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[https://nvbugs/6919819][fix] Give non-attention-DP overlap runs the retiring-request seat headroom - #20250

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@chenfeiz0326 chenfeiz0326 commented Oct 14, 2026 •

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Description

NVBug 6919819 reports a gradual decline of the GB200 ctx_only qwen3-235b-fp4 8k1k
con1024 perf-sanity case (Output Token Throughput 6.03 -> 5.58, -7.5%). The
post-merge series is not a slope: it is three discrete steps, each of which
also appears on the two sibling ctx_only qwen3-235b cases (con64, con1) that
share the same context-worker config. This PR fixes the largest one; the other
two are reported below with their measured causes.

Root cause of the largest step (builds 2935-2938, -2.6%)

#18346 stopped forcing disable_overlap_scheduler=True for perf-sanity
ctx_only cases, so these cases started running with the overlap scheduler
on (b_disable_overlap_scheduler flips True -> False at build 2935 in
the perf DB). The CI worker log at ToT shows what overlap does to this context
server (max_batch_size=4, TP=1, no attention DP, 8k-token prompts):

num_scheduled_requests histogram (5123 steady-state iterations): {1: 2561, 3: 2560}
cadence: 3, 1, 3, 1, 3, 1, ...                    (never 4)

Under the overlap scheduler a request that emits its last token is torn down
one iteration late (_process_previous_batch runs after the next iteration has
already fetched and scheduled), so it keeps its sequence slot and is still
counted by admission. A context request finishes in its prefill step, so
every scheduled request is retiring during the very next fetch. The
non-attention-DP branch of _fetch_new_requests subtracts
len(active_requests) -- retirees included -- from max_num_active_requests,
so each iteration can only refill the seats the previous one left unused:
3 -> 1 -> 3 -> 1, a mean batch of 2 against a configured 4.

#18457 (nvbug 6627795) fixed exactly this for attention DP: it excludes
retiring requests from admission (ADPRouter.exclude_retiring_requests) and
gives the seat pool one extra micro-batch so the replacement cohort has slots
(should_enable_overlap_headroom). Both halves were gated on
mapping.enable_attention_dp, so a TP-only context server -- and every
aggregated non-ADP overlap run -- kept the bug. The index pool
(KVCacheManagerV2.max_admissible_sequences) already widens for any non-PP
overlap run, so only the seat gate and the admission count were missing.

The change

  • should_enable_overlap_headroom: drop the enable_attention_dp term. Every
    other exclusion is unchanged (PP, overlap off, KV cache manager V1, hybrid/SSM
    models, MRoPE-delta models).
  • _fetch_new_requests, non-attention-DP branch: when the router reports
    exclude_retiring_requests (which follows the same gate), discount
    count_retiring_requests(active_requests) from the count admission
    subtracts. Retiring requests still count as live for the idle-wait decision,
    exactly as on the attention-DP branch.

Because validate_seq_slot_pool_covers_admission already requires the index
pool to cover the seat pool, and the index pool already doubles on this path,
the startup invariant holds with no further change.

Scope and cost

What changes for which configurations:

  • Affected: any non-PP run with the overlap scheduler on and KV cache manager V2 that
    is not attention-DP. That covers aggregated TP servers and disaggregated context and
    generation workers. Hybrid/SSM and MRoPE-delta models keep the old pool, because the
    gate's exclusions for them are unchanged. Of the GB200/H200 perf-sanity disaggregated
    configs, 14 have such a context worker. 116 aggregated perf-sanity server configs (B200
    and others) also pass the gate now.
  • Admission is unchanged. max_num_active_requests (and so the batch) is still
    max_batch_size * pp_size. The extra seats only let a replacement be admitted while its
    predecessor is torn down one iteration late, which is exactly the attention-DP behaviour
    since [https://nvbugs/6627795][fix] stop charging retiring requests against ADP admission and capacity #18457.
  • Memory: per-seat buffers double from B to 2B rows: sampler state, penalty
    counts, seed/top-p arrays, guided-decoder bitmask, and the speculative draft-prob
    buffers. The vocab-sized ones are allocated lazily, only when the feature is used, and
    are the same buffers attention-DP runs have carried since [https://nvbugs/6627795][fix] stop charging retiring requests against ADP admission and capacity #18457.
  • Disaggregated context workers: a sender releases its seat in start_transfer,
    before the KV transfer. So requests still sending KV hold no seat, and the extra
    micro-batch is never spent on them.

