perf(decoding): read predefined sequence tables in place; report benchmarks from the fastest sample

[polaz]

Two things that turned out to be the same investigation: a dashboard alarm that did not reproduce, and the real cost sitting underneath it.

The decoder change

A block whose LL/ML/OF mode byte says Predefined copied the cached default table into the per-frame scratch. The copy moves the whole fixed-size decode array (512 entries, 4 KiB per axis) although only the live span matters (64 entries for LL/ML, 32 for OF), and although the source is an immutable process-wide cache that never needs duplicating. Upstream points its axis at the static default table instead.

The cost is per block and independent of frame size, so it dominates small frames. A profile of the decompress-dict / small-4k-log-lines / level_16_btopt shape (47-byte frame, 4096 bytes out; LL and OF in Repeat mode reading the dictionary, ML in Predefined mode) attributed 10.8% of the whole decode to that single 4 KiB copy.

The per-axis copy-on-write source already distinguished the local table from the dictionary's, so this adds a third state for the predefined cache and the axis costs a flag write. The entropy snapshot path still materialises every axis into owned local storage, so exported state stays self-contained, and a Repeat-mode block keeps reading whatever the axis had, which for a predefined axis is that same cache. The Huffman literals table has no predefined form in the format, so it keeps the two-state source and the two domains no longer share an enum.

Four smaller things ride along, all op reductions with no measurable time change and none of them claimed as a speedup: each axis is resolved once instead of twice (the second call was for accuracy_log, and for a predefined axis that repeated a OnceLock probe); the offsets long-share is named rather than read back out of the cache, which had made the offsets axis probe twice per block; the axis keeps the resolved table rather than re-deriving it, so the Repeat blocks that follow a Predefined one stop re-entering the lock for a table that cannot change; and the cached tables are wrapped in the same aligned container the per-frame ones use, so borrowing one in place keeps the placement the copy used to give it.

The measurement change

The alarm that started this (0.1680 (-83.20%) on that cell) does not reproduce in any shape. Chasing why led to the pipeline itself.

Criterion takes flat samples of a few milliseconds each. Scheduler interference can only ADD time to a sample, so the distribution is skewed right: on an idle host that cell spans 728 to 947 ns, with the Rust and libzstd arms skewed alike (max/min 1.30 and 1.25), so it is the environment and not the code. The printed point estimate is a central statistic over that tail, and run-benchmarks.sh read it while discarding the (+/- X) printed beside it. Every downstream artifact was therefore one tail-contaminated number with no uncertainty attached, compared against the previous run's with no confirmation. A single sample stalled for tens of milliseconds out of thirty is arithmetically enough to produce the reported value, and nothing in the pipeline would have rejected it.

So the run now reads criterion's own per-sample data and reports the minimum. Six runs of one binary, spread by estimator:

	min	median	mean
ours	0.20%	1.42%	1.54%
libzstd	2.00%	1.69%	1.81%

The minimum also agrees with a standalone timing loop over the same code (725 to 740 ns across six whole-process runs of 2M frames), which the central estimate misses by four to five percent. The two harnesses already measured the same quantity; only the statistic differed.

What this does not fix, and why each cell now publishes its spread instead of hiding it: a ratio also carries whole-distribution shifts of an arm. One run in six had libzstd sitting 5% high at every quantile, minimum included. Across four full-shard runs the ratio spread was 5.75% from minimums, 7.33% from medians, 21.62% from maximums — the ordering holds, but the floor is set by those shifts rather than by the tail. Their cause is worth its own issue.

Sample count, measurement budget, fixtures, the bench harness and the emitted fields are unchanged, so the graphs keep their shape. There is no per-row fallback to the printed estimate: a ratio pairs two implementations, so one side falling back would divide a central estimate by the other side's minimum and manufacture a delta out of nothing. Any benchmark whose samples cannot be read stops the run and is named.

