diag: corrected passage-off ceiling + cold worker/tile timelines (L87); passages ARE the gate
L86's switch left ApplyResolvedStratePassageCarves running (near-tile service unchanged at ~21 worker-s), so its "no change" ceiling was wrong. Corrected (bands + carves off): FI LOD0-2 2.34 -> 0.66 s, whole 3.47 -> 1.49 s @W12; TN 2.27 -> 0.74 / 3.28 -> 1.52 s. Near-tile service 15.6-22.5 -> 2.6-3.8 worker-s. Critical chain: shape/base compile -> LOD0-1 -> far-parent build (107-153 ms, pipeline thread) -> LOD2. Workers 81-85% busy in the direct window. No production scheduling change; hashes equal L85. Fast tier PASS. 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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"""Interleaved L87 passage A/B readiness and worker timeline matrix."""
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from __future__ import annotations
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import json
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import argparse
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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/l87/timeline/switch-fixed"
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DATA = ROOT / "Standalone/data/owner_world.json"
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BINARY = ROOT / "Saved/Linux/l87/bin/VoxelForgeCoreHeadless-clang19"
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SOURCE_STAMP = "ac3d8ea64e9ac4bd5526c61990070fb504528ff56dae52d33c1937327374032b"
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STRATA = {
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"FI": {"id": 1, "camera": (25.8369140625, 3.19921875, -737.0),
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"near": 1216, "whole": 2249},
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"TN": {"id": 2, "camera": (19.166015625, -14.2001953125, -753.3740234375),
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"near": 1344, "whole": 2233},
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}
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WORKERS = (8, 12)
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MODES = ("direct", "passage_off")
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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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)
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PUBLISHED = re.compile(
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r"^\[WorldAssemblerNearLODPublished\] lods=0-2 tiles=(\d+)/(\d+) cold_ready_s=([0-9.]+)$",
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re.M,
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)
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PIPELINE_READY = re.compile(
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r"^\[WorldAssemblerNearLODPipelineReady\] lods=0-2 tiles=(\d+)/(\d+) cold_ready_s=([0-9.]+)$",
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re.M,
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)
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SHAPE = re.compile(
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r"^\[FarShapeStage\] parent_shapes=([0-9.]+) ms spatial_bins=([0-9.]+) ms total=([0-9.]+) ms",
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re.M,
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)
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CONFIG = re.compile(r"^\[HeadlessConfig\] (.*)$", re.M)
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STAMP = re.compile(r"^\[VoxelForgeSourceStamp\] sha256=(\S+)$", re.M)
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VOLUME = re.compile(r"^\[PipelineVolume\] tiles=(\d+) lod=", re.M)
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TIMELINE_EVENTS = re.compile(r"^\[CpuTileTimeline\] event=(\S+)", re.M)
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def command(stratum: str, workers: int, mode: str, timeline: bool) -> list[str]:
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camera = ",".join(f"{v:.12f}" for v in STRATA[stratum]["camera"]) + ",0,0"
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child = [
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str(BINARY), str(DATA), "--world-assembler-prototype", "--stream-benchmark",
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"--stream-pipeline", f"--workers={workers}", "--clip-radius=3",
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"--max-clip-level=8", "--max-level=8", f"--camera={camera}",
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"--profile-lod-work", "--stream-scheduler-policy=3",
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]
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if timeline:
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child.append("--cold-worker-timeline")
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env = ["VOXELFORGE_L81_PASSAGE_BOUND_PADDING_VOXELS=0"]
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if mode == "passage_off":
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env.append("VOXELFORGE_L86_DISABLE_PASSAGE_COMPOSITION=1")
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return [
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"taskset", "-c", "0-11", "prlimit", "--as=6442450944", "--", "env",
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*env, "timeout", "1740s", *child,
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]
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def run(stratum: str, workers: int, mode: str, phase: str,
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replicate: int, timeline: bool) -> dict:
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OUT.mkdir(parents=True, exist_ok=True)
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rep = f"-r{replicate}" if phase == "measured" else ""
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label = f"{stratum.lower()}-w{workers}-{mode}-{phase}{rep}"
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log = OUT / f"{label}.log"
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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(stratum, workers, mode, timeline), cwd=ROOT,
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stdout=output, stderr=subprocess.STDOUT,
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check=False, timeout=1740)
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content = log.read_text(encoding="utf-8", errors="replace")
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near, published, pipeline_ready = (
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NEAR.search(content), PUBLISHED.search(content), PIPELINE_READY.search(content)
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)
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pipeline_match, far = PIPELINE.search(content), SHAPE.search(content)
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stamp_match = STAMP.search(content)
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config_match, volume_match = CONFIG.search(content), VOLUME.search(content)
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if result.returncode or not all((near, published, pipeline_ready, pipeline_match, far,
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config_match, volume_match, stamp_match)):
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raise RuntimeError(f"run failed or required timeline is missing: {log}; exit={result.returncode}")
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if stamp_match.group(1) != SOURCE_STAMP:
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raise RuntimeError(f"source stamp mismatch in {log}: {stamp_match.group(1)}")
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expected = STRATA[stratum]
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config_fields = dict(FIELDS.findall(config_match.group(1)))
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if int(config_fields["workers"]) != workers:
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raise RuntimeError(f"worker mismatch in {log}: {config_fields['workers']}")
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if int(volume_match.group(1)) != expected["whole"]:
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raise RuntimeError(f"wrong camera/strate window in {log}: {volume_match.group(1)} tiles")
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if ("[L86PassageCeiling]" in content) != (mode == "passage_off"):
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raise RuntimeError(f"passage switch state mismatch in {log}")
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for match in (near, published, pipeline_ready):
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if (int(match.group(1)), int(match.group(2))) != (expected["near"], expected["near"]):
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raise RuntimeError(f"incomplete near set in {log}: {match.group(1)}/{match.group(2)}")
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fields = dict(FIELDS.findall(pipeline_match.group(1)))
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whole_done, whole_total = (int(v) for v in fields["whole_tiles"].split("/"))
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if (whole_done, whole_total) != (expected["whole"], expected["whole"]):
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raise RuntimeError(f"incomplete whole view in {log}: {whole_done}/{whole_total}")
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cpu_events = TIMELINE_EVENTS.findall(content)
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if timeline and not cpu_events:
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raise RuntimeError(f"worker timeline missing in {log}")
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row = {
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"stratum": stratum, "stratum_id": expected["id"], "workers": workers,
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"mode": mode, "phase": phase, "replicate": replicate,
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"timeline": timeline, "headless_recipe_label": config_fields.get("recipe"),
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"cpu_tile_timeline_events": len(cpu_events),
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"exit_code": result.returncode, "wall_s": round(time.monotonic() - started, 3),
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"source_stamp": stamp_match.group(1),
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"lod02_ready_s": float(near.group(3)),
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"lod02_published_s": float(published.group(3)),
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"lod02_pipeline_ready_s": float(pipeline_ready.group(3)),
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"whole_view_ready_s": float(fields["whole_view_ready"].removesuffix("s")),
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"shape_s": float(fields["shape"].removesuffix("s")),
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"far_shape_s": float(far.group(3)) / 1000.0,
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"far_parent_ms": float(far.group(1)), "far_bins_ms": float(far.group(2)),
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"near_tiles": expected["near"], "whole_tiles": expected["whole"],
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"log": str(log.relative_to(ROOT)),
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}
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print("[L87TimelineRun] " + json.dumps(row, sort_keys=True), flush=True)
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return row
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def main() -> int:
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global OUT
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parser = argparse.ArgumentParser()
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parser.add_argument("--out", type=Path, default=Path("Saved/Linux/l87/timeline/final-phase"))
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args = parser.parse_args()
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OUT = args.out if args.out.is_absolute() else ROOT / args.out
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if not BINARY.is_file() or not DATA.is_file():
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raise SystemExit(f"missing input: {BINARY} or {DATA}")
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# L80 warmup: once per camera window and worker count. Rotate both mode and
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# worker order across three paired measured replicates.
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for stratum in STRATA:
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for workers in WORKERS:
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for mode in MODES:
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run(stratum, workers, mode, "warmup", 0, False)
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measured = []
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orders = (
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((8, "direct"), (8, "passage_off"), (12, "passage_off"), (12, "direct")),
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((12, "direct"), (12, "passage_off"), (8, "passage_off"), (8, "direct")),
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((8, "passage_off"), (8, "direct"), (12, "direct"), (12, "passage_off")),
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)
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for stratum in STRATA:
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timeline_pending = {(workers, mode) for workers in WORKERS for mode in MODES}
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for replicate, order in enumerate(orders, 1):
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for workers, mode in order:
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timeline = (workers, mode) in timeline_pending
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if timeline:
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timeline_pending.remove((workers, mode))
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measured.append(run(stratum, workers, mode, "measured", replicate, timeline))
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(OUT / "runs-partial.json").write_text(
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json.dumps(measured, indent=2) + "\n", encoding="utf-8")
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summary = []
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for stratum in STRATA:
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for workers in WORKERS:
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for mode in MODES:
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rows = [row for row in measured if row["stratum"] == stratum
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and row["workers"] == workers and row["mode"] == mode]
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if len(rows) != 3:
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raise RuntimeError(f"expected 3 measured replicates for {stratum} W{workers} {mode}")
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item = {"stratum": stratum, "workers": workers, "mode": mode,
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"measured_runs": 3}
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for metric in ("lod02_ready_s", "lod02_published_s",
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"lod02_pipeline_ready_s", "whole_view_ready_s",
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"shape_s", "far_shape_s"):
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values = [row[metric] for row in rows]
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item[metric] = values
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item[f"{metric}_median"] = statistics.median(values)
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summary.append(item)
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(OUT / "summary.json").write_text(
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json.dumps({"runs": measured, "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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