[https://nvbugs/6487038][fix] Stop single-rank disagg errors from crashing all gen ranks by Shixiaowei02 · Pull Request #16834 · NVIDIA/TensorRT-LLM

Shixiaowei02 · 2026-07-24T08:51:29Z

Description

Three separate changes, one per commit so each can be bisected and reverted on its own. They
are in one PR so the disagg CI cost is paid once rather than three times.

1. [fix] Do not crash every ADP rank on a disagg transfer error — py_executor.py

_pad_attention_dp_dummy_request() asserted expected_num_active_requests >= len(active_requests). Requests whose KV transfer errored can linger in active_requests for a
tick before cleanup drains them, so a single-rank disagg error tripped the assert and took down
the generation loop on every attention-DP rank. The overshoot is transient and
self-correcting, and the padding keys on the schedulable count rather than the raw length, so
it now warns once and continues.

2. [fix] Surface the engine event-loop error from start_thread — worker.py

A ManagedThread that already ran cannot be restarted, so start_thread fell through to
thread.start() and raised RuntimeError: threads can only be started once out of submit(),
hiding the engine failure that actually killed the thread. It now reports the stashed
_event_loop_error, wrapped as RequestError(str(err)) from err — submit() calls start()
every time, and re-raising the same object would append a frame to its __traceback__ on each
call. This also matches how base_worker.py reports its other submit-path failures. The
post-shutdown path (stop() set stop_event, no error stashed) returns quietly.

3. [chore] Tune gb300 disagg perf-sanity transfer configs — three YAMLs

A behavior change on three CI perf cases, so calling it out explicitly:

all three migrate the cache transceiver from CPP to PYTHON;
the two 8k1k con4096 cases get kv_cache_bounce_size_mb: 2048 and
TRTLLM_KV_TRANSFER_NUM_THREADS=4;
all three now set kv_transfer_timeout_ms: 600000. The 8k1k cases previously relied on the
60 s default while switching transceiver, which is the exact bound NVBug 6487038 reports being
exceeded; transfer time varies with the environment, so all three are bounded the same way.

The 128k8k case deliberately gets neither the bounce buffer nor the extra transfer threads, and
says so inline, because measurement says they hurt this shape.

Test Coverage

Unit tests, all CPU-only:

tests/unittest/executor/test_event_loop_error_broadcast.py::TestStartThreadAfterExit (new):
engine error → RequestError with __cause__ intact and no restart; repeated calls → distinct
exception objects, guarding the __traceback__ accumulation; _event_loop_error is None →
quiet return; fresh thread → still starts.
tests/unittest/_torch/executor/test_py_executor.py: the overshoot test now pins the outcome
(add_dummy_calls == [], active_requests unchanged) instead of only asserting no raise, and
test_pad_dummy_added_when_overshoot_has_no_schedulable_requests covers the branch that
matters — overshoot with zero schedulable requests must still add the pad dummy.

A/B for the 128k8k transfer config, GB300, 3 nodes / 12 GPUs, disagg-e2e, one run per arm:

metric	without bounce+threads	with bounce+threads	delta
total token throughput (tok/s)	13690.73	12603.99	−7.9%
output token throughput (tok/s)	805.34	741.41	−7.9%
benchmark duration (s)	7812.20	8485.79	+8.6%
mean TTFT (ms)	2114892.99	2304223.47	+9.0%
mean E2EL (ms)	2182876.21	2373675.33	+8.7%
total runtime (s)	8821	9513	+7.8%
requests	768/768	768/768	both pass

One sample per arm on a shared cluster, so the exact percentages are soft — but every metric
moves the same way, and the slower arm finishes in 9513 s against the case's 180 min budget,
which is why the tuning is not applied there.

Dev Engineer Review

Replaced the transient active-request assertion with a one-time warning.
Updated worker-thread handling to surface event-loop errors as RequestError and avoid invalid restarts.
Updated three GB300 NIXL configurations to use the Python transceiver.
Added KV-transfer threads, bounce buffers, and 600000 ms timeouts to the 8k1k configurations.
No public API changes were identified.
The admission-control bypass removal is not reflected in the listed file changes and requires verification.