The spread is rendered where the question it answers gets asked, and nowhere else: in the tooltip of a hovered point on the delta chart, on the lines of the deviation list, and as median and maximum columns in the generated timing table. It is deliberately not drawn on the plots, which have enough on them already, and nothing is withheld from the deviation list: that list exists to pick the level and fixture worth attacking next, so it ranks by lag against libzstd and lets each line's spread say whether the number is solid enough to spend a day on.

The wasm harness had the same defect and now reports the same statistic. It collected up to 200 single-operation samples and returned their median, so the two dashboard sections were reading different statistics from the same page.

Reporting the fastest there needed one more thing, because that harness bounds a sample run by time rather than by count. The fastest is an extreme order statistic, so its expected value falls as the count rises, and under a fixed budget a quick arm fits hundreds of operations where a slow one fits a handful: comparing their minima directly would hand the quick arm an advantage unrelated to its code, worst on the 8 MiB fixtures at high levels. Every arm of a comparison is therefore sampled first and all of them reduced over the count the slowest one reached, both for the engines against each other and for streaming against one-shot.

The published series stays joined across this change, deliberately. Points measured before it sit a few percent away, so the first snapshot after the merge shows a one-time step on every timing cell. Nothing here versions the series, stamps the estimator onto a record or drops retained rows to hide that: the series is read to see that a cell was 0.168 and is now 0.60, which needs the points connected, and severing them at the commit where the measurement improved would destroy real history to avoid a step whose cause is this PR.

What this does to the reported outlier

The cell that prompted this was published at 0.1680 (-83.20%), which reads as six times slower than libzstd. It is not: the same cell measures 0.536 to 0.625 across four independent runs in two harnesses on post-merge code, its neighbours show no step (L14 0.620, L15 0.642, L17 0.611), and its own history on the dashboard reads 0.650, 0.647, 0.706 before that one snapshot.

The raw samples settle it. For that cell in one run, ours spans 728.1 to 946.8 ns and libzstd 427.4 to 533.3 ns. Our slowest sample against their fastest is 0.451, so 0.168 is not reachable from the distribution at all: it needs about 2.7 us on our side, a value no sample holds. A central statistic could be dragged there by one stalled sample out of thirty; a minimum cannot, since it would need all thirty to be slower.

Run end to end through the updated pipeline, that cell now publishes 0.6029 and 0.6091 — about 1.66 times slower, which is the real standing gap. The figure also came out ABOVE the old central estimate (0.536 to 0.570), because our arm's tail was heavier than libzstd's and the central statistic had been understating us.

What remains is a disturbance covering one arm's whole measurement window while sparing the other's. The arms run back to back, roughly half a second each, and a minimum needs only one clean sample out of thirty per arm, so this requires a disturbance matched to one arm in both length and phase. The residual uncertainty in a published ratio is then the structural drift of a whole run, measured at about 2% per side on an idle host.

Measurements

Instruction counts come from callgrind, which needs no PMU: the bench host has no passthrough, so perf stat -e cycles,instructions answers No supported events found and task-clock is the time gate. Every timing row is three interleaved runs of two prebuilt binaries in one session, listed in order taken, because a single criterion reading of these cells is exactly what this PR stops trusting. ratio is libzstd time over ours: higher is better, 1.0 is parity.

Instructions per frame

Two frame counts per binary (3000 and 9000) fit a line, so the intercept absorbs process startup and the slope is the per-frame cost. The intercepts agree to 155 instructions out of 527k, which is the check that the fit is sound.

	main	branch	delta
per frame	6417.0 Ir	5979.0 Ir	-438.0 (-6.8%)
startup	527122 Ir	526967 Ir	-155

decompress-dict / level_16_btopt / small-4k-log-lines

run	ours	libzstd	ratio
main	851 ns	458 ns	0.538
branch	759 ns	460 ns	0.606
main	820 ns	467 ns	0.570
branch	762 ns	476 ns	0.625
main	842 ns	457 ns	0.543
branch	760 ns	439 ns	0.578

The two sets do not overlap, and the libzstd side stays inside 457 to 476 across all six runs, so the machine held still and our side is what moved.

decompress / level_16_btopt / small-4k-log-lines / rust_stream

Same fixture without a dictionary, where every axis that is not FSE-compressed is predefined.

