[https://nvbugs/6590666][fix] Detect worker death during initialization - #17578
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WalkthroughExecutor startup exchanges worker process identities for locally monitorable sessions. The proxy registers identities before readiness, supports legacy READY responses, acknowledges initialization statuses, and detects worker death during initialization. ChangesWorker readiness monitoring
Estimated code review effort: 3 (Moderate) | ~20 minutes Merge Risk: 🟡 Moderate · up to This change is intended to fail startup promptly when a worker dies before becoming ready, but the current head still risks waiting until the long health timeout in that case. The initialization failure path needs correction or explicit owner acceptance before merge. Sequence Diagram(s)sequenceDiagram
participant GenerationExecutorProxy
participant worker_main
participant InitializationStatusQueue
participant WorkerProcessMonitor
GenerationExecutorProxy->>worker_main: provide WORKER_PROCESS_IDENTITIES_SIGNAL
worker_main->>InitializationStatusQueue: publish worker process identities
worker_main->>GenerationExecutorProxy: continue initialization
GenerationExecutorProxy->>InitializationStatusQueue: wait for initialization status
InitializationStatusQueue-->>GenerationExecutorProxy: identity or READY message
GenerationExecutorProxy->>WorkerProcessMonitor: register worker identities
WorkerProcessMonitor-->>GenerationExecutorProxy: report dead worker before READY
Suggested reviewers: 🚥 Pre-merge checks | ✅ 4 | ❌ 1❌ Failed checks (1 warning)
✅ Passed checks (4 passed)
✨ Finishing Touches🧪 Generate unit tests (beta)
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In `@tensorrt_llm/executor/proxy.py`:
- Around line 695-701: Update _wait_for_executor_workers_ready() to call
_check_remote_worker_death() while polling readiness, so remote worker failures
are detected before READY even without local MPI futures or status entries.
Preserve the existing fatal-error handling, and add a regression test covering
an empty status queue, empty mpi_futures, and check_worker_error() returning a
worker-death error.
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tensorrt_llm/executor/proxy.pytensorrt_llm/executor/worker.pytests/unittest/executor/test_proxy_fast_death.py
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Signed-off-by: Chien-Chun Hung <2679986+chienchunhung@users.noreply.github.com>
Signed-off-by: Chien-Chun Hung <2679986+chienchunhung@users.noreply.github.com>
Signed-off-by: Chien-Chun Hung <2679986+chienchunhung@users.noreply.github.com>
Signed-off-by: Chien-Chun Hung <2679986+chienchunhung@users.noreply.github.com>
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@NVIDIA/trt-llm-ci-approvers Please approve the multi-GPU CI pipeline for this PR. Thanks! |
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…init-failure path A rank that dies during initialization leaves its peers wedged in the init collective still holding their share of the weights. The init wait loop (NVIDIA#17578) detects the death but never aborts the owned world, and the runtime checks it reuses mark the engine dead as a side effect of detection: release_exit_joins() marks the pool dead, which forces shutdown_abort()'s blocking shutdown() non-blocking and defangs its MPI_Abort escalation, so an abort added after those checks could never fire. Route every initialization failure (worker death and non-ready status) through a single _fail_initialization helper that aborts the owned session strictly before marking the engine dead, keep the init loop's death detection side-effect free, and defer the MPI future done-callback registration until the world reported ready (on an already-completed future add_done_callback() runs synchronously and would mark before the abort). The marking runs even if the abort itself raises, so the engine-dead bookkeeping and the original initialization error cannot be lost to a teardown failure. Add regression tests for every path. Signed-off-by: qgai <qgai@nvidia.com>
4 participants
Summary
NVBUG 6590666 captured a worker SIGKILL while Kimi K2.5 weights were loading. The cause of the SIGKILL is unknown. The spawned MPI job aborted, but the proxy did not observe the worker death and serving eventually reached its 1800-second health timeout.
Worker identities were previously registered only with the final
READYsignal. This change publishes identities before backend construction and weight loading, then monitors those processes while waiting forREADY. A worker exit now fails startup promptly with its rank and PID, even if the MPI future remains pending. READY-time registration remains as a compatibility fallback.Scope
This PR does not attempt to prevent SIGKILL or determine why the worker exited. It fixes the secondary failure: after a pre-
READYworker death, the parent must react promptly instead of remaining idle until the serving health timeout.Validation
25bb7f1ccea2c432f4455f8757d4b99fa7954cd6;A10-PyTorch-1,A10-PyTorch-2, andA10-PyTorch-3all succeeded.A10-PyTorch-1:test_worker_publishes_identities_before_backend_constructiontest_worker_death_before_ready_is_reported_from_registered_identityREADYdeath is surfaced even while the MPI future remains pending.The validation success criterion is prompt failure propagation to the parent. Reproducing the original GB200 Kimi workload or identifying the SIGKILL cause is outside this PR scope.
Dev Engineer Review
READY.READY-time identity registration remains as a compatibility fallback.worker_mainretains an optional identity-signal parameter.RuntimeError.SIGKILLremains unresolved.QA Engineer Review
tests/unittest/executor/test_proxy_fast_death.py.READY, pending MPI futures, remote worker errors, status acknowledgements, identity publication before backend construction, and identity delivery failures.tests/integration/test_lists/test-db/l0_a10.yml.