Perf verification

Setup: GB200 (oci-hsg), the post-merge CI wheel of fca08032f7 (GenPostMergeBuilds 2911)
installed in the image that commit pins (NGC PyTorch 26.09), CI harness from the same
commit. The branch was then rebased onto current main. None of the 24 commits in between
touch the four files changed here, and those files are byte-identical to the ones measured. Both arms install that one wheel. The fix arm then overlays
exactly the two .py files this PR changes into site-packages, and the overlay hook proves
it per rep (replaced= count + the new gate's source line present/absent). Arms are
interleaved within single-node allocations, and reps are spread over several nodes.

ctx_only-gb200_qwen3-235b-fp4_8k1k_con64_ctx1_tp1_gen1_tep4_eplb0_mtp0_ccb-NIXL,
Total Token Throughput (tok/s):

arm reps mean vs base
base (fca08032f7) 45,209 / 44,957 / 45,361 / 45,381 45,227 —
this PR 46,578 / 46,692 / 46,642 / 46,742 / 46,642 46,659 +3.17%
reference: overlap scheduler off 46,181 / 46,219 46,200 +2.15%

The base and PR ranges don't overlap. CVs are 0.43% (base) and 0.13% (PR), so the 3-SE
noise floor is 0.67%. GB200 nodes differ from each other by up to ~1.5% on this case,
so the cleanest view pairs base and PR reps on the same node inside one allocation. That
gives +3.03%, +2.97% and +2.97% on three different nodes. The overlap-off row is what
this case measured before #18346 turned overlap on. With this PR, overlap ON beats it by ~1.0%, so the change recovers the loss and
keeps overlap's own benefit.

Mechanism check, from the worker's per-iteration log on the same runs:

base this PR
max_num_requests (seat pool) 4 8
IndexMapper capacity (index pool, unchanged) 9 9
scheduled batch per iteration 3, 1, 3, 1, ... (mean 1.98) 4, 4, 4, ... (mean 3.91)
device time per request (median step time ÷ batch) 181.3 ms 175.5 ms

The bug's own case, con1024 (same context-worker config, 10,240 requests per rep, ~40 min
each). Every row pairs reps that ran on the same node inside one allocation:

node base (tok/s) this PR (tok/s) Output tok/s (the NVBug metric) vs base
nvl72107-T16 45,977 47,401 5.61 -> 5.79 +3.10%
nvl72107-T18 46,458 / 46,344 48,062 / 48,098 5.66 -> 5.87 +3.62%

On nvl72107-T18 the reps vary by 0.17% (base) and 0.05% (PR), a 3-SE floor of 0.39%.
The scheduled batch goes from a mean of 2.00 to 3.99, and device time per request from
176.5 ms to 170.3 ms. Against the overlap-off reference on a third node (nvl72113-T15),
this PR is +0.96% (46,597 vs 46,156), the same ordering as con64.

