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Claude
4402775ed2
Attempt 4 (phase0-tokei-002, class 3, ACCEPTED — first auto-accept): every file was read through encoding_rs_io's DecodeReaderBytes via generic read_to_end, which zero-fills every grown buffer chunk (~221MB memset/run, 8.5% of Ir) and grows without a size hint. Patch: fs::read with a BOM-gated fallback to the identical decode path (a UTF-8-BOM file transcodes invalid sequences, so the fallback is required for equivalence). Gates: golden byte-identical; differential fuzz old-vs- new binaries 4,332 iterations (BOM grid, invalid UTF-8, binary junk, randomized) zero divergence; 250 upstream tests green; ASan+LSan clean with ASan-run output hashing to golden. Bench: +9.9% [8.0%, 12.7%]. Attempt 5 (phase0-tokei-003, ship tree, ACCEPTED): stacks fat LTO+cgu=1 (real +1.6% standalone but under threshold, phase0-tokei-001) on the accepted patch; benched as a whole vs pristine: +10.4% [8.5%, 12.0%]. Median clears the Phase 0 exit bar; CI lower bound 8.5%. Case study written (results/phase0/case-study-tokei.md), ledger at 5 attempts, CLAUDE.md phase line moved to Phase 1, next hypotheses logged (tokei class-5 byte-skip table; comrak class-3 arena). Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01EcKPWQ3MQD4NdEHwar96u2
74 lines
3.0 KiB
Markdown
74 lines
3.0 KiB
Markdown
# peltier.io
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Spot cooling for hot paths. A profile-guided optimization agent that only ships wins it can prove.
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hotpath finds the 10–90% left on the floor between "the compiler" and
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"hire a perf consultant," with two properties no consultant offers:
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**verified equivalence** (a change provably preserves behavior or is
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discarded) and **self-verifying ROI** (the value claim is a stopwatch on
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trusted infrastructure, not a survey).
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Full design: **[SPEC.md](SPEC.md)**.
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## Layout
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```
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crates/ Trust layer (agent has NO write access — SPEC §10)
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bench-runner/ Interleaved A/B timing, bootstrap CIs, A/A calibration
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diff-test/ Equivalence gates, corpus hash-pinning, per-target policy
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ledger/ Append-only SQLite attempt ledger (enforced by triggers)
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report/ ROI math: speedup CI → cores → dollars, caveats included
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agent/ Untrusted proposer (Claude Agent SDK, Python)
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playbook/ Optimization classes 1–7, tried strictly cheapest-first
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config/ accept.toml (thresholds), pricing.toml (ROI inputs)
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targets/ Per-target checkouts — the only agent-writable path
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corpora/ Hash-pinned golden-replay inputs (read-only to agent)
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results/ Calibration evidence, per-engagement outputs
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```
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## Quick start
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```sh
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cargo test --workspace # trust-layer unit tests
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just aa # A/A self-test: must yield a null verdict
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just compare "cmd-a" "cmd-b" # interleaved A/B with bootstrap CI
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```
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## Status
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**Phase 0 complete** (see SPEC §5). Five attempts in the ledger across
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two pinned targets (comrak 0.53.0, tokei 14.0.0), A/A-calibrated,
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every number with CI and workload:
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- **tokei +10.4% median [95% CI +8.5%, +12.0%]** — read-path buffer
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zeroing eliminated + fat LTO, byte-identical, 4,332-iteration
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diff-fuzz clean, sanitizers clean, auto-accepted
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(`results/phase0/case-study-tokei.md`). Meets the Phase 0 exit bar.
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- comrak +4.6% [+3.3%, +5.8%] — mimalloc swap, `needs-human-review`
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on an LSan reachability flag (`results/phase0/case-study-comrak.md`).
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- Two null/sub-threshold results correctly rejected and logged.
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Next: Phase 1 trust-layer hardening (containers, perf, automated
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calibration, gate orchestration, agent IPC).
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Done:
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- Workspace with the four trust-layer crates; core statistics
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(interleaved scheduling, bootstrap ratio CIs, CI-lower-bound accept
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rule), append-only ledger schema with mutation-refusing triggers,
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corpus hash-pin verifier, equivalence-policy parser, ROI formulas —
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all unit-tested.
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- bench-runner CLI: whole-program `compare` and `aa` modes with env
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fingerprinting.
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- Playbook classes 1–7; agent tool contract and prompting spine.
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Next (Phase 1 exit criteria):
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- `perf stat` counters + max RSS + RAPL capture per run.
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- Automated A/A calibration sessions and regression-injection self-test
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recorded to `results/calibration/` (<5% FP, ≥95% detection).
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- diff-test orchestration end-to-end on two real targets; harness IPC
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for the agent tool surface.
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## License
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GPL-3.0-or-later — see [LICENSE](LICENSE).
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