fix: prevent MM cache hang from stale LRU order keys

[jeffye-dev]

FIX #43941

LRUCache.touch() inserted keys into the internal LRU order even when the key was not present in the cache data. The multimodal processor and receiver caches touch every hash in a request before updating the cache so that items used by the current request are not evicted midway through the batch. For cache misses, the old touch() behavior created order-only ghost keys.

When the cache was full, eviction selected the oldest key from the order and called pop(). If the selected key was a ghost key, pop() returned without deleting a real value, currsize did not decrease, and cachetools could keep retrying eviction without making progress. In vLLM this can leave the EngineCore input processing path spinning inside MM cache updates, so requests are accepted but never reach scheduling or model execution.

Make touch() a pure recency update by ignoring missing keys, and harden popitem() to remove stale order-only keys left by older behavior before returning a real cache item. Add regression tests for both missing-key touch behavior and stale order cleanup during popitem().

Summary

This PR fixes a possible infinite eviction loop in vllm.utils.cache.LRUCache
that can be triggered by the multimodal processor cache.

The issue is caused by LRUCache.touch() creating an entry in the internal LRU
order for keys that are not actually present in the cache data. Such
order-only entries can later be selected by popitem() during eviction. Since
there is no real cache value for that key, pop() does not reduce currsize,
so cachetools can repeatedly try to evict without making progress.

In the multimodal path, this can leave the EngineCore input processing thread
spinning inside MM cache updates. The API server may accept the request, but
the request never reaches scheduling or model execution.

Root Cause

The multimodal processor and receiver caches intentionally call touch() for
all multimodal hashes in a request before updating cache values:

• P0 processor cache: _merge_mm_kwargs() calls
  cache.touch_sender_cache_item(item_hash) for every item hash before
  inserting or reusing cached processor outputs.
• P1 receiver cache: get_and_update_features() calls
  touch_receiver_cache_item(cache_key, feature.data) for every feature before
  inserting or reusing cached multimodal kwargs.

That pre-touch step is meant to keep the cache eviction order stable within a
single request. If a request contains several multimodal items and inserting a
new item triggers eviction, items used later in the same request should not be
evicted halfway through the batch.

However, the old LRUCache.touch() implementation did this:

def touch(self, key):
    try:
        self._LRUCache__order.move_to_end(key)
    except KeyError:
        self._LRUCache__order[key] = None

For cache misses, this added the key only to the internal LRU order, without
adding a value to the underlying cache data. This creates a "ghost key":

key exists in __order
key does not exist in __data

When the cache is full, eviction selects the oldest key from the order and then
calls pop():

lru_key = next(key for key in self.order if key not in self.pinned_items)
value = self.pop(lru_key)

If lru_key is a ghost key, pop() sees that the key is not in the real cache
and returns without deleting any value. As a result:

• currsize does not decrease.
• The stale order key may remain in the order.
• cachetools eviction can keep retrying without making progress.

This is especially visible in multimodal workloads because cache misses are
normal for new images, videos, or audio inputs, and the MM cache may be close to
its configured capacity.

User-visible Impact

When this happens, a vLLM instance can appear to accept requests but stop making
forward progress on them:

• The request is added by the API server.
• The EngineCore input processing path can spin inside MM cache update logic.
• The request does not reach scheduling or model execution.
• GPU utilization can remain at zero.
• The client or upstream proxy may eventually cancel or abort the request.

The py-spy call stack is like as below:

top -H -p 1209
PID USER PR  NI    VIRT    RES    SHR S  %CPU  %MEM     TIME+ COMMAND
5713 root 20   0  196.8g 105.3g   2.4g R  99.9   3.5     14,01 VLLM::EngineCor 