run	ours	libzstd	ratio
main	3253 ns	2164 ns	0.665
branch	2614 ns	2098 ns	0.803
main	3247 ns	2168 ns	0.668
branch	2533 ns	2065 ns	0.815
main	3076 ns	2111 ns	0.686
branch	2519 ns	2092 ns	0.830

decompress-dict / level_16_btopt / small-10k-random (control)

No Predefined axis, so the change provably cannot run on it. Flat, which is what makes the two tables above attributable to the change rather than to code layout.

run	ours	libzstd	ratio
main	2073 ns	1013 ns	0.489
branch	2018 ns	991 ns	0.491
main	1974 ns	1010 ns	0.512
branch	2020 ns	968 ns	0.479
main	2025 ns	971 ns	0.480
branch	1980 ns	988 ns	0.499

Paired A/B on the dedicated decode loop

Three interleaved rounds of perf stat -r 5 -e task-clock, 300k frames, outside criterion.

arm	main	branch
small-4k-log-lines (Predefined ML axis)	845 / 847 / 825 ns	752 / 727 / 741 ns
small-10k-random (control)	1961 / 1991 / 2002 ns	1963 / 2015 / 1969 ns

The saving of about 99 ns per frame matches the roughly 91 ns the profile attributed to the copy: two independent methods landing on the same number.

The four follow-ups, measured separately

Interleaved whole-process runs, both fixture shapes, on the arm each one can actually reach.

arm	before	after
single-block 4 KiB frame, 6M frames per run	701.67 to 725.00 ns	696.67 to 721.67 ns
multi-block 1 MiB frame, 40k frames per run	67.25 to 68.25 us	67.25 to 69.50 us

Every range overlaps, so no time change is established in either direction. The multi-block shape is the one where keeping the resolved table can pay at all, since the saving is on the Repeat blocks that follow a Predefined one and a 47-byte frame has exactly one block; the arithmetic says three atomic loads against roughly 150000 cycles of block decode, which is far below what any timer here resolves. They are kept for the work they remove and the invariant they restore, and reported as that. An earlier lower-resolution pass over the first pair appeared to show a gain; it did not survive the longer runs.

The remaining gap on the dict fixture is the copy of the 4096 output bytes itself (extend_from_within_unchecked, repeat_from_dict and the memmove in repeat_in_chunks are about 30% combined), which is the ground #507 covers.

Testing

• cargo nextest run --workspace --features hash,std,dict-builder: 1207 in the library crate, all passing
• cargo test --doc -p structured-zstd --features hash,std,dict-builder: 37 passed
• cargo clippy -p structured-zstd --all-targets --features hash,std,dict-builder -- -D warnings: clean
• cargo check -p structured-zstd --target thumbv7em-none-eabihf --no-default-features: clean (the no-std path keeps building the table locally, since the cache needs OnceLock)
• Three new tests: two assert the zero-copy contract by pointer identity, which is the only assertion that separates reading in place from copying (one for a Predefined-mode block, one for a Repeat-mode block following it), and one pins the named long-share against the builder.
• The CI script was run end to end on the bench host against a prebuilt binary: 60 of 60 benchmarks joined to their samples, and the published record carries both arms' min, median and max.

Closes #512
Closes #514

Summary by CodeRabbit

• Performance

  • Improved decoding efficiency when handling standard compression tables.

• Benchmarking

  • Benchmark reports now use fastest per-sample timings for more reliable comparisons.
  • Reports include timing spread and sample counts.
  • Benchmarks with missing sample data are skipped and reported as errors.
  • Benchmark results now distinguish timing methodologies for consistent comparisons.
  • Disabled plot generation and improved temporary-file cleanup.
  • Dashboard charts display sample-noise details in statuses and tooltips.

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📝 Walkthrough

Walkthrough

The change enables in-place access to cached predefined FSE tables and preserves those sources across Repeat mode. Benchmark pipelines now use minimum sample timings, publish sample spreads, reject incompatible or missing data, and display sample-noise information.

