fix(v1): freeze offline multiprocess front-end heap (#48229)

[aryanyadav0402]

fix(v1): freeze offline multiprocess front-end heap and unfreeze on teardown (#48229)

Summary

In multiprocess mode the offline LLM / LLMEngine front-end process (the one that runs step()) is never handed to gc.freeze(), even though every comparable long-lived heap in vLLM already is:

• the online API server freezes its front-end heap in the serve lifespan (entrypoints/serve/utils/server_utils.py),
• the EngineCore child freezes its own heap at the end of __init__ (v1/engine/core.py),
• the GPU worker freezes after warmup (v1/worker/gpu_worker.py).

Only the offline multiprocess front-end was left out. This PR closes that gap: LLMEngine.__init__ calls freeze_gc_heap() at the end of construction when multiprocess_mode is set, and — because offline callers can build and destroy many LLMs in one long-lived process — pairs it with a deterministic gc.unfreeze() on explicit teardown.

Reference: #48229.

Motivation and honest framing

This is a consistency + insurance change, not a fix for the original sporadic 0.7–2 s step stall reported in #48229. That stall did not reproduce on fresh hosts, and I am deliberately not claiming it does. What is real and measurable is oldest-generation GC pressure in the front-end process:

• Reporter @arjmandi (thanks for the investigation and for OK'ing citing it) measured driver-side gen-2 collection time growing from ~23 ms to ~422 ms on their H100 over a long-lived run, silenced by freezing the driver heap.
• On the H100 verification box (vLLM 0.25.0), a full front-end gen-2 collection over ~631,928 tracked objects takes ~379 ms. After freeze_gc_heap() that startup heap is out of the cyclic collector's reach, so those objects no longer contribute to every subsequent oldest-gen pause.

The offline front-end is the process that runs step(), so this is exactly where such a pause matters. Matching the online server / EngineCore behavior here is a strict, low-risk consistency improvement even in the absence of the original stall.

Not a duplicate

git grep and gh pr list -R vllm-project/vllm --state open --search "freeze_gc_heap" (and --search "48229 in:body") return no open PR touching freeze_gc_heap or referencing #48229. On main today v1/engine/llm_engine.py has no import gc, no gc_utils import, and no freeze/unfreeze anywhere — this front-end freeze does not exist yet, so there is nothing to collide with.

Design: why unfreeze is an explicit teardown, not __del__/finalizer

freeze_gc_heap() → gc.freeze() moves all currently tracked objects (including self, its EngineCoreClient, the config graph, and the outer LLM) into the permanent generation, which the cyclic collector never scans again. Frozen objects are still freed by reference counting, but not by the cyclic collector.

Consequence: if any frozen object sits in a reference cycle, del llm will not drive its refcount to zero, and the collector that would normally break the cycle skips it because it is frozen. So a gc.unfreeze() hung off LLMEngine.__del__, or off a weakref.finalize gated on collecting the frozen LLMEngine/engine_core, would not fire on del llm in that case — each new instance would re-freeze and strand the prior graph until interpreter exit. That is the precise leak @arjmandi asked us to avoid, and a finalizer-on-self design would appear to work while silently failing.

The only trigger that fires reliably and promptly for a frozen-and-possibly-cyclic self is a direct method call. This PR therefore mirrors the sanctioned EngineCore.__init__ (freeze) / EngineCore.shutdown() (gc.unfreeze()) precedent:

• LLMEngine.shutdown() — new explicit teardown: unfreezes (guarded by a _frozen_gc_heap flag so in-process mode is a pure no-op and only the multiprocess path that actually froze thaws) and delegates to engine_core.shutdown() (idempotent for the SyncMPClient), so it both releases the frozen heap and terminates the child EngineCore process. Safe to call more than once.
• LLM.shutdown() + context manager (__enter__/__exit__) — the offline entrypoint had no explicit teardown at all; this gives callers a deterministic path: with LLM(...) as llm: or llm.shutdown().
• Backstop weakref.finalize(self, gc.unfreeze) — the callback holds no reference to self, so it never pins the frozen graph. It fires per-instance on del llm in the common acyclic case, and at worst runs at interpreter exit via weakref.finalize's atexit hook. shutdown() detaches it to avoid a redundant global unfreeze.

