mirror of
https://github.com/bdbrown4/peltier.io.git
synced 2026-11-07 19:08:27 +00:00
Claude
03113312ad
phase3-cjson-002 (class 5+3): stack-buffer number parsing + strtod round-trip replacing sscanf. +8.85% median, 95% CI [+7.5%, +10.0%] on the C target, banked. 100% audit: byte-identical golden replay, independent ASan+UBSan clean, 10k-input differential fuzz 0 divergences, patch bounds/free-gating verified by eye. - verdict: an infrastructure sanitizer-BUILD failure (missing runtime, broken toolchain) now caps the accept at needs-human-review and logs it, instead of crashing the verdict and losing a measured bench. - results/phase3/: four public case studies (tokei class-5 wins; build flags + allocators; the comrak caught false-accept; the cJSON cross-language proof) + README. Compound-speedup claim stated as an approximation, not a measured figure (CIs don't multiply). - .gitignore: cjson build-artifact dirs. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01EcKPWQ3MQD4NdEHwar96u2
51 lines
2.4 KiB
Markdown
51 lines
2.4 KiB
Markdown
# Case study 2 — cheap wins first: build flags and allocators
|
|
|
|
**The playbook's ordering principle (SPEC §3.3, CLAUDE.md
|
|
non-negotiable #3): build flags → LTO → PGO → allocator swap → *then*
|
|
code changes.** The cheapest classes are tried first because they carry
|
|
the lowest cost-per-attempt and the lowest risk. Two of them produced
|
|
Phase-0 results that frame the whole project's discipline.
|
|
|
|
## Class 1 — link-time optimization (tokei) — ACCEPTED
|
|
|
|
`phase0-tokei-003`: set `lto = true` (fat LTO, up from `thin`) and
|
|
`codegen-units = 1` in tokei's release profile.
|
|
|
|
- **Speedup: 1.104 median, 95% CI [1.085, 1.120]** vs the pristine
|
|
`thin`-LTO baseline.
|
|
- Byte-identical golden replay; no source change, so equivalence is by
|
|
construction (same code, different codegen). Auto-accept tier.
|
|
- A pure build-config win worth **+10%** — the cheapest possible class,
|
|
and on this target the single largest individual increment.
|
|
|
|
The lesson the ledger enforces: you do not go hand-optimize a hot loop
|
|
before you have tried turning on the optimizer's own switches.
|
|
|
|
## Class 2 — allocator swap (comrak) — NEEDS-HUMAN-REVIEW
|
|
|
|
`phase0-comrak-002`: swap the global allocator to
|
|
[mimalloc](https://github.com/microsoft/mimalloc).
|
|
|
|
- **Speedup: 1.046 median, 95% CI [1.033, 1.058]** — a real, CI-clean
|
|
+4.6% on comrak's Pro Git render.
|
|
- Byte-identical golden replay. And yet the verdict is **not
|
|
`accepted`** — it is **`needs-human-review`**.
|
|
|
|
Why: an allocator swap changes the process's memory behavior globally.
|
|
It is exactly the class of change SPEC §8 routes to a human — not
|
|
because this instance is wrong, but because "the benchmark got faster"
|
|
is not sufficient evidence that a global allocator change is safe under
|
|
every workload, fragmentation pattern, and concurrency scenario the
|
|
target will meet in production. The pipeline measured a real win and
|
|
then **refused to auto-ship it**, tagging it for a human ruling instead.
|
|
|
|
## What the pair demonstrates
|
|
|
|
The cheap classes are not lesser — class 1 produced this project's
|
|
biggest single win. But "cheap to try" is not "safe to auto-accept."
|
|
LTO is deterministic codegen: accept it. An allocator swap is a global
|
|
behavioral change: measure it, prove the speedup, and *still* hand it to
|
|
a human. The tier is decided by the *nature* of the change, never by the
|
|
size of the number — the same rule that later caught a leaking teardown
|
|
patch the bench loved (case study 3).
|