Changes

Predefined FSE table handling

Layer / File(s)	Summary
Sequence-table source tracking zstd/src/decoding/scratch.rs	FSE scratch tracks local, dictionary, and predefined sources independently for each sequence axis. Accessors resolve aligned cached tables under std.
Decoder source selection zstd/src/decoding/sequence_section_decoder.rs	Predefined modes select cached LL, OF, and ML tables under std. no_std modes mark rebuilt tables local. Decoder initialization reuses resolved table references.
Source behavior tests zstd/src/decoding/sequence_section_decoder/tests.rs	Tests verify zero description bytes, cached table identity, OF long-share propagation, and Repeat-mode preservation.

Benchmark sample reporting

Layer / File(s)	Summary
Criterion sample capture and parsing .github/scripts/run-benchmarks.sh	The runner stores Criterion samples in a temporary directory, computes minimum, median, maximum, and count values, and fails when sample data is missing.
Wasm sample estimation and compatibility zstd-wasm/bench/bench.mjs, .github/scripts/parse-wasm-bench.py, .github/scripts/merge-wasm-bench.py	Wasm timings use fastest samples over a common sample count. Records carry an estimator, and merges exclude records from other estimators.
Benchmark payload propagation .github/scripts/run-benchmarks.sh, .github/scripts/merge-benchmarks.py	Timing, speed, throughput, and merged records include sample spreads and retain only sample-min timing rows.
Dashboard sample-noise display .github/bench-dashboard/index.html	The dashboard computes sample-tail percentages and displays them in status text, chart tooltips, and introductory text.

Priority: ➖ Normal

Estimated code review effort: 4 (Complex) | ~60 minutes

Change: Refactor · Severity of issue fixed: Medium

Sequence Diagram(s)

Predefined FSE table selection

sequenceDiagram
  participant SequenceSectionDecoder
  participant FSEScratch
  participant PredefinedTableCache
  SequenceSectionDecoder->>FSEScratch: process predefined or Repeat modes
  FSEScratch->>PredefinedTableCache: resolve cached LL, OF, and ML tables
  PredefinedTableCache-->>FSEScratch: return table references and OF long-share
  FSEScratch-->>SequenceSectionDecoder: provide tables for sequence decoding

Loading

Benchmark sample reporting

sequenceDiagram
  participant Criterion
  participant BenchmarkRunner
  participant BenchmarkMerger
  participant Dashboard
  Criterion-->>BenchmarkRunner: write benchmark and sample data
  BenchmarkRunner->>BenchmarkRunner: calculate sample minimum and spread
  BenchmarkRunner-->>BenchmarkMerger: publish estimator and sample fields
  BenchmarkMerger-->>Dashboard: retain compatible records
  Dashboard->>Dashboard: display sample-tail notes

Loading

Merge Risk: 🔵 Low · up to 54fbe

Existing Wasm ratio history can disappear from the dashboard after this update. Preserve ratio records independently of timing-estimator filtering before merging.

🚥 Pre-merge checks | ✅ 6 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 70.59% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 34 functions across 8 files. (1 skipped: …	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (6 passed)

Check name	Status	Explanation
Linked Issues check	✅ Passed	The stated objectives are addressed by the predefined-table changes, benchmark updates, estimator separation, sample validation, and reported tests.
Out of Scope Changes check	✅ Passed	The decoding and benchmark changes match the PR objectives. No unrelated changes are identified in the provided summary.
Linked Issues check	✅ Passed	Issue #512 coding requirements are met. SeqTableSource::Predefined lets FSE accessors borrow immutable cached tables without copying. Predefined axes resolve once and Repeat mode retains the cached …
Out of Scope Changes check	✅ Passed	The decoder source, aligned cached-table representation, source reuse, and pointer tests support issue #512. The Criterion parsing, join validation, spread publication, dashboard rendering, wasm sampl…
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title clearly summarizes both primary changes: in-place predefined sequence-table access and fastest-sample benchmark reporting.

Full details: Docstring Coverage

Explanation

Docstring coverage is 70.59% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 34 functions across 8 files. (1 skipped: 1 unsupported.)

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