: list of instance URLs")
|
||
p.add_argument("--prefill", nargs="+", action="append", dest="prefill_raw",
|
||
help="PD-Sep prefill: URL [bootstrap_port]")
|
||
p.add_argument("--decode", nargs=1, action="append", dest="decode_raw",
|
||
help="PD-Sep decode: URL")
|
||
p.add_argument("--heavy-threshold", type=int, default=20000,
|
||
help="New tokens threshold for HEAVY classification (adaptive offload)")
|
||
p.add_argument("--offload", action="store_true",
|
||
help="Enable Mooncake KV offload for HEAVY requests (requires kv_both instances)")
|
||
p.add_argument("--bootstrap-ports", type=str, default="",
|
||
help="Comma-separated bootstrap ports for combined instances (for offload mode)")
|
||
p.add_argument("--policy", type=str, default="linear",
|
||
choices=["linear", "lmetric", "unified"],
|
||
help="Routing policy: linear (cache-aware), lmetric (P_tokens × BS), "
|
||
"or unified (hybrid affinity + LMetric fallback)")
|
||
p.add_argument("--overload-factor", type=float, default=2.0,
|
||
help="Break session affinity when instance load > factor * avg")
|
||
# The four flags below are accepted for bench.sh backward compatibility but
|
||
# have no effect after the PD-sep offload path was retired (REPORT §3.9,
|
||
# commits 4c583f2 / cc6e562). Removing them would break scripts/bench.sh and
|
||
# scripts/legacy/*.sh which still pass them through.
|
||
p.add_argument("--max-offload-inflight", type=int, default=4,
|
||
help="[DEPRECATED] PUSH offload retired; no effect")
|
||
p.add_argument("--offload-mode", type=str, default="cached_prefill",
|
||
choices=["direct_read", "cached_prefill"],
|
||
help="[DEPRECATED] PUSH offload retired; no effect")
|
||
p.add_argument("--cache-gate-ratio", type=float, default=0.0,
|
||
help="[DEPRECATED] PUSH offload retired; no effect")
|
||
p.add_argument("--decode-iteration-s", type=float, default=0.05,
|
||
help="[DEPRECATED] PUSH offload retired; no effect")
|
||
args = p.parse_args()
|
||
|
||
args.prefill = []
|
||
if args.prefill_raw:
|
||
for entry in args.prefill_raw:
|
||
url = entry[0]
|
||
bp = int(entry[1]) if len(entry) > 1 and entry[1].lower() != "none" else None
|
||
args.prefill.append((url, bp))
|
||
args.decode = [e[0] for e in (args.decode_raw or [])]
|
||
|
||
if not args.combined and not args.prefill:
|
||
p.error("Must specify either --combined or --prefill/--decode")
|
||
return args
|
||
|
||
|
||
if __name__ == "__main__":
|
||
global_args = parse_args()
|
||
SETTINGS.heavy_threshold = global_args.heavy_threshold
|
||
SETTINGS.overload_factor = global_args.overload_factor
|
||
SETTINGS.max_offload_inflight = global_args.max_offload_inflight
|
||
SETTINGS.cache_gate_ratio = global_args.cache_gate_ratio
|
||
SETTINGS.decode_iteration_s = getattr(global_args, 'decode_iteration_s', 0.05)
|
||
print("SETTINGS: throughput=%.0f rdma_overhead=%.2f offload=%s" % (
|
||
SETTINGS.prefill_throughput, SETTINGS.rdma_overhead_s,
|
||
getattr(global_args, 'offload', False)))
|
||
uvicorn.run(app, host=global_args.host, port=global_args.port)
|