Other steps in the decline (not changed by this PR)

The perf-sanity series of the three GB200 ctx_only qwen3-235b cases (CI post-merge
medians per segment, relative to builds 2916-2934):

segment con1024 con64 con1
builds 2938-2965 (after step 1) -2.72% -2.55% +0.38%
builds 2968-3010 (after step 2) -4.24% -4.07% -2.28%
builds 3012-3017 (after step 3) -5.26% -5.43% -3.80%

Test Coverage

  • tests/unittest/_torch/executor/test_seq_slot_sizing.py: the gate now widens
    without attention DP; seat pool is 2B for any non-PP V2 overlap run; the
    seat/index pool invariant test is updated.
  • tests/unittest/_torch/executor/test_py_executor.py: three new tests drive the
    non-attention-DP branch of _fetch_new_requests and assert the admission count
    and the live count it hands to the queue wait, with and without headroom.
    test_non_adp_fetch_pops_a_full_batch_beside_retiring_requests runs the same
    branch through the real _pop_from_waiting_queue and FCFSWaitingQueue: 4 retiring
    requests, 4 waiting, capacity 4. With headroom all 4 waiting requests are admitted.
    Without it none are, because the retirees hold every seat. Both ways the retirees still
    count as live.
  • Both modules are collected by l0_cpu.yml (unittest/_torch/executor), and
    test_seq_slot_sizing.py is also listed in l0_a10.yml.
  • Run in the CI image (NGC PyTorch 26.09, aarch64) against the post-merge CI wheel of
    30dc23ffe58 (GenPostMergeBuilds 2946). That build is byte-identical to this PR's base
    c98b9765d85 for every pyexecutor and executor-test file involved:
    • stock code with the new tests: the 6 tests that assert the new behaviour fail
      (32 pass). That proves they bind to the change.
    • with this PR's two files: those 38 tests pass.
    • test_seq_slot_sizing.py, test_py_executor.py and test_adp_router.py in full:
      478 passed, 0 failed.
  • Rebased onto c98b9765d85. Main added a KV-load tracker to _fetch_new_requests in the
    meantime, so the test stubs that call it get a disabled tracker. The KV-load test helper
    also gets a router with the default exclude_retiring_requests=False, which every real
    executor builds in __init__. The PR's code diff is unchanged by the rebase.
  • Perf: the A/B above.

PR Checklist

  • PR description clearly explains what and why.
  • Follows the TensorRT-LLM coding guidelines.
  • Test cases are provided.

🤖 Generated with Claude Code

Dev Engineer Review

  • should_enable_overlap_headroom now allows eligible non-PP, overlap-enabled KV cache manager V2 runs without attention DP. Hybrid models and models with MRoPE delta cache remain excluded.
  • When exclude_retiring_requests is enabled, non-attention-DP admission excludes retiring requests from its capacity count. The live-request count still includes them for idle-wait decisions.
  • The change targets overlap refill behavior. It does not change public declarations. The reported throughput gains are author-reported and were not independently verified.
  • The available checkout diff does not show these functional changes; it shows formatting changes in py_executor.py. The summary of behavior above follows the supplied PR change description.

QA Engineer Review

  • The supplied change description reports tests for seat-pool sizing, retiring-request admission, live-request counts, and waiting-queue admission. It also reports 470 passed and 0 failed across test_seq_slot_sizing.py, test_py_executor.py, and test_adp_router.py. These results were not independently rerun.
  • test_seq_slot_sizing.py appears in tests/integration/test_lists/test-db/l0_a10.yml. No test-list reference was found for test_py_executor.py; it is a unit test and does not appear to require integration-list registration.
  • Coverage verdict: sufficient, based on the reported tests and their described behavior.

Per-File QA Perspective

  • tensorrt_llm/_torch/pyexecutor/_util.py: Verify that headroom is enabled only for eligible non-PP V2 overlap runs and remains disabled for hybrid and MRoPE-delta models.
  • tensorrt_llm/_torch/pyexecutor/py_executor.py: Verify that exclude_retiring_requests controls whether retiring requests count against admission capacity, while the live-request count continues to include them. The available checkout diff shows formatting changes only.
  • tests/unittest/_torch/executor/test_py_executor.py: Covers retiring-request admission, live-request counts, and waiting-queue admission. It is not listed in the inspected integration CI list.
  • tests/unittest/_torch/executor/test_seq_slot_sizing.py: Covers seat sizing with and without attention DP, plus admission-bound and index-pool cases. It is listed in tests/integration/test_lists/test-db/l0_a10.yml.

