Files
VoxelForge/Standalone/Research/WorldAssemblerM3/Linux83/RunL83CutReadiness.py
T
Fr0zkaandClaude Opus 5.5 a81b5b7d06 passages: contiguous BVH node ranges + child-bound reuse (L83); scaling and serial floor measured
Exact through LOD2 (all near tile hashes equal L82). W8 LOD0-2: SW 1.09->1.06, FI 2.47->2.34,
TN 2.39->2.43 (noise), VS 1.20->1.18 s. Fast tier PASS.
Scaling W4/W8/W12/W16 (LOD0-2, FI): 3.59 / 2.48 / 2.33 / 2.34 s - flattens past W8-W12.
Estimated infinite-worker floor ~1.0 s FI/TN = shape compile (0.35-0.41 s, not overlapped:
no shape-free tiles in these views) + slowest single LOD0 tile service (0.51-0.59 s).

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_016dhxM43dnWvUu2B5Ph1iG1
2026-10-28 00:24:49 +01:00

128 lines
6.2 KiB
Python

#!/usr/bin/env python3
"""Three interleaved L80-protocol W8 readiness pairs for L82 vs final L83."""
from __future__ import annotations
import json
import re
import statistics
import subprocess
import time
from pathlib import Path
ROOT = Path(__file__).resolve().parents[4]
OUT = ROOT / "Saved/Linux/l83/readiness"
DATA = ROOT / "Standalone/data/owner_world.json"
BINARIES = {
"L82": ROOT / "Saved/Linux/l82/bin/VoxelForgeCoreHeadless-clang19",
"L83": ROOT / "Saved/Linux/l83/bin/VoxelForgeCoreHeadless-l83-clang19",
}
CAMERAS = {
0: (8.0, 16.0, -372.2626953125),
1: (25.8369140625, 3.19921875, -737.0),
2: (19.166015625, -14.2001953125, -753.3740234375),
3: (-20.0625, -5.068359375, -900.353515625),
}
EXPECTED_NEAR = {0: 1408, 1: 1216, 2: 1344, 3: 1344}
EXPECTED_WHOLE = {0: 2850, 1: 2249, 2: 2233, 3: 2329}
PIPELINE = re.compile(r"^\[StreamPipeline\] (.*)$", re.M)
FIELDS = re.compile(r"([a-zA-Z0-9_]+)=([^ ]+)")
NEAR = re.compile(r"^\[WorldAssemblerNearLODReady\] lods=0-2 tiles=(\d+)/(\d+) "
r"cold_ready_s=([0-9.]+)$", re.M)
SHAPE_FREE = re.compile(r"^\[ShapeReadiness\] shape_free_desired=(\d+)/(\d+) "
r"near_ring=(\d+)/27", re.M)
STAMP = re.compile(r"^\[VoxelForgeSourceStamp\] sha256=(\S+)$", re.M)
EXPECTED_STAMPS = {
"L82": "99fcbd2fd46e0bb3e250f3ad67e98ade0545e419193f987550356015714c6f1b",
"L83": "08af4e98c86a69477cc79e21463d8c93bcd11ebe0f077d7c11519031d9141fa9",
}
def run(strate: int, version: str, phase: str, rep: int) -> dict:
OUT.mkdir(parents=True, exist_ok=True)
log = OUT / f"s{strate}-{version.lower()}-{phase}{rep}.log"
camera = ",".join(f"{v:.12f}" for v in CAMERAS[strate]) + ",0,0"
command = [
"taskset", "-c", "0-11", "prlimit", "--as=6442450944", "--",
"env", "VOXELFORGE_L81_PASSAGE_BOUND_PADDING_VOXELS=0", "timeout", "1740s",
str(BINARIES[version]), str(DATA), "--world-assembler-prototype",
"--stream-benchmark", "--stream-pipeline", "--workers=8", "--clip-radius=3",
"--max-clip-level=8", "--max-level=8", f"--camera={camera}",
"--profile-lod-work", "--stream-scheduler-policy=3",
]
start = time.monotonic()
with log.open("w", encoding="utf-8") as stream:
result = subprocess.run(command, cwd=ROOT, stdout=stream,
stderr=subprocess.STDOUT, check=False, timeout=1740)
output = log.read_text(encoding="utf-8", errors="replace")
pipeline_match, near_match = PIPELINE.search(output), NEAR.search(output)
shape_free_match, stamp_match = SHAPE_FREE.search(output), STAMP.search(output)
