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fix(server): serve an over-budget item between cheaper batches - #656
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Refs superlinked#390 Starvation was cost-order, not inference time: cheaper items kept filling max_batch_cost, so a high-cost extract request never reached the front even though the GPU work itself is only seconds.
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Check name Status Explanation Description Check Check skipped - CodeRabbit’s high-level summary is enabled. Title check The title clearly and concisely describes the main change: serving an over-budget item between cheaper batches. Linked Issues check Check skipped because no linked issues were found for this pull request. Out of Scope Changes check Check skipped because no linked issues were found for this pull request.
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Review comments at @packages/sie_server/tests/core/test_batcher.py:
- Line 1301: Update the test around `clock.monotonic` so it saves the real clock
and assigns it to the running event loop’s `time` method before monkeypatching
`time.monotonic`. This keeps `asyncio.wait_for` able to enforce its timeout if
`get_batch` stalls.
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an item is promoted after 15 ms (max_batch_wait_ms), so under load nearly every batch is “oldest plus cheapest”. That affects encode and score too, not just extract. There are no throughput numbers, the Rust sidecar batcher isn’t changed, and the tests can hang. Trying the #648 setting on GLiClass would be a better first step.
… window" The 15ms promotion is reverted because it reschedules encode and score, not only extract. This reverts commit 70408e9.
…-large-v1.0 Refs superlinked#390 This follows the superlinked#648 profile setting instead of a global batcher change.
YeonwooSung
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The scheduler change is reverted for the reason in the review: promoting a request after 15 ms reschedules encode and score, not only extract, and under load nearly every batch is the oldest item plus cheaper work. The replacement is the profile setting from #648. Adaptive batching is turned off on knowledgator/gliclass-large-v1.0 only, and the other GLiClass catalogs are unchanged. packages/sie_server/tests/core/test_batcher.py passes as on main (89 passed). The shipped model schema check passes, and the GLiClass test that loads the profile YAML still passes. No throughput numbers are claimed. |
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Thanks for reverting the scheduler change. The PR is now the 4-line adaptive_batching.enabled: false on knowledgator/gliclass-large-v1.0, which is the same shape as #648. To merge it we need the evidence #648 came with:
- Measurements. #648 had a one-L4 benchmark (base vs change at several in-flight levels over steady intervals) and an output-equivalence check. Could you run the same protocol for this model, plus the #390 reproduction with timeout counts before and after? Without that we cannot tell whether this resolves #390, so "Refs #390" fits better than a fix claim.
- Scope. 20 profiles under
packages/sie_server/models/use the GLiClass adapter, and only one changes here. If the numbers hold, please either apply it to all of them or explain why only this one.
Please also trim the description to the final change, since it still opens with the reverted scheduler work.
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The 15 ms scheduler promotion stays reverted. Measurements. Not run, and none are claimed. #648 used one L4, base vs change, several in-flight levels, steady intervals, and an output-equivalence check. #390 also needs timeout counts before and after. This machine has no NVIDIA GPU, so that protocol cannot be run here. No benchmark was run. There are no throughput, latency, or timeout numbers for this change. Scope. 20 catalogs under Description. It now describes only that YAML change and uses |
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The bounded L4 comparison reproduced the mixed-load stall, and this profile-only change did not resolve it. Both arms had one 300-second read timeout in each of the The public harness and method ran the real SIE server and The fixed mixed phase used 480 seconds of arrivals: 12 cheap one-item lanes and four 24-item heavy lanes (
Latency columns describe successful calls only; the timeouts are retained separately. Both candidate long requests were admitted within 11 ms but dispatched zero of 24 items before the timeout. First dispatch was at 482.63 seconds and 497.43 seconds, after the cheap arrival window ended. More than 1,600 cheap requests completed during the final 30 seconds before each timeout. All four timed-out requests across both arms eventually completed on the server, 195–212 seconds after the client deadline; no request remained unresolved at shutdown. The steady phases had eight sequential warmups each. Rates below count actual successful completions during the arrival window; all submitted calls completed successfully, including those finishing in the drain.
This was one ordered baseline→candidate pair, not statistical throughput equivalence. Candidate completion throughput was +2.57% at C1, −3.07% at C8 and −0.67% at C32. All successful measured responses passed the prospectively fixed absolute 0.002 FP16 comparison, including direct candidate-to-baseline checks, with exact item count/order, labels, chosen values, model identity and no item errors. Maximum observed numeric difference was 0.001953125. This concerns the fixed fixtures, not classification quality. The run retained all outcomes and used unchanged ceilings: runner 3,900 s, operator 4,500 s, provider 4,800 s, outer guard 5,100 s and startup 300 s. Actual runner time was 2,044.91 s. Both servers and all ten SDK processes exited; the owned app was stopped and independently verified with zero containers. The complete 92-member archive (29,105,457 compressed bytes; 282,560,100 raw bytes) is retained with SHA-256 Only one of the 20 GLiClass profiles is changed by this PR, and even that profile retains the reproduced long-item failure. The next step is a separately reviewed scheduler progress fix and deterministic starvation controls, not extending this setting to other models. The existing human requested-changes review is unchanged; this result does not support merging the profile-only proposal as a resolution of #390. |
The L4 comparison showed that disabling the controller on knowledgator/gliclass-large-v1.0 does not dispatch the over-budget rows in superlinked#390. The profile matches main again. Refs superlinked#390
Cost-sorted packing never reaches an item above the configured batch cost while a cheaper item is waiting, so a cheap stream holds it until the stream ends. Those items now take turns with one cheaper batch, and the over-budget batch is that item alone. Items that fit the configured cost stay on cost order. This does not promote by wait time. Refs superlinked#390
YeonwooSung
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The profile opt-out is removed. The L4 run showed it leaves the long rows undispatched, and I am not treating that run as a reason to widen the flag. The replacement is in Tests cover the 24-row case with cheaper rows still arriving, the fitting-item cost order, a raised live budget, and a seeded bound. |
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Actionable comments posted: 1
- 🪄 Fix comments: Fix CodeRabbit comments on this PR
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Inline comments:
Review comments at @packages/sie_server/src/sie_server/core/batcher.py:
- Around line 478-504: Reset _last_over_budget_batch whenever extraction or
drain_pending() leaves the queue empty, so _over_budget_turn() starts the next
queue using its oldest item rather than stale lane history.
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A finished batch left the lane flag set, so the next queue served a cheaper batch before an older over-budget item. Clearing the flag when the queue is empty, including drain_pending, makes that queue follow its oldest item. Refs superlinked#390
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An item whose cost is above the configured
max_batch_costnever joins a cost-sorted batch while a cheaper item is pending. Onknowledgator/gliclass-large-v1.0that limit is 16,384, and the long separate-group rows in #390 cost about 22,355–27,314, so a stream of cheaper rows holds them until the stream ends.BatchFormernow alternates one cost-sorted batch of items that fit the configured limit with the oldest over-budget item, served alone. The first batch follows the oldest pending item. An over-budget item with k over-budget items ahead of it waits for at most k + 1 cheaper batches. Items at or under the configured limit stay on cost order, including when cheaper items fill the budget in front of them. Lane membership uses the budgetBatchConfigwas built with, so a later adaptive change to the live limit does not pull an over-budget item into the cheaper batch.runs_aloneis unchanged.The
adaptive_batching.enabled: falseprofile change is removed. The L4 comparison showed it does not dispatch these rows.This is the in-process
BatchFormerpath. The Rust sidecar batcher is unchanged. There is no new GPU measurement here, so this does not claim the 300-second timeout is gone.Refs #390
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