[Core][RFC #34303] Add CuMemTagBackend for tag-selective offload on top of #44074

[terafin]

Purpose

This is a draft sibling extension to #44074, implementing the tag-based selective offload approach @AlanFokCo described in RFC #34303 comment 4689082496 on top of @matteso1's SleepModeBackend abstraction.

Dependencies

This PR depends on two prerequisites:

1. [Core] Pluggable sleep-mode backend abstraction (RFC #34303) #44074 ([Core] Pluggable sleep-mode backend abstraction) — provides the SleepModeBackend ABC + SleepModeBackendFactory we extend. Carried as the first commit on this branch (Nils Matteson) for review visibility; will drop out of this PR's diff once [Core] Pluggable sleep-mode backend abstraction (RFC #34303) #44074 lands upstream.
2. [v2 of #45506] EngineArgs CLI plumbing for --sleep-mode-backend #45513 ([Core] EngineArgs CLI plumbing for --sleep-mode-backend) — owns the public API surface: declares ModelConfig.sleep_mode_backend and ModelConfig.sleep_mode_backend_options plus the corresponding CLI flags. This PR's runtime code (SleepModeBackendFactory.create_backend(model_config) at vllm/device_allocator/sleep_mode_backend.py) reads those fields off the live ModelConfig.

Dependency direction inverted from the original filing: was #45513 depending on this PR, now #45398 depends on #45513. The CLI surface lands first; this implementation lands second — the natural order for a public API change. With the field declarations relocated, this PR can be reviewed against the implementation it actually adds (CuMemTagBackend in vllm/device_allocator/sleep_mode_backend.py) without bundling the schema declarations.

What this adds

File	Change
vllm/device_allocator/sleep_mode_backend.py	+ CuMemTagBackend class, + supports_selective_offload() base capability, + cumem_tag factory registration
tests/test_sleep_mode_backend.py	+ tests covering tag-based dispatch, capability-flag introspection, factory-options round-trip, and the default-matches-CuMemBackend invariant
vllm/v1/executor/abstract.py, vllm/v1/worker/gpu_worker.py	+ tags= parameter threaded through Executor.sleep / GPUWorker.sleep so per-call tag overrides reach the backend

What CuMemTagBackend does

Subclasses CuMemBackend and exposes the existing CuMemAllocator.sleep(offload_tags=...) / .wake_up(tags=...) primitives as a first-class backend API:

backend = CuMemTagBackend()
backend.suspend(level=1)                                # = CuMemBackend behavior (offload "weights" only)
backend.suspend(level=1, tags=("weights", "kv_cache"))  # explicit: offload BOTH
backend.resume(tags=["weights"])                        # restore weights only, keep kv_cache offloaded

Tag-resolution precedence (most to least specific):

1. tags= keyword argument on the call
2. suspend_tags= constructor argument
3. Level-based default (DEFAULT_SUSPEND_TAGS_L1 = ("weights",), DEFAULT_SUSPEND_TAGS_L2 = ())

The default-arguments path is identical to CuMemBackend.suspend()/resume() — asserted by test_default_suspend_tags_match_cumem_backend_level1. Adopting this backend with default config is a no-op.

resume() is inherited unchanged from CuMemBackend: it already forwards tags to allocator.wake_up(tags), which is the selective-restore primitive the design needs.

Why this is useful (use case)

Multi-model GPU sharing: weights, KV cache, and compiled artifacts have independent lifecycles. Switching between models on a shared GPU benefits from offloading only what conflicts (weights of the swapped-out model) while keeping reusable pieces hot.

Concrete data from the @AlanFokCo field report on RFC #34303 (Alibaba Cloud ACK production, A10 / A100 nodes):

Model pair	TP	Switch time
Qwen3-0.6B ↔ Qwen2.5-0.5B	1	1.1s
Qwen3-8B ↔ Qwen-7B-Chat	8	853ms
Qwen3-32B ↔ Qwen2.5-32B	8	2.0s
Dense ↔ MoE (32B)	4	1.4s

Baseline (full engine teardown + rebuild) for the same models: 60–100s.

The new capability flag

@classmethod
def supports_selective_offload(cls) -> bool: ...