Deliberately no LLM.__del__: it would route engine_core.shutdown() onto in-process del (changing unrelated in-process semantics) and would not fire for a frozen-cyclic LLM anyway.

To route the existing test suite's offline teardown through the unfreeze, tests/conftest.py now calls self.llm.llm_engine.shutdown(timeout=...) instead of ...engine_core.shutdown(timeout=...). For in-process runs this calls the identical engine_core.shutdown(timeout) (no behavior change); for multiprocess it additionally unfreezes between sequential models.

Testing

Regression test added to tests/v1/engine/test_llm_engine.py asserting both freeze on build and unfreeze on teardown (GPU CI lane — requires a real engine build):

def test_offline_multiprocess_frontend_heap_freeze_lifecycle(...):
    before = gc.get_freeze_count()
    with LLM(MODEL, ..., enforce_eager=True):
        frozen = gc.get_freeze_count()
        assert frozen > before
    assert gc.get_freeze_count() < frozen

Verified on 4× H100 NVL (driver 595.71.05), precompiled editable build of this
branch (VLLM_USE_PRECOMPILED=1), multiprocess (VLLM_ENABLE_V1_MULTIPROCESSING=1),
facebook/opt-125m:

• With the patch: PASS.
• Negative control (freeze_gc_heap() disabled in-place, re-run, then restored):
  FAIL with assert frozen > before → assert 375 > 375 — the freeze count
  does not move without the patch, confirming the test genuinely exercises the
  change and is not vacuous.
• Lint: pre-commit on the changed files — all hooks passed, no reformatting.

Magnitude (earlier freeze-only round, same opt-125m, vLLM 0.25.0, H100):
gc.get_freeze_count() jumped 375 → 643,160 after build, and a full
front-end gen-2 collection over ~631,928 tracked objects took ~379 ms —
that startup heap is out of the cyclic collector's reach after freeze_gc_heap().

The final unfreeze assertion runs after __exit__ → shutdown() → synchronous
gc.unfreeze(), so it never depends on del+GC timing and is not flaky. It
requires a GPU to build the engine, so it lands in the GPU CI lane. Not asserted
(stated for honesty): bare-del llm unfreeze on a cyclic graph cannot be
tested deterministically — it resolves only at interpreter exit — so it is
intentionally left uncovered.

Caveats

• Deterministic unfreeze requires explicit teardown (llm.shutdown() or with LLM(...)). Plain del llm unfreezes per-instance only when the front-end graph is acyclic (the backstop finalizer fires on collection); if the graph is cyclic, del llm degrades to an unfreeze at interpreter exit. This is a fundamental CPython constraint of gc.freeze(), not fixable by any GC-triggered hook, and is never worse than not unfreezing at all.
• Single-instance / one-shot processes (the common offline case) need no unfreeze — the process exits and the OS reclaims everything, exactly like the online-server precedent that freezes and never unfreezes. The teardown machinery only matters for repeated create/destroy in one long-lived process.
• gc.unfreeze() is process-global (same coarse semantics as EngineCore.shutdown() / gpu_worker.shutdown()): tearing down one of several coexisting offline LLMs thaws the others' frozen startup heaps — a loss of the pause optimization, not a correctness issue. Concurrent offline LLMs are rare.

Out of scope

The separate offline teardown issue #48620 is not addressed here.

Credits and disclosure

• Co-developed with reporter @arjmandi, whose driver-side gen-2 measurements (23 → 422 ms on H100) and testing motivated and validated this change.
• AI assistance disclosure: this change was developed with AI assistance (analysis, drafting, and review). All design decisions, the GC-semantics reasoning above, and the H100 test results were reviewed and verified by a human before submission.

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