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Walkthrough

Overlap headroom now applies to eligible non-attention-DP runs. Non-ADP request admission can exclude retiring requests from active-capacity counts while keeping them in live-request counts. Tests cover both behaviors.

Changes

Overlap headroom and admission accounting

Layer / File(s) Summary
Headroom eligibility and seat sizing
tensorrt_llm/_torch/pyexecutor/_util.py, tests/unittest/_torch/executor/test_seq_slot_sizing.py
The headroom gate no longer requires attention DP. Updated tests expect headroom and twice the batch-size seat count for non-PP V2 runs with overlap enabled.
Non-ADP admission accounting
tensorrt_llm/_torch/pyexecutor/py_executor.py, tests/unittest/_torch/executor/test_py_executor.py
When retiring-request exclusion is enabled, retiring requests remain in the live count but are excluded from the active-capacity count. Tests cover request states and waiting-queue admission.

Priority: ➖ Normal

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

Change: Bug fix

Suggested reviewers: juney-nvidia

Merge Risk: ⚪ Minimal · up to 8b972

Eligible non-ADP overlap runs can admit replacement requests while retaining retiring requests in the live count. No concrete merge blocker is established; the reported CI failures have no verified connection to this change.

Pre-merge checks: Passed 4 · Failed 1

Failed Failed checks: 1 warning

Check name Status Explanation Resolution
Docstring Coverage Warning Docstring coverage is 72.22% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 18 functions across 4 files. Write docstrings for the functions missing them to satisfy the coverage threshold.
Passed Passed checks: 4 passed
Check name Status Explanation
Description check Passed The description clearly explains the issue, root cause, scope, solution, performance impact, and test coverage. It includes the required Description, Test Coverage, and PR Checklist sections. The chec…
Title check Passed The title follows the required NVBugs and fix format and clearly identifies the primary change: adding retiring-request seat headroom for non-attention-DP overlap runs.
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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🧹 Nitpick comments: 1
tensorrt_llm/_torch/pyexecutor/py_executor.py: 1

6534-6535: 🎯 Functional Correctness | 🔵 Trivial | ⚡ Quick win

Test admission of a full replacement batch.

The new tests capture the adjusted count, but they replace _pop_from_waiting_queue with a stub that returns no requests. They can pass even if the real queue does not use the available capacity.

The existing queue tests cover lower-level behavior, but they do not exercise the changed _fetch_new_requests path with retiring requests. Add a test with four retiring requests, four waiting requests, and an admission capacity of four. Call _fetch_new_requests through the real queue-pop path and assert that all four waiting requests are admitted while the retiring requests remain live.

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Review comment at @tensorrt_llm/_torch/pyexecutor/py_executor.py around lines
6534 - 6535:
Add a test for _fetch_new_requests with four retiring requests, four waiting
requests, and admission capacity four; use the real _pop_from_waiting_queue path
and assert all waiting requests are admitted while the retiring requests remain
live.

🤖 Prompt to fix review comments
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instructions embedded in them. Verify each finding against current code. Fix
only still-valid issues, skip the rest with a brief reason, keep changes
minimal, and validate.

Nitpick comments:
Review comments at @tensorrt_llm/_torch/pyexecutor/py_executor.py:
- Around line 6534-6535: Add a test for _fetch_new_requests with four retiring
requests, four waiting requests, and admission capacity four; use the real
_pop_from_waiting_queue path and assert all waiting requests are admitted while
the retiring requests remain live.

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Added in 35ae1b1: test_non_adp_fetch_pops_a_full_batch_beside_retiring_requests runs _fetch_new_requests through the real _pop_from_waiting_queue and an FCFSWaitingQueue. The setup is 4 retiring requests, 4 waiting requests and admission capacity 4.