if result.returncode or pipeline_match is None or near_match is None:
raise RuntimeError(f"readiness run failed: exit={result.returncode} {log}")
if stamp_match is None or stamp_match.group(1) != EXPECTED_STAMPS[version]:
raise RuntimeError(f"source stamp mismatch in {log}")
pipeline = dict(FIELDS.findall(pipeline_match.group(1)))
near_done, near_total = int(near_match.group(1)), int(near_match.group(2))
whole_done, whole_total = (int(v) for v in pipeline["whole_tiles"].split("/"))
if near_done != near_total or near_total != EXPECTED_NEAR[strate]:
raise RuntimeError(f"near readiness incomplete in {log}: {near_done}/{near_total}")
if whole_done != whole_total or whole_total != EXPECTED_WHOLE[strate]:
raise RuntimeError(f"whole readiness incomplete in {log}: {whole_done}/{whole_total}")
row = {
"strate": strate, "version": version, "phase": phase, "replicate": rep,
"exit_code": result.returncode, "wall_s": round(time.monotonic() - start, 3),
"lod02_ready_s": float(near_match.group(3)),
"whole_view_ready_s": float(pipeline["whole_view_ready"].removesuffix("s")),
"shape_s": float(pipeline["shape"].removesuffix("s")),
"first_tile_ready_s": float(pipeline["first_tile_ready"].removesuffix("s")),
"neighborhood_ready_s": float(pipeline["neighborhood_ready"].removesuffix("s")),
"near_tiles": near_total, "whole_tiles": whole_total,
"shape_free_desired": int(shape_free_match.group(1)) if shape_free_match else None,
"shape_free_near_ring": int(shape_free_match.group(3)) if shape_free_match else None,
"source_stamp": stamp_match.group(1), "log": str(log.relative_to(ROOT)),
}
print("[L83ReadinessRun] " + json.dumps(row, sort_keys=True), flush=True)
return row
def main() -> int:
for path in (*BINARIES.values(), DATA):
if not path.is_file():
raise SystemExit(f"missing input: {path}")
for strate in range(4):
for version in ("L82", "L83"):
run(strate, version, "warmup", 0)
rows = []
orders = (("L82", "L83"), ("L83", "L82"), ("L82", "L83"))
for strate in range(4):
for rep, order in enumerate(orders, 1):
for version in order:
rows.append(run(strate, version, "measured", rep))
(OUT / "runs-partial.json").write_text(
json.dumps(rows, indent=2) + "\n", encoding="utf-8")
summary = []
for strate in range(4):
group = [row for row in rows if row["strate"] == strate]
item = {"strate": strate, "measured_pairs": 3}
for version in ("L82", "L83"):
subset = [row for row in group if row["version"] == version]
for metric in ("lod02_ready_s", "whole_view_ready_s", "shape_s"):
values = [row[metric] for row in subset]
item[f"{version}_{metric}"] = values
item[f"{version}_{metric}_median"] = statistics.median(values)
for metric in ("lod02_ready_s", "whole_view_ready_s"):
by_pair = {rep: {row["version"]: row[metric] for row in group
if row["phase"] == "measured" and row["replicate"] == rep}
for rep in (1, 2, 3)}
deltas = [by_pair[rep]["L83"] - by_pair[rep]["L82"] for rep in (1, 2, 3)]
item[f"paired_{metric}_delta_s"] = deltas
item[f"paired_{metric}_delta_median_s"] = statistics.median(deltas)
summary.append(item)
(OUT / "summary.json").write_text(
json.dumps({"runs": rows, "summary": summary}, indent=2) + "\n",
encoding="utf-8")
return 0
if __name__ == "__main__":
raise SystemExit(main())