Lives on the SleepModeBackend base class, defaults to False. CuMemTagBackend overrides to True. Lets the executor and /health introspect whether explicit per-tag lifecycle is available, parallel to #44074's preserves_nccl / preserves_compiled_artifacts / preserves_graphs_with_nccl / supports_durable_storage flags. Backends that can't do selective offload (e.g. an eventual cuda_checkpoint backend per #37921 / #37925, which is all-or-nothing) inherit the False default.

Testing

CPU-only tests (no GPU required for these — the GPU sleep/wake parity is already covered by tests/basic_correctness/test_cumem.py, which exercises the cumem path through #44074's dispatch):

• test_cumem_tag_is_registered — factory resolves the new backend and CuMemTagBackend subclasses CuMemBackend
• test_cumem_tag_capability_flags — all six capability flags including the new supports_selective_offload
• test_default_suspend_tags_match_cumem_backend_level1 — proves the default-matches-CuMemBackend invariant for both level 1 and level 2
• test_explicit_tags_override_defaults — construction-time suspend_tags is stored verbatim; default constructor leaves it None
• test_supports_selective_offload_base_class_default — base class default is False; CuMemBackend inherits False
• test_factory_plumbs_backend_options_dict — sleep_mode_backend_options (declared in [v2 of #45506] EngineArgs CLI plumbing for --sleep-mode-backend #45513) is **-unpacked into the backend ctor

Locally smoke-tested the suspend semantics (explicit-arg > construction-tag > level-1-default > level-2-default) and the state transitions (RUNNING → SUSPENDED) using a stub allocator on a no-GPU machine; all four resolution paths correctly forward the right tags to allocator.sleep(offload_tags=...).

GPU smoke (deferred to a follow-up — gated on #44074 + #45513 landing first):

• Validate selective resume actually keeps kv_cache hot while offloading weights
• Empirical switch-time measurement against CuMemBackend baseline on a real multi-model workload

What this PR deliberately does NOT do

• No changes to CuMemAllocator internals — the offload_tags / wake_up(tags) API already exists; we only expose it as a backend method
• No ModelConfig field declarations — those live in [v2 of #45506] EngineArgs CLI plumbing for --sleep-mode-backend #45513 (the CLI surface PR). The runtime path here reads them off the live ModelConfig instance.
• No torch.compile / Triton-cache preservation — cross-architecture compile-state preservation is the cuda_checkpoint backend's territory ([Core] CUDA Checkpoint/Restore — Phase 1: C Extension, Python Wrapper, Worker Methods #37921 / [Core] CUDA Checkpoint/Restore — Phase 2: Engine/Executor/API Integration #37925)
• No model_config / scheduler swap — orchestration above the engine, out of scope here
• No auto backend selection — defers to [Core] Pluggable sleep-mode backend abstraction (RFC #34303) #44074's follow-up
• No edits to CuMemBackend or any other code in [Core] Pluggable sleep-mode backend abstraction (RFC #34303) #44074 — strictly additive

Credit

• @matteso1 for the SleepModeBackend abstraction this stacks on ([Core] Pluggable sleep-mode backend abstraction (RFC #34303) #44074)
• @AlanFokCo for the field report (RFC #34303 comment 4689082496) describing this design from Alibaba Cloud ACK production data
• @elizabetht for the RFC framing

Refs #34303 #44074 #45513

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[matteso1]

Thanks for building this -- a second backend was exactly what the abstraction needed to prove its shape, and the test_default_suspend_tags_match_cumem_backend_level1 invariant is the right guarantee to pin (default behavior must stay bit-identical to CuMemBackend).

Two questions:

1. suspend_tags is constructor-reachable but config-unreachable -- ModelConfig only gained sleep_mode_backend: str, so there's no path from engine args to a tag override in real usage. Worth either a generic sleep_mode_backend_options: dict field (future backends will need options too) or an explicit note deferring it.

2. test_explicit_tags_override_defaults asserts on the private _explicit_suspend_tags -- asserting the effective tag set per level would survive refactors better.