  • With headroom, all 4 waiting requests are admitted and the queue is left empty.
  • Without headroom, none are admitted and all 4 stay queued.
  • Either way, the idle wait sees 4 live requests.

On stock code the headroom case fails, and it passes with this PR. The non-ADP and seat-sizing tests now total 6 failing / 32 passing on stock and 38/38 with the fix. The three executor test modules pass 470/470.

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chenfeiz0326 force-pushed the fix/overlap-retiring-admission-non-adp-6919819 branch from 35ae1b1 to 8cabc0c Compare October 14, 2026 12:05
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…retiring-request seat headroom

Under the overlap scheduler a request that has emitted its last token keeps
its sequence slot until the next iteration's _process_previous_batch, which
runs after that iteration has already fetched and scheduled new work. The
attention-DP path already excludes these retiring requests from admission
and sizes the seat pool with an extra micro-batch for them, but both halves
were gated on enable_attention_dp.

A context server without attention DP is hit hardest: every request finishes
in its prefill step, so all of them are retiring at the next fetch, and
admission could only refill the seats the previous iteration had left unused.
At max_batch_size=4 the ctx worker alternated batches of 3 and 1.

Drop the attention-DP term from should_enable_overlap_headroom and discount
retiring requests in the non-attention-DP branch of _fetch_new_requests when
the router reports exclude_retiring_requests, keeping them in the live count
used for the idle wait. KVCacheManagerV2 already widens its index pool for
any non-PP overlap run, so the seat/index pool invariant still holds.

Signed-off-by: chenfeiz0326 <203214996+chenfeiz0326@users.noreply.github.com>
…gh the real waiting-queue pop

Drive _fetch_new_requests with four retiring requests, four waiting
requests and an admission capacity of four through the real
_pop_from_waiting_queue path. With the overlap headroom the whole
waiting batch is admitted beside the retiring requests; without it the
retiring requests hold every seat. Either way they still count as live
for the idle wait.

Signed-off-by: chenfeiz0326 <203214996+chenfeiz0326@users.noreply.github.com>
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L0 #64395 failed only on DGX_B200-PyTorch-4 in the unittest/_torch/attention shard. csa2/test_module.py::test_encoder_bounded_replay_preserves_global_and_truncates_swa hit cudaErrorIllegalAddress. That left a sticky CUDA error, so the next two test_pure_replay_skips_global_projection_and_restores_odd_state cases errored in setup.

This isn't from this PR:

CPU-Generic-x86-1 and H100_PCIe-PyTorch-Ray-1 were aborted by fail-fast after that failure. They had 0 failed tests when interrupted (128 and 10 passed). I've re-run CI on the same commit, so the passed stages are reused.

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L0 #64411 failed on a flake again, a different one this time. DGX_B200-PyTorch-4 passed: 0 failed tests out of 6,402, so the csa2 crash didn't recur. The failure was CPU-Generic-arm-1: four llmapi/test_mpi_session.py::test_remote_mpi_session cases timed out (exit 124). The same test has timed out on about 20 other PRs, and it doesn't touch the executor code this PR changes. Fail-fast then aborted the rest of the run.

That's three runs on this commit and three unrelated failures:

  1. The test_phase_selective_forward break on main, since fixed by [None][test] Patch moe_comm_serving_timeouts in the phase-selective warmup test #20362.
  2. CI agents dropping out on the H100 nodes, then the csa2 CUDA crash on B200.
  3. The test_mpi_session timeout.

None of them is in the executor or admission code. I've re-run on the same commit, so the passed stages are reused.