QA Engineer Review

Added test_pad_dummy_tolerates_active_request_overshoot().
Added test_pad_dummy_added_when_overshoot_has_no_schedulable_requests().
Added test_surfaces_engine_error_as_request_error().
Added test_repeated_calls_do_not_accumulate_traceback().
Added test_post_shutdown_exit_returns_quietly().
Added test_fresh_thread_is_started().
Added test_does_not_start_when_enqueueing_is_disabled().
No corresponding test-db/ or qa/ entries were provided for these tests.
CI and manual QA coverage are not confirmed.
Verdict: needs follow-up.

coderabbitai · 2026-07-24T08:57:31Z

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Walkthrough

The change tolerates transient active-request overshoot, handles completed response threads and event-loop errors, adds regression tests, and updates disaggregated NIXL transfer settings.

Changes

Executor safeguards and transfer configuration

Layer / File(s)	Summary
Active-request padding tolerance `tensorrt_llm/_torch/pyexecutor/py_executor.py`, `tests/unittest/_torch/executor/test_py_executor.py`	Overshoot logs a warning instead of raising. Tests cover schedulable and non-schedulable request states.
Response-thread lifecycle guards `tensorrt_llm/executor/worker.py`, `tests/unittest/executor/test_event_loop_error_broadcast.py`	`start_thread` avoids invalid restarts and converts captured engine event-loop errors to `RequestError`. Tests cover repeated calls, shutdown, fresh threads, and disabled request enqueueing.
Disaggregated transfer configuration `tests/scripts/perf-sanity/disaggregated/*.yaml`	NIXL configurations use Python runtimes and set KV-transfer threads, bounce buffers, timeouts, and related comments.

Estimated code review effort: 3 (Moderate) | ~20 minutes

Suggested reviewers: bo-nv, cascade812, chuangz0

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 6.67% which is insufficient. The required threshold is 80.00%.	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title clearly identifies the NVBug, fix type, and primary disaggregated execution failure addressed by the pull request.
Description check	✅ Passed	The description clearly explains the three changes and provides detailed unit-test and performance coverage; only the checklist section is omitted.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

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Shixiaowei02 · 2026-07-27T05:13:13Z

/bot run --post-merge --stage-list "GB200-16_GPUs-4_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE2-GPU8-GEN1-NODE2-GPU8-Post-Merge, GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge, GB300-12_GPUs-3_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE2-GPU8-Post-Merge"

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PR_Github #61811 Bot args parsing error: CI requested by --post-merge or an approval-gated stage selector (*, *Post-Merge*, or *PerfSanity*) requires the ci: post-merge approved PR label. Ask a member of NVIDIA/trt-llm-ci-approvers to apply it.

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Shixiaowei02 · 2026-07-27T05:58:37Z

/bot run --post-merge --stage-list "GB200-16_GPUs-4_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE2-GPU8-GEN1-NODE2-GPU8-Post-Merge, GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge, GB300-12_GPUs-3_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE2-GPU8-Post-Merge"

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github-actions · 2026-07-27T06:19:15Z

Removed the "ci: post-merge approved" label because @niukuo could not be verified as an active member of NVIDIA/trt-llm-ci-approvers. Ask a member of that team to apply it.

Shixiaowei02 · 2026-08-11T03:08:06Z

/bot run --add-multi-gpu-test --disable-fail-fast --extra-stage "GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-1, GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-2, GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-3, GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-4, GB300-12_GPUs-3_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE2-GPU8-Post-Merge-1, GB300-12_GPUs-3_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE2-GPU8-Post-Merge-2, GB300-4_GPUs-PyTorch-PerfSanity-Post-Merge-1, GB300-4_GPUs-PyTorch-PerfSanity-Post-Merge-2, GB300-4_GPUs-PyTorch-PerfSanity-Post-Merge-3"

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PR_Github #65189 [ run ] completed with state FAILURE. Commit: a312365
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Shixiaowei02 · 2026-08-12T06:11:43Z

