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Tooling: accelerate exact frame-pair enumeration with unchanged D/E/H checks - #1099

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Mister-Meeseeks merged 1 commit into
CrocSwap:mainfrom
woklerx:research/sprint30-r19-s93
Oct 13, 2026
Merged

Mister-Meeseeks merged 1 commit into
CrocSwap:mainfrom
woklerx:research/sprint30-r19-s93

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@woklerx woklerx commented Oct 13, 2026

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PR968 repeatedly scans eight-element neighborhood lists during its complete
frame-pair split census. An exact mask representation preserves the full
ordered solution stream and makes this kernel 4.57x faster in three paired
trials. A separate D/E/H replay is 2.97x faster on the recorded Windows run;
this is not a whole-repository timing claim.

Both paths retain all 1,260 frames, 7,168 decoders, 57,344 term-rank checks,
25 attainment cases and six inherited controls. Ten additional controls
check source binding, malformed inputs, stream tampering and preservation
of source assertions under an optimized caller. The complete canonical
receipt matches; benchmark timing is excluded from mathematical equality.

Reproduce: python -I -O -B research/frame-pair-enumeration-fast-seed93/verify.py.
Only this new package is added. Sections A/B/C/F/G, native suppliers and
the full theorem are outside this replay. No new kappa is claimed.

Credit themilkman216's PR968 enumeration and proof checks; parallel PR1071
and PR1077 address different mathematical questions. Prepared for @woklerx
with substantial OpenAI Codex assistance. Apache-2.0.

@Mister-Meeseeks
Mister-Meeseeks merged commit f02fd94 into CrocSwap:main Oct 13, 2026
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cursor Bot pushed a commit to VictorLiwentao/integer-mult-bounds that referenced this pull request Oct 15, 2026
Promote woklerx CrocSwap#1099 / research/frame-pair-enumeration-fast-seed93 into
research/complex-frame-pair-decoders/verify.py:frame_pair_solutions with
identical D/E/H receipts. Demote dependent VERIFY live pins to provenance,
retarget selected-p104 E8 model to vendored baseline, and vendor pairwise
bytes for the historical opt-in adapter.

Prepared by Wentao Li with substantial AI assistance.
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2 participants