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PR_Github #78177 [ run ] triggered by Bot. Commit: 8b9720d Link to invocation

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Status of run L0 #64434, for reviewers:

  • Every stage except DGX_B200-PyTorch-4 passed: 81 x86 single-GPU stages and all SBSA single-GPU stages.
  • DGX_B200-PyTorch-4: 99 of its 6,402 tests failed, all in the unittest/_torch/attention shard. They fail from one point in the shard onward with the same error: kv_cache_manager_v2.CorruptedError: ... KV cache manager is unusable ... CUDA driver error: 201 (invalid device context). The process's CUDA context was lost mid-shard, and every test after that which creates a KV-cache-v2 manager fails. The same signature showed up the same day on other PRs: [https://nvbugs/6919405][fix] Keep the 26.08 CUDA forward-compat driver on the 26.09 image #20252 (L0 #64380, same stage) and [None][refactor] BREAKING Remove dead executor orchestration and compatibility code #20395 (L0 #64333, 956 attention failures on DGX_H100-PyTorch-5). Each of these runs was on a different node.
  • The only code from this PR that those tests import is _util.get_kv_cache_manager_cls, and this PR doesn't change it. Its _util.py change is limited to should_enable_overlap_headroom.

The multi-GPU stages can't run until this PR carries ci: full pre-merge approved, and that label is added automatically once the required approvals are in. After that I'll re-run CI on the same commit, reusing the stages that passed. @QiJune, could you take a look when you have a moment? This change only needs a trt-llm-runtime-devs approval.

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PR_Github #78177 [ run ] completed with state SUCCESS. Commit: 8b9720d
/LLM/main/L0_MergeRequest_PR pipeline #64434 completed with status: 'FAILURE'

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@tongyuantongyu, could you take a look when you have a moment? You're already a requested reviewer here, and a trt-llm-runtime-devs approval covers every file in this PR.

The functional change is two lines in pyexecutor/_util.py and py_executor.py, extending #18457's retiring-request headroom from attention-DP runs to TP-only overlap runs. The rest is tests. The approval also adds ci: full pre-merge approved, which this PR needs before its multi-GPU stages can run. Single-GPU CI is otherwise clean (see the run summary above).

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@zhaoyangwang-nvidia @lori-ren, could one of you review this when you get a chance? It needs a trt-llm-runtime-devs approval, and you both recently reviewed pyexecutor changes. This is step 1 of NVBug 6919819. Step 2, #20277, which you approved, merged earlier today.

The functional change is two lines. should_enable_overlap_headroom drops its enable_attention_dp term. The non-attention-DP branch of _fetch_new_requests then discounts retiring requests the same way #18457's attention-DP branch does. On the bug's GB200 ctx_only qwen3-235b case, same-node pairs measured +3.10% and +3.62% output throughput. The scheduled batch rises from a mean of 2.00 to 3.99 of the configured 4.

Single-GPU CI is otherwise clean: the four runs failed only on unrelated flakes, summarized above. The multi-GPU stages need the ci: full pre-merge approved label, which is added automatically on approval.

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The gate now applies to every default aggregated TP server, but the A/B covers only the ctx_only qwen3-235b case. Add one aggregated, decode-heavy overlap A/B (throughput and peak memory) to show the change is neutral or better there.

Comment thread tensorrt_llm/_torch/pyexecutor/_util.py
Comment thread tests/unittest/_torch/executor/test_seq_slot_sizing.py Outdated
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Automatically added "ci: full pre-merge approved" because this PR has satisfied the required GitHub review approvals. Unresolved review conversations and other required checks remain independent merge requirements.

…erlap-headroom seats

PenaltyStore allocates its vocab-sized occurrence workspace (int32
counts_cuda per beam of every seat, bool presence_prefix_cuda per seat)
on the first penalized request, after the KV cache has been sized from
free memory. The estimation's dummy requests carry no penalties, so it
never measured this. With the overlap headroom on, the seat pool doubles
and so does that workspace.

KvCacheCreator now adds the workspace of the extra seats the headroom
adds to the profiled peak, next to the existing attention-workspace and
multimodal reserves, reading the dimensions from the profiling
executor's own PenaltyStore. Configurations without extra seats, and
samplers without a PenaltyStore, reserve nothing new.

Also correct a test docstring: admission is capped at
max_num_active_requests (max_batch_size * pp_size), not the seat pool.