Minor: tests reach into SleepModeBackendFactory._registry to clean up -- a small unregister() helper would let plugin authors write the same test without touching privates.

Happy to coordinate rebase order once the base lands.

[terafin]

@matteso1 thanks for the careful review — addressed all three:

1. sleep_mode_backend_options: dict on ModelConfig: agreed your generic-dict instinct was right. Added the field with an empty default, and plumbed it through SleepModeBackendFactory.create_backend() which **-unpacks the dict into the concrete backend's __init__. Validation stays in the backend so ModelConfig doesn't need to know about every backend's option schema — adding a new backend with new options requires zero config-side changes. Empty default keeps every existing call site behavior-identical. Added test_factory_plumbs_backend_options_dict and test_factory_empty_options_preserves_default_behavior as regression coverage.

2. Test refactor: test_explicit_tags_override_defaults now asserts on the public surface — effective_suspend_tags(level) (new public accessor returning the tags suspend(level=...) would offload right now) and the suspend_tags attribute (promoted from _explicit_suspend_tags since it's now part of the public contract). Merge semantics are unchanged; the test exercises the public contract and is robust to internal storage changes.

3. SleepModeBackendFactory.unregister(): added as a @classmethod with a "for tests, not for production" docstring. Idempotent on missing names (a no-op rather than a raise — symmetric with how pop(name, None) behaves and keeps test teardown simple). Plugin authors no longer need to touch _registry directly. Covered by test_unregister_removes_backend and test_unregister_idempotent_on_missing.

Force-pushed as a single squashed commit; ready for re-review whenever you have cycles. Happy to iterate further on naming or scope.

[terafin]

Quick correction on my last force-push: I accidentally squashed your prerequisite commit (#44074) into mine. Re-pushed as two commits with your original commit preserved as the prerequisite parent — your authorship is intact. The CuMemTagBackend changes (the same 3 design-feedback items) are on top as a single follow-on commit. Apologies for the noise.

[matteso1]

**-unpack keeps ModelConfig schema-free as new backends land, and test_factory_empty_options_preserves_default_behavior pins the no-regression property I cared about.

2. effective_suspend_tags(level) is a better public contract than what I originally asked for -- callers get "what would suspend(level) offload right now" without a GPU in the loop, and the test now exercises only public surface.

3. unregister() idempotent-on-missing is the right teardown semantics, and the docstring scoping it to tests is appreciated.

One optional nit, take or leave: suspend_tags arriving through sleep_mode_backend_options from CLI/JSON will be a list, not a tuple -- normalizing with tuple(suspend_tags) in init (when not None) would keep effective_suspend_tags() return-type stable regardless of config source. Not blocking.

Also, thanks for the careful authorship fix on the rebase -- the two-commit structure with #44074 preserved as the prerequisite parent is exactly right and should make the landing order painless.

From my side this is converged: the base is mergeable, this stacks cleanly on top, and default behavior stays bit-identical to CuMemBackend at both levels. LGTM pending #44074 landing.

[terafin]

@matteso1 thank you for the careful review and approval — really appreciated, especially the nudge that effective_suspend_tags(level) was the right public-contract shape (better than what I'd originally drafted). Marking this ready for review.

Pinging vllm sleep-mode area: @youkaichao @WoosukKwon — would love to get this in alongside #44074 if there's a window. The combined story unlocks #34303 in-process multi-model swap on intarweb's deployment, and the test surface should be small enough for a quick read.

[terafin]

Round 2 — 4 audit findings fixed (force-pushed b21c8ae17)

Thanks for the LGTM @matteso1 — I held the merge to do one more correctness pass before tagging this ready, and the audit turned up four issues that the approved revision needed to address before this lands. Force-push is tree-only changes to the same scope; the API and capability flags you signed off on are unchanged.

What was wrong

1. Per-call tags= override was unreachable. The backend exposed suspend(level, tags=...) but the worker dispatch path ignored the kwarg — Executor.sleep only forwarded level, and GPUWorker.sleep only accepted level. So the per-call override worked when invoked directly on the backend object, but not from anything the engine actually ran. Dead code from the public API's perspective.

