core: A/A noise floor (±1%) and small hot-path trims for the cave planner (L137, output = v236)
Identical builds differ <=0.6% median; residual near-ready vs assembler/world is real: Surface World +2.9..+3.6%, Vertical Shafts +4.0..+4.3%, Tunnel Network -3.6/+6.8%. Profile points at column-cache reads and the sweep lookup. Removed an unused sample field and per-lookup shared_ptr refcounting. 16/16 seeds, fast tier, Clang/GCC green. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_016dhxM43dnWvUu2B5Ph1iG1
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#!/usr/bin/env python3
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"""L80 Surface World A/A and no-op evaluator-version control timings."""
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from __future__ import annotations
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import json
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import os
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import re
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import statistics
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import subprocess
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import time
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from pathlib import Path
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ROOT = Path(__file__).resolve().parents[4]
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OUT = ROOT / "Saved/Linux/l137/timing/aa"
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DATA = ROOT / "Standalone/data/owner_world.json"
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BINARIES = {
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"aa_a": ROOT / "Saved/Linux/l137/bin/VoxelForgeCoreHeadless-l137-aa-a",
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"aa_b": ROOT / "Saved/Linux/l137/bin/VoxelForgeCoreHeadless-l137-aa-b",
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"v228": ROOT / "Saved/Linux/l137/bin/VoxelForgeCoreHeadless-l137-v228",
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}
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CAMERA = "8.000000000000,16.000000000000,-372.262695312500,0,0"
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PIPELINE = re.compile(r"^\[StreamPipeline\] (.*)$", re.M)
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FIELDS = re.compile(r"([a-zA-Z0-9_]+)=([^ ]+)")
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NEAR = re.compile(
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r"^\[WorldAssemblerNearLODReady\] lods=0-2 tiles=(\d+)/(\d+) cold_ready_s=([0-9.]+)$",
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re.M)
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STAMP = re.compile(r"^\[VoxelForgeSourceStamp\] sha256=([0-9a-f]+)$", re.M)
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def run(workers: int, version: str, phase: str, replicate: int) -> dict:
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OUT.mkdir(parents=True, exist_ok=True)
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label = f"sw-w{workers}-{version}-{phase}{replicate}"
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log = OUT / f"{label}.log"
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command = [
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"taskset", "-c", "0-11", "prlimit", "--as=6442450944", "--",
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"timeout", "1740s", str(BINARIES[version]), str(DATA),
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"--world-assembler-prototype", "--stream-benchmark", "--stream-pipeline",
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f"--workers={workers}", "--clip-radius=3", "--max-clip-level=8",
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"--max-level=8", f"--camera={CAMERA}", "--profile-lod-work",
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"--stream-scheduler-policy=3",
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]
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started = time.monotonic()
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with log.open("w", encoding="utf-8") as output:
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result = subprocess.run(command, cwd=ROOT, stdout=output,
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stderr=subprocess.STDOUT, check=False, timeout=1740)
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content = log.read_text(encoding="utf-8", errors="replace")
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pipeline, near, stamp = PIPELINE.search(content), NEAR.search(content), STAMP.search(content)
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if result.returncode or pipeline is None or near is None or stamp is None:
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raise SystemExit(f"L80 run failed or trace missing: {log}; exit={result.returncode}")
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fields = dict(FIELDS.findall(pipeline.group(1)))
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row = {
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"strate": 0, "workers": workers, "version": version,
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"phase": phase, "replicate": replicate, "source_stamp": stamp.group(1),
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"lod02_ready_s": float(near.group(3)),
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"whole_view_ready_s": float(fields["whole_view_ready"].removesuffix("s")),
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"whole_tiles": int(fields["whole_tiles"].split("/")[0]),
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"wall_s": round(time.monotonic() - started, 3),
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"log": str(log.relative_to(ROOT)),
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}
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print("[L137AARun] " + json.dumps(row, sort_keys=True), flush=True)
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return row
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def quiet_machine() -> tuple[float, float]:
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load_1m = os.getloadavg()[0]
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def totals() -> tuple[int, int]:
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fields = Path("/proc/stat").read_text().splitlines()[0].split()
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values = [int(value) for value in fields[1:]]
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return sum(values), values[3] + values[4]
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before = totals()
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time.sleep(2.0)
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after = totals()
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idle = 100.0 * (after[1] - before[1]) / max(1, after[0] - before[0])
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return load_1m, idle
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def main() -> int:
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missing = [str(path) for path in [DATA, *BINARIES.values()] if not path.is_file()]
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if missing:
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raise SystemExit("missing L137 A/A input: " + ", ".join(missing))
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OUT.mkdir(parents=True, exist_ok=True)
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load_1m, idle = quiet_machine()
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(OUT / "machine-load-before.txt").write_text(
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f"1-minute load: {load_1m:.2f}\n2-second CPU idle: {idle:.1f}%\n")
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print(f"[L137AAGate] load_1m={load_1m:.2f} cpu_idle_2s={idle:.1f}%", flush=True)
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if load_1m >= 0.9 or idle < 97.0:
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raise SystemExit("timing refused: machine is above the L80 quiet-load gate")
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rows = []
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versions = tuple(BINARIES)
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for workers in (8, 12):
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for version in versions:
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run(workers, version, "warmup", 0)
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orders = (versions, ("v228", "aa_b", "aa_a"),
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("aa_b", "aa_a", "v228"), ("aa_a", "v228", "aa_b"),
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("v228", "aa_a", "aa_b"))
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for replicate, order in enumerate(orders, 1):
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for version in order:
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rows.append(run(workers, version, "measured", replicate))
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(OUT / "runs-partial.json").write_text(
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json.dumps(rows, indent=2) + "\n", encoding="utf-8")
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summary = []
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for workers in (8, 12):
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group = [row for row in rows if row["workers"] == workers]
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medians = {
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version: {
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key: statistics.median(row[key] for row in group
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if row["version"] == version)
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for key in ("lod02_ready_s", "whole_view_ready_s")
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}
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for version in versions
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}
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item = {"strate": 0, "workers": workers, "replicates_per_version": 5,
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"medians": medians}
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for metric in ("lod02_ready_s", "whole_view_ready_s"):
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for lhs, rhs in (("aa_b", "aa_a"), ("v228", "aa_a")):
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item[f"{lhs}_vs_{rhs}_{metric}_delta_pct"] = round(
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100.0 * (medians[lhs][metric] / medians[rhs][metric] - 1.0), 3)
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paired = []
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for replicate in range(1, 6):
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values = {row["version"]: row[metric] for row in group
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if row["phase"] == "measured" and row["replicate"] == replicate}
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paired.append({"replicate": replicate,
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"aa_b_vs_aa_a_pct": round(
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100.0 * (values["aa_b"] / values["aa_a"] - 1.0), 3),
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"v228_vs_aa_a_pct": round(
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100.0 * (values["v228"] / values["aa_a"] - 1.0), 3)})
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item[f"{metric}_paired_deltas_pct"] = paired
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summary.append(item)
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(OUT / "summary.json").write_text(
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json.dumps({"runs": rows, "summary": summary}, indent=2) + "\n",
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encoding="utf-8")
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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