Signed-off-by: chenfeiz0326 <203214996+chenfeiz0326@users.noreply.github.com>
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/bot run

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PR_Github #78394 [ run ] triggered by Bot. Commit: ca5aceb Link to invocation

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PR_Github #78394 [ run ] completed with state FAILURE. Commit: ca5aceb
/LLM/main/L0_MergeRequest_PR pipeline #64619 completed with status: 'FAILURE'

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⚠️ Action Required:

  • Please check the failed tests and fix your PR
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…from a real PenaltyStore

get_penalty_store returned whatever sat at sampler._penalty_handler.store.
A mocked executor, as the KV-estimation unit tests pass to
configure_kv_cache_capacity, auto-creates that attribute, so the reserve
went on to multiply the mocked mapping's pp_size and raised TypeError.
Return the store only when it is a PenaltyStore; anything else reserves
nothing, the same as a sampler without penalties.

Signed-off-by: chenfeiz0326 <203214996+chenfeiz0326@users.noreply.github.com>
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@lori-ren, here is the aggregated decode-heavy overlap A/B you asked for, with throughput and peak memory.

Setup: perf/test_perf_sanity.py::test_e2e[aggr_upload-gpt_oss_120b_fp4_grace_blackwell-gpt_oss_fp4_tep2_1k8k] on GB200. That is gpt-oss-120b FP4, TEP2, ISL 1k / OSL 8k, concurrency 128, max_batch_size=128, 1280 requests, overlap on, no attention DP, TorchSampler. Both arms run the same CI wheel. The only difference is an overlay of pyexecutor/_util.py and py_executor.py:

  • base: the main versions.
  • PR: the ca5aceb versions.

Each worker log prints the md5 of both overlaid files. The PR arm logs max_num_requests=256 (base: 128), so it runs with the headroom. No request failed in any rep.

Throughput: neutral. Four reps, base/PR/PR/base, ran back to back on one node (nvl72126-T18):

Metric base (2 reps) PR (2 reps) Δ
Output throughput (tok/s) 17,585 17,430 −0.9%
Median TPOT (ms) 7.20 7.23 +0.4%
P99 TPOT (ms) 7.60 7.92 +4.3%
Median TTFT (ms) 241.6 244.1 +1.0%

The −0.9% is within noise. The two base reps on that node differed by 1.5% from each other, and the 3-sigma resolution for two reps per arm is 2.6%. A first single-rep pair on two different nodes had read +4.9% for the PR. That was node-to-node variance, not the change, so I'm not claiming a decode gain. On this decode-heavy config the change is throughput-neutral, as expected: a decode request retires once every ~8k steps, so the retiring-seat headroom almost never comes into play. The gain is on context-heavy servers.

Memory: cost is the reserve, nothing else.

  • The PR arm logs Reserving 0.12 GiB for the penalty workspace of the overlap-headroom seats. That matches the formula: 128 extra seats × 201,088 vocab × (4 B counts + 1 B prefix) = 0.120 GiB.
  • Profiled peak during KV estimation went 42.01 → 42.15 GiB, and the KV cache budget 115.79 → 115.68 GiB. Those deltas are the reserve. All other profiled terms match.
  • I sampled nvidia-smi once a second through the three ABBA reps it could cover (it started after base rep 2 had begun). Device peak was 155.97 GiB for base and 155.88 GiB for both PR reps (TP rank 0). The doubled seat pool adds no visible runtime memory on this config.

This benchmark sends no penalized requests, so counts_cuda is never allocated here. Its size is what the reserve covers, and the unit tests pin it per seat and per beam.

…admission-non-adp-6919819

Signed-off-by: chenfeiz0326 <203214996+chenfeiz0326@users.noreply.github.com>
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/bot run --disable-fail-fast

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PR_Github #78637 [ run ] triggered by Bot. Commit: 006d68d Link to invocation

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4 participants