[Bugfix][KV Offload] Recover from disk I/O failures

[Woolgathererer]

Purpose

Disk I/O errors can terminate a SimpleCPUOffloadConnector background thread
before it reports completion, leaving KV transfers pending.

Following discussion about the initial error-propagation approach, this revision
treats recoverable disk failures as request-level KV
load failures. The I/O thread remains available for subsequent transfers, and
the scheduler can recompute or fail only the affected requests through the
existing failure policy.

Handle disk syscall errors and short reads/writes within the transfer loop.
Drain outstanding DMA before reporting completion or reusing buffers, and keep
the I/O thread running for subsequent transfers.

• Failed reads: skip DMA for unreadable blocks, continue the rest of the batch,
  and report only failed GPU blocks together with receive completion. Invalidate
  affected disk cache entries so retries cannot reload them. Healthy requests
  sharing the batch continue normally.
• Failed stores: aggregate failures across ranks and discard the store after
  every rank finishes, releasing references without caching incomplete data.
• Recovery safety: drain queued disk work before preempted blocks are reused.
  Reuse the upstream hybrid load recovery from [Core] Fix ValueError on KV load failure with a hybrid KV cache #50388 for multiple KV groups.
  This PR no longer changes the core scheduler.

Recomputation uses the existing kv_load_failure_policy="recompute" setting.
The default, "fail", ends only affected requests. Device initialization, CUDA,
event and stream synchronization failures remain fatal.

Related PRs cover different work: #52838 targets OffloadingConnector, and
#55424 addresses O_DIRECT alignment. This change handles failure recovery in
SimpleCPUOffload's disk backend.

Test Plan

Local command (macOS arm64, without CUDA):

VLLM_TARGET_DEVICE=cpu HF_HUB_OFFLINE=1 TRANSFORMERS_OFFLINE=1 \
VLLM_NO_USAGE_STATS=1 PYTEST_DISABLE_PLUGIN_AUTOLOAD=1 \
.venv/bin/python ../pr55066-verification/run_cpu_tests.py . \
  tests/v1/simple_kv_offload \
  tests/v1/kv_connector/unit/test_kv_load_failure_recovery.py \
  tests/v1/kv_connector/unit/test_simple_cpu_offload_connector.py \
  tests/v1/kv_connector/unit/test_output_aggregator.py \
  tests/v1/executor/test_multiproc_executor.py -q --tb=short

The local wrapper invokes pytest with the existing skip_global_cleanup marker
to avoid a host torch teardown crash. It does not patch connector behavior.
On a supported test host, use .venv/bin/python -m pytest with the same test
paths. Tests exercise real threads, queues, workers, block pools and scheduler
with mocked CUDA operations and injected disk outcomes.

Test Result

• After rebasing onto main (9f03b510c3): 152 passed; 2 GPU-dependent modules
  skipped.
• Regression coverage includes shared-batch request isolation, both failure
  policies, subsequent transfers, DMA draining, preemption, async multi-group
  recovery, rank aggregation and reset.
• Code-related pre-commit hooks, mypy 3.12 and git diff --check passed.
• Model evaluation was not run. Real GPU DMA, NVMe/O_DIRECT, multi-rank serving,
  output equivalence and performance still need hardware validation.

Previous full-repository hooks encountered local environment failures: actionlint
dependency downloads timed out, pip-compile could not access the uv cache,
and test-nonroot-entrypoint failed on macOS /var versus /private/var path
handling. For the rebase, applicable pre-commit hooks and mypy 3.12 passed;
actionlint remained skipped. Dependency and entrypoint hooks had no matching
changed files.

AI assistance was used to develop the tests, every changed line has been reviewed and tested by me.

[claude]

Claude Code Review

This pull request is from a fork — automated review is disabled. A repository maintainer can comment @claude review to run a one-time review.

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[mergify]

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

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