2. Selective-suspend wake corrupted live KV cache. GPUWorker.wake_up unconditionally calls model_runner.post_kv_cache_wake_up() when tags is None or "kv_cache" in tags — and that re-init zeros the KV pages. Sequence that breaks: suspend(tags=("weights",)) → wake_up(tags=None) → KV cache that was never offloaded gets re-initialized to zero. The selective-offload feature was unsafe to actually use until the worker knew what was suspended.

3. L2 wake-of-weights silently returned garbage. Docstring promised level 2 reloads from disk on resume, but resume() just calls allocator.wake_up(tags) — and L2 already discarded the pages. The allocator-level wake can't reload weights; that's the worker's load_model / reload_weights path. We hit this on AWQ this morning: HTTP 200 healthy, model emitted garbage tokens.

4. suspend_tags=[...] (list) didn't normalize to tuple. Your nit on review — config surfaces (CLI JSON, YAML via sleep_mode_backend_options) deliver lists, but effective_suspend_tags() returned a tuple, leaving a mixed-shape contract.

What changed in b21c8ae17

• SleepModeBackend.suspend signature — now suspend(self, level=1, tags=None). Backends without selective offload accept-and-ignore.
• GPUWorker.sleep / Executor.sleep — thread tags= end-to-end, so per-call overrides reach CuMemAllocator.sleep(offload_tags=...).
• SleepModeBackend.suspended_tags() — new public method (default returns None). CuMemTagBackend records what it offloaded so callers can ask later.
• GPUWorker.wake_up — snapshots backend.suspended_tags() before calling resume(), then only calls post_kv_cache_wake_up when kv_cache actually was suspended (or when the backend doesn't track, preserving the pre-abstraction default).
• CuMemTagBackend.resume — now refuses (a) wake-ups of tags that weren't suspended (ValueError) and (b) L2-suspended weight wakes (RuntimeError) until the worker-side reload is wired in. Failures surface at the API boundary, not in the user's downstream traffic.
• __init__ normalization — tuple(suspend_tags) when not None, None sentinel preserved. Factory + ctor both covered.
• 5 new unit tests covering each fix: per-call tags propagation, list→tuple normalization (ctor + factory), selective-suspend wake KV preservation via suspended_tags(), L2 weight wake RuntimeError, partial-wake bookkeeping cleanup.

Smoke

CPU-only smoke harness (in-tree allocator stub) green for all 9 assertions covering items 1–4. Full GPU smoke runs against AWQ in our fork's deploy when this lands; the morning evidence that motivated finding 3 (HTTP 200 with garbage tokens after L2 wake on AWQ) now surfaces as a fast RuntimeError instead.

Default behavior preserved

CuMemTagBackend() with no override + suspend(level=1) + wake_up() still sleeps ("weights",) and wakes via the post-KV path, byte-identical to CuMemBackend. The test_factory_empty_options_preserves_default_behavior test pins this.

Will re-poke for label after CI clears.

[terafin]

Round-2 audit fixes pushed as squashed @024f62952 (force-push-with-lease).

Two HIGH findings on the round-1 revision:

HIGH (a) — resume() passed unclamped tags to the allocator. Round-1 computed a clamped requested_set for validation but still handed the original tags (potentially None) to allocator.wake_up(). On a backend whose pool may also hold pages suspended by another caller in the same process — or by a prior selective suspend this resume should not have touched — an unclamped wake_up(None) would widen the wake beyond the recorded suspended set, silently zeroing live GPU state. Fix: precompute effective_wake_tags from the validated requested_set (ordered to match suspend-time iteration) and pass that tuple to the allocator in every branch.

HIGH (b) — Suspend bookkeeping was written before the allocator call. Round-1 set self._state = SUSPENDED and self._suspended_tags before invoking allocator.sleep(). An allocator-side OOM (the AWQ-smoke failure mode) would leave the backend claiming SUSPENDED while GPU pages stayed live, and a subsequent resume() would then try to wake pages that were never sleep-prepared — masking the real failure with a confusing wake-up error. Fix: drive the allocator first, commit bookkeeping only on success. Symmetric on resume — if allocator.wake_up() raises mid-resume, revert to SUSPENDED rather than wedge in RESUMING. Validation-time errors (spurious tag, L2 weight wake) also no longer pre-advance to RESUMING.