py-spy dump -p 1209 --locals 
Thread 5713 (active+gil): "Thread-1 (process_input_sockets)"
    popitem (vllm/utils/cache.py:197)
        Arguments:
            self: <cell at 0x7f802d99baf0>
            remove_pinned: False
    __setitem__ (cachetools/__init__.py:85)
        Arguments:
            self: <LRUCache at 0x7f86a46ac4a0>
            key: "79ba13f0055eab5fe445ab4047cf29e4993a4c872d4bc095e766cdffb3217fa0"
            value: <MultiModalKwargsItem at 0x7f802b85d820>
        Locals:
            maxsize: 4294967296
            size: 19418136
    __setitem__ (cachetools/__init__.py:297)
        Arguments:
            self: <LRUCache at 0x7f86a46ac4a0>
            key: "79ba13f0055eab5fe445ab4047cf29e4993a4c872d4bc095e766cdffb3217fa0"
            value: <MultiModalKwargsItem at 0x7f802b85d820>
            cache_setitem: <function at 0x7f876d276700>
    get_and_update_item (vllm/multimodal/cache.py:646)
        Arguments:
            self: <MultiModalReceiverCache at 0x7f86b82e7b00>
            mm_item: <MultiModalKwargsItem at 0x7f802b85d820>
            mm_hash: "79ba13f0055eab5fe445ab4047cf29e4993a4c872d4bc095e766cdffb3217fa0"
        Locals:
            cached_item: None
    get_and_update_features (vllm/multimodal/cache.py:591)
        Arguments:
            self: <MultiModalReceiverCache at 0x7f86b82e7b00>
            mm_features: [<MultiModalFeatureSpec at 0x7f802d1dac90>, <MultiModalFeatureSpec at 0x7f801ad2f1a0>, ...]
        Locals:
            feature: <MultiModalFeatureSpec at 0x7f801ad2f1d0>
            cache_key: "79ba13f0055eab5fe445ab4047cf29e4993a4c872d4bc095e766cdffb3217fa0"
    preprocess_add_request (vllm/v1/engine/core.py:787)
        Arguments:
            self: <EngineCoreProc at 0x7f873fc731d0>
            request: <EngineCoreRequest at 0x7f802d6b20b0>
    process_input_sockets (vllm/v1/engine/core.py:1466)
        Arguments:
            self: <EngineCoreProc at 0x7f873fc731d0>
            input_addresses: ["ipc:///tmp/99992e83-a376-465d-9b75-2460c26a9fb0"]
            coord_input_address: None
            identity: <bytes at 0x7f873fc98ea0>
        Locals:
            add_request_decoder: <MsgpackDecoder at 0x7f8d1f7b33b0>

Fix

This PR makes two defensive changes to LRUCache.

First, touch() is changed to be a pure recency update:

def touch(self, key):
    if key in self:
        self._LRUCache__order.move_to_end(key)

Missing keys are ignored. This prevents new ghost keys from being created.

Second, popitem() is hardened to handle any stale order-only keys that may
already exist, either from older code or from an existing in-memory cache state:

while True:
    ...
    if lru_key in self:
        value = self.pop(lru_key)
        return (lru_key, value)

    self._LRUCache__order.pop(lru_key, None)

This ensures eviction only returns a real cache item and can make progress even
if stale order entries are encountered.

Tests

This PR adds regression coverage for both sides of the fix:

• test_lru_cache_touch_missing_key_does_not_add_order_entry
  verifies that touching a missing key does not add it to the cache order.
• test_lru_cache_popitem_cleans_stale_order_key
  manually creates a stale order-only key and verifies that popitem() removes
  it while still evicting a real cache entry.

Local validation:

python3 -m py_compile vllm/utils/cache.py tests/utils_/test_cache.py

uv run pytest tests/utils_/test_cache.py was attempted locally, but dependency
setup failed while fetching the triton-cpu git dependency due to a network/RPC
disconnect. The failure happened before the test file was executed.

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[gemini-code-assist]

Code Review

This pull request modifies the LRUCache implementation to prevent and clean up stale keys within the LRU order. The touch method was updated to only move keys that already exist in the cache, and popitem now includes a loop to identify and remove keys from the internal order that are no longer present in the cache. While new tests were added to verify these changes, feedback indicates that test_lru_cache_popitem_cleans_stale_order_key contains a logic error: the stale key is currently added after the valid key, meaning popitem returns the valid key immediately without exercising the cleanup code. A suggestion was provided to reorder the insertions in the test.

[DarkLight1337]

Have you actually encountered this problem in practice? It would be best to have a test that actually triggers this issue (infinite hang)

[jeffye-dev]

Have you actually encountered this problem in practice? It would be best to have a test that actually triggers this issue (infinite hang)

yes, It's not easy to reproduce, but I got the problem several times in our high-stress scenario. When the Worker process hangs at popitem(), I use the py-spy to capture the call stack (see the PR description).

[DarkLight1337]

Since others have also reported this issue, let's just merge this first