#!/usr/bin/env python3 """Interleaved L87 passage A/B readiness and worker timeline matrix.""" from __future__ import annotations import json import argparse import re import statistics import subprocess import time from pathlib import Path ROOT = Path(__file__).resolve().parents[4] OUT = ROOT / "Saved/Linux/l87/timeline/switch-fixed" DATA = ROOT / "Standalone/data/owner_world.json" BINARY = ROOT / "Saved/Linux/l87/bin/VoxelForgeCoreHeadless-clang19" SOURCE_STAMP = "ac3d8ea64e9ac4bd5526c61990070fb504528ff56dae52d33c1937327374032b" STRATA = { "FI": {"id": 1, "camera": (25.8369140625, 3.19921875, -737.0), "near": 1216, "whole": 2249}, "TN": {"id": 2, "camera": (19.166015625, -14.2001953125, -753.3740234375), "near": 1344, "whole": 2233}, } WORKERS = (8, 12) MODES = ("direct", "passage_off") 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+) cold_ready_s=([0-9.]+)$", re.M, ) PUBLISHED = re.compile( r"^\[WorldAssemblerNearLODPublished\] lods=0-2 tiles=(\d+)/(\d+) cold_ready_s=([0-9.]+)$", re.M, ) PIPELINE_READY = re.compile( r"^\[WorldAssemblerNearLODPipelineReady\] lods=0-2 tiles=(\d+)/(\d+) cold_ready_s=([0-9.]+)$", re.M, ) SHAPE = re.compile( r"^\[FarShapeStage\] parent_shapes=([0-9.]+) ms spatial_bins=([0-9.]+) ms total=([0-9.]+) ms", re.M, ) CONFIG = re.compile(r"^\[HeadlessConfig\] (.*)$", re.M) STAMP = re.compile(r"^\[VoxelForgeSourceStamp\] sha256=(\S+)$", re.M) VOLUME = re.compile(r"^\[PipelineVolume\] tiles=(\d+) lod=", re.M) TIMELINE_EVENTS = re.compile(r"^\[CpuTileTimeline\] event=(\S+)", re.M) def command(stratum: str, workers: int, mode: str, timeline: bool) -> list[str]: camera = ",".join(f"{v:.12f}" for v in STRATA[stratum]["camera"]) + ",0,0" child = [ str(BINARY), str(DATA), "--world-assembler-prototype", "--stream-benchmark", "--stream-pipeline", f"--workers={workers}", "--clip-radius=3", "--max-clip-level=8", "--max-level=8", f"--camera={camera}", "--profile-lod-work", "--stream-scheduler-policy=3", ] if timeline: child.append("--cold-worker-timeline") env = ["VOXELFORGE_L81_PASSAGE_BOUND_PADDING_VOXELS=0"] if mode == "passage_off": env.append("VOXELFORGE_L86_DISABLE_PASSAGE_COMPOSITION=1") return [ "taskset", "-c", "0-11", "prlimit", "--as=6442450944", "--", "env", *env, "timeout", "1740s", *child, ] def run(stratum: str, workers: int, mode: str, phase: str, replicate: int, timeline: bool) -> dict: OUT.mkdir(parents=True, exist_ok=True) rep = f"-r{replicate}" if phase == "measured" else "" label = f"{stratum.lower()}-w{workers}-{mode}-{phase}{rep}" log = OUT / f"{label}.log" started = time.monotonic() with log.open("w", encoding="utf-8") as output: result = subprocess.run(command(stratum, workers, mode, timeline), cwd=ROOT, stdout=output, stderr=subprocess.STDOUT, check=False, timeout=1740) content = log.read_text(encoding="utf-8", errors="replace") near, published, pipeline_ready = ( NEAR.search(content), PUBLISHED.search(content), PIPELINE_READY.search(content) ) pipeline_match, far = PIPELINE.search(content), SHAPE.search(content) stamp_match = STAMP.search(content) config_match, volume_match = CONFIG.search(content), VOLUME.search(content) if result.returncode or not all((near, published, pipeline_ready, pipeline_match, far, config_match, volume_match, stamp_match)): raise RuntimeError(f"run failed or required timeline is missing: {log}; exit={result.returncode}") if stamp_match.group(1) != SOURCE_STAMP: raise RuntimeError(f"source stamp mismatch in {log}: {stamp_match.group(1)}") expected = STRATA[stratum] config_fields = dict(FIELDS.findall(config_match.group(1))) if int(config_fields["workers"]) != workers: raise RuntimeError(f"worker mismatch in {log}: {config_fields['workers']}") if int(volume_match.group(1)) != expected["whole"]: raise RuntimeError(f"wrong camera/strate window in {log}: {volume_match.group(1)} tiles") if ("[L86PassageCeiling]" in content) != (mode == "passage_off"): raise RuntimeError(f"passage switch state mismatch in {log}") for match in (near, published, pipeline_ready): if (int(match.group(1)), int(match.group(2))) != (expected["near"], expected["near"]): raise RuntimeError(f"incomplete near set in {log}: {match.group(1)}/{match.group(2)}") fields = dict(FIELDS.findall(pipeline_match.group(1))) whole_done, whole_total = (int(v) for v in fields["whole_tiles"].split("/")) if (whole_done, whole_total) != (expected["whole"], expected["whole"]): raise RuntimeError(f"incomplete whole view in {log}: {whole_done}/{whole_total}") cpu_events = TIMELINE_EVENTS.findall(content) if timeline and not cpu_events: raise RuntimeError(f"worker timeline missing in {log}") row = { "stratum": stratum, "stratum_id": expected["id"], "workers": workers, "mode": mode, "phase": phase, "replicate": replicate, "timeline": timeline, "headless_recipe_label": config_fields.get("recipe"), "cpu_tile_timeline_events": len(cpu_events), "exit_code": result.returncode, "wall_s": round(time.monotonic() - started, 3), "source_stamp": stamp_match.group(1), "lod02_ready_s": float(near.group(3)), "lod02_published_s": float(published.group(3)), "lod02_pipeline_ready_s": float(pipeline_ready.group(3)), "whole_view_ready_s": float(fields["whole_view_ready"].removesuffix("s")), "shape_s": float(fields["shape"].removesuffix("s")), "far_shape_s": float(far.group(3)) / 1000.0, "far_parent_ms": float(far.group(1)), "far_bins_ms": float(far.group(2)), "near_tiles": expected["near"], "whole_tiles": expected["whole"], "log": str(log.relative_to(ROOT)), } print("[L87TimelineRun] " + json.dumps(row, sort_keys=True), flush=True) return row def main() -> int: global OUT parser = argparse.ArgumentParser() parser.add_argument("--out", type=Path, default=Path("Saved/Linux/l87/timeline/final-phase")) args = parser.parse_args() OUT = args.out if args.out.is_absolute() else ROOT / args.out if not BINARY.is_file() or not DATA.is_file(): raise SystemExit(f"missing input: {BINARY} or {DATA}") # L80 warmup: once per camera window and worker count. Rotate both mode and # worker order across three paired measured replicates. for stratum in STRATA: for workers in WORKERS: for mode in MODES: run(stratum, workers, mode, "warmup", 0, False) measured = [] orders = ( ((8, "direct"), (8, "passage_off"), (12, "passage_off"), (12, "direct")), ((12, "direct"), (12, "passage_off"), (8, "passage_off"), (8, "direct")), ((8, "passage_off"), (8, "direct"), (12, "direct"), (12, "passage_off")), ) for stratum in STRATA: timeline_pending = {(workers, mode) for workers in WORKERS for mode in MODES} for replicate, order in enumerate(orders, 1): for workers, mode in order: timeline = (workers, mode) in timeline_pending if timeline: timeline_pending.remove((workers, mode)) measured.append(run(stratum, workers, mode, "measured", replicate, timeline)) (OUT / "runs-partial.json").write_text( json.dumps(measured, indent=2) + "\n", encoding="utf-8") summary = [] for stratum in STRATA: for workers in WORKERS: for mode in MODES: rows = [row for row in measured if row["stratum"] == stratum and row["workers"] == workers and row["mode"] == mode] if len(rows) != 3: raise RuntimeError(f"expected 3 measured replicates for {stratum} W{workers} {mode}") item = {"stratum": stratum, "workers": workers, "mode": mode, "measured_runs": 3} for metric in ("lod02_ready_s", "lod02_published_s", "lod02_pipeline_ready_s", "whole_view_ready_s", "shape_s", "far_shape_s"): values = [row[metric] for row in rows] item[metric] = values item[f"{metric}_median"] = statistics.median(values) summary.append(item) (OUT / "summary.json").write_text( json.dumps({"runs": measured, "summary": summary}, indent=2) + "\n", encoding="utf-8") return 0 if __name__ == "__main__": raise SystemExit(main())