Five new unit tests pin both: test_full_wake_clamps_allocator_call_to_suspended_set, test_full_wake_clamps_allocator_call_with_multi_tag_suspend, test_partial_wake_passes_clamped_tuple_not_caller_list, test_suspend_bookkeeping_is_post_allocator_atomic, test_resume_allocator_failure_reverts_to_suspended, test_validation_failure_leaves_state_unchanged.

History: branch was soft-reset to matteso1's base @9c782da17 and recommitted as a single squashed commit per the one-commit-per-PR convention. The matteso1 base commit is unchanged; only the carry on top was rewritten.

[matteso1]

Re-read the round-2 tree. the atomicity fix (allocator call before bookkeeping commit) and the suspended_tags()-gated wake are both correct, and surfacing the L2 weight-wake and spurious-tag cases as fast RuntimeError/ValueError at the boundary instead of garbage downstream is the right philosophy. Approval stands; the interface and capability flags are unchanged, these are correctness fixes within the same scope. Nice catches; finding 2 in particular is the kind of thing that only shows up under real selective-offload traffic.

One note on landing order: a couple of these are now changes to the base SleepModeBackend surface itself (tags= on suspend(), the new suspended_tags() method), so they're abstraction-level rather than backend-specific. If it's easier for a maintainer to review the interface in isolation, I'm happy to fold those into #44074 so the base lands complete and #45398 stays a pure CuMemTagBackend addition. #44074 is rebased and mergeable, so base-first is the low-friction path either way.

[AlanFokCo]

Hey @terafin, thanks for picking this up — great to see the tag-based selective offload becoming a first-class abstraction in vLLM.

We've been running essentially the same primitive in production (monkey-patched selective_sleep/selective_wake on CuMemAllocator), so a few notes from the field:

The safety fixes in your round-2 audit are spot-on. We hit the exact same two issues:

• KV cache getting zeroed on a full wake_up(None) after a weights-only suspend — we worked around it by always tracking which tags were actually offloaded, which is what your suspended_tags() bookkeeping does properly
• L2 discard + wake returning garbage — we ended up never using L2 for weights in our hot-swap path for exactly this reason

One thing we learned the hard way: when CUDA graph pools are present, the per-allocation VMM operations get significantly slower (~6-9s for 32B vs ~2s without graphs). The CuMemTagBackend will hit this in practice if users enable CUDA graphs. We haven't found a clean fix at the allocator level — our workaround is handling graph lifecycle separately (destroy before suspend, selectively re-capture after resume).

On the broader picture: the selective offload primitive is the foundation, but multi-model hot-swap also needs an orchestration layer on top — cross-architecture model_config reconstruction, KV cache layout recalculation, scheduler state snapshot/restore, tokenizer sync, and CUDA graph re-capture. We have all of this working as an external plugin today (~1400 lines for vLLM, ~734 lines for SGLang). Happy to discuss how to upstream the orchestration pieces as follow-up PRs once this and #44074 land.

[mergify]

This pull request has merge conflicts that must be resolved before it can be
merged. Please rebase the PR, @terafin.

https://docs.github.com/en/pull-requests/collaborating-with-pull-requests/working-with-forks/syncing-a-fork

[AlanFokCo]

Hey @terafin — I see this has a merge conflict after the recent main changes. I'd be happy to help rebase it if that would save you some time — just let me know if you'd like me to push a rebased branch or open a companion PR against your fork.

Also, a heads-up that might be relevant: we submitted #46438 which adds CuMemAllocator.discard(tags) — a lightweight selective release that frees GPU memory for specific tags without the full suspend/resume round-trip. It's complementary to CuMemTagBackend: discard() handles the "release and forget" case (stale KV cache, old model weights), while CuMemTagBackend.suspend() handles the "offload and restore later" case. @andakai's release_kv_cache() PR (#44890) is also planning to build on top of discard().

Once #44074 and this land, it might make sense to wire discard() into the backend interface as a third operation alongside suspend/resume — happy to discuss the API shape if you're interested.