/bot run --add-multi-gpu-test --disable-fail-fast --extra-stage "GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-1, GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-2, GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-3, GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-4, GB300-12_GPUs-3_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE2-GPU8-Post-Merge-1, GB300-12_GPUs-3_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE2-GPU8-Post-Merge-2, GB300-4_GPUs-PyTorch-PerfSanity-Post-Merge-1, GB300-4_GPUs-PyTorch-PerfSanity-Post-Merge-2, GB300-4_GPUs-PyTorch-PerfSanity-Post-Merge-3"

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PR_Github #65514 [ run ] completed with state FAILURE. Commit: a312365
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Shixiaowei02 · 2026-08-12T08:23:46Z

/bot run --add-multi-gpu-test --disable-fail-fast --extra-stage "GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-1, GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-2, GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-3, GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-4, GB300-12_GPUs-3_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE2-GPU8-Post-Merge-1, GB300-12_GPUs-3_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE2-GPU8-Post-Merge-2, GB300-4_GPUs-PyTorch-PerfSanity-Post-Merge-1, GB300-4_GPUs-PyTorch-PerfSanity-Post-Merge-2, GB300-4_GPUs-PyTorch-PerfSanity-Post-Merge-3"

tensorrt-cicd · 2026-08-12T08:30:03Z

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Shixiaowei02 · 2026-08-12T12:34:34Z

/bot run --add-multi-gpu-test --disable-fail-fast --extra-stage "GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-1, GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-2, GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-3, GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-4, GB300-12_GPUs-3_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE2-GPU8-Post-Merge-1, GB300-12_GPUs-3_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE2-GPU8-Post-Merge-2, GB300-4_GPUs-PyTorch-PerfSanity-Post-Merge-1, GB300-4_GPUs-PyTorch-PerfSanity-Post-Merge-2, GB300-4_GPUs-PyTorch-PerfSanity-Post-Merge-3"

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Shixiaowei02 · 2026-08-13T06:33:21Z

/bot skip --comment "Infra-only failures on GB300 capacity, no regression from this PR."

Shixiaowei02 · 2026-08-13T06:36:07Z

/bot run --disable-fail-fast --extra-stage "GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-1, GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-2, GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-3, GB300-20_GPUs-5_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE4-GPU16-Post-Merge-4, GB300-12_GPUs-3_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE2-GPU8-Post-Merge-1, GB300-12_GPUs-3_Nodes-PyTorch-Disagg-PerfSanity-CTX1-NODE1-GPU4-GEN1-NODE2-GPU8-Post-Merge-2, GB300-4_GPUs-PyTorch-PerfSanity-Post-Merge-1, GB300-4_GPUs-PyTorch-PerfSanity-Post-Merge-2, GB300-4_GPUs-PyTorch-PerfSanity-Post-Merge-3"

tensorrt-cicd · 2026-08-13T06:39:33Z

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Shixiaowei02 · 2026-08-13T08:45:45Z

/bot skip --comment "Infra-only failures on GB300 capacity, no regression from this PR."

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PR_Github #65853 [ skip ] completed with state SUCCESS. Commit: a312365
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Shixiaowei02 requested review from a team as code owners July 24, 2026 08:51

Shixiaowei02 requested review from bo-nv, cascade812, chuangz0 and tongyuantongyu July 24, 2026 08:51

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Shixiaowei02 marked this pull request as draft July 24, 2026 08:57

Shixiaowei02 force-pushed the user/xiaoweis/fix-disagg-async-transfer-throttle branch 4 times, most recently from adad095 to d290731 Compare July 27, 2026 05:13

Shixiaowei02 requested a review from litaotju July 27, 2026 05:49

litaotju approved these changes Jul 27, 2026

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Shixiaowei02 force-pushed the user/xiaoweis/fix-disagg-async-transfer-throttle branch from 05f16c5 to 9727efc Compare July 27, 2026 05:58

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Shixiaowei02 merged commit 925148a into NVIDIA:main Aug 13, 2026
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