L78's strict near-first order starved far LODs at 30 m/s (100% far holes, never completed). Unreal policy 2: once the collision ring is ready, LOD0-2 keep their reserve and far tiles are admitted as low-priority Horizon work; headless gives far work 1 of every 16 requests. Moving camera, far holes while moving: 1.4 m/s L77 8% / L78 29% / L79 31%; 30 m/s L77 8% / L78 100% / L79 72% (completes on dwell). Near readiness while moving at 30 m/s: 52 / 51 / 67%. Still worse than L77 for fast travel -> speed-adaptive policy next. World unchanged (v213). Fast tier PASS; Linux UE host builds. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_016dhxM43dnWvUu2B5Ph1iG1
188 lines
9.5 KiB
Python
188 lines
9.5 KiB
Python
#!/usr/bin/env python3
|
|
"""Compare L77, L78, and L79 production streaming orders while the pawn moves."""
|
|
from __future__ import annotations
|
|
|
|
import csv
|
|
import json
|
|
import re
|
|
import subprocess
|
|
import time
|
|
from pathlib import Path
|
|
|
|
|
|
ROOT = Path(__file__).resolve().parents[4]
|
|
HOST = Path("/home/jahni/VFHost")
|
|
PLUGIN_SAVED = ROOT / "Saved/Linux/l79"
|
|
HOST_PLUGIN_SAVED = HOST / "Plugins/VoxelForge/Saved/Linux/l79"
|
|
HOST_SAVED = HOST / "Saved/Linux/l79"
|
|
EDITOR = Path("/home/jahni/UnrealEngine/Engine/Binaries/Linux/UnrealEditor-Cmd")
|
|
SPAWN_M = (19.166015625, -14.2001953125, -753.3740234375) # owner TunnelNetwork
|
|
SPEEDS = {"walk": 140.0, "fast": 3000.0} # cm/s: 1.4 m/s and 30 m/s
|
|
POLICY_NAMES = {0: "L77", 1: "L78", 2: "L79"}
|
|
TRACE_DIR = PLUGIN_SAVED / "movement/traces"
|
|
MOVE_START_S = 6.0
|
|
EXIT_S = 18.0
|
|
|
|
|
|
def parse_trace(path: Path, run: dict) -> tuple[list[dict], dict]:
|
|
events = []
|
|
if path.is_file():
|
|
for line in path.read_text(encoding="utf-8", errors="replace").splitlines():
|
|
try:
|
|
events.append(json.loads(line))
|
|
except json.JSONDecodeError:
|
|
pass
|
|
samples = [event for event in events if event.get("type") == "streaming_sample"
|
|
and float(event.get("speed_cm_s", 0.0)) >= 50.0]
|
|
scheduler = [event for event in events if event.get("type") == "scheduler_admission"
|
|
and float(event.get("moving", 0)) > 0]
|
|
rows = []
|
|
for event in samples:
|
|
desired = event.get("desired_by_lod", [0] * 9)
|
|
resident = event.get("resident_by_lod", [0] * 9)
|
|
pending = event.get("pending_by_lod", [0] * 9)
|
|
far_desired = sum(desired[3:])
|
|
far_resident = sum(resident[3:])
|
|
near_desired = sum(desired[:3])
|
|
near_resident = sum(resident[:3])
|
|
rows.append({
|
|
"run": run["label"], "policy": run["policy_name"], "speed": run["speed"],
|
|
"t_s": event.get("t_s"), "position_cm": event.get("position_cm"),
|
|
"speed_cm_s": event.get("speed_cm_s"),
|
|
"far_desired": far_desired, "far_resident": far_resident,
|
|
"far_pending": sum(pending[3:]),
|
|
"far_missing_pct": round(100.0 * (far_desired - far_resident)
|
|
/ max(1, far_desired), 3),
|
|
"near_desired": near_desired, "near_resident": near_resident,
|
|
"near_ready_pct": round(100.0 * near_resident / max(1, near_desired), 3),
|
|
"walkable_ready": event.get("walkable_ready"),
|
|
**{f"lod{i}_desired": desired[i] for i in range(9)},
|
|
**{f"lod{i}_resident": resident[i] for i in range(9)},
|
|
})
|
|
submitted_far = sum(sum(event.get("submitted_by_lod", [0] * 9)[3:])
|
|
for event in scheduler)
|
|
submitted_near = sum(sum(event.get("submitted_by_lod", [0] * 9)[:3])
|
|
for event in scheduler)
|
|
far_missing = [row["far_missing_pct"] for row in rows]
|
|
near_ready = [row["near_ready_pct"] for row in rows]
|
|
abslog_lines = (run["abslog_path"].read_text(encoding="utf-8", errors="replace").splitlines()
|
|
if run["abslog_path"].is_file() else [])
|
|
summary = {
|
|
"moving_samples": len(rows),
|
|
"moving_duration_s": round(max((float(row["t_s"]) for row in rows), default=0.0)
|
|
- min((float(row["t_s"]) for row in rows), default=0.0), 3),
|
|
"far_missing_pct_mean": round(sum(far_missing) / max(1, len(far_missing)), 3),
|
|
"far_missing_pct_max": max(far_missing, default=None),
|
|
"far_missing_pct_first": far_missing[0] if far_missing else None,
|
|
"far_missing_pct_last": far_missing[-1] if far_missing else None,
|
|
"near_ready_pct_mean": round(sum(near_ready) / max(1, len(near_ready)), 3),
|
|
"near_ready_pct_min": min(near_ready, default=None),
|
|
"near_ready_pct_last": near_ready[-1] if near_ready else None,
|
|
"walkable_ready_samples": sum(row["walkable_ready"] == 1 for row in rows),
|
|
"submitted_near_tiles": submitted_near,
|
|
"submitted_far_tiles": submitted_far,
|
|
"lod0_ring_ready_events": sum(event.get("type") == "lod0_ring_ready" for event in events),
|
|
"visual_gap_result": next((line.split("result=")[1].split()[0]
|
|
for line in abslog_lines
|
|
if "[VoxelForgeVisualGapAudit] result=" in line), "not-run"),
|
|
"visual_staleness_result": next((line.split("result=")[1].split()[0]
|
|
for line in abslog_lines
|
|
if "[VoxelForgeVisualStaleness] result=" in line), "not-run"),
|
|
}
|
|
return rows, summary
|
|
|
|
|
|
def run(policy: int, speed_name: str, replicate: int, audit: bool = False) -> tuple[dict, list[dict]]:
|
|
label = f"{speed_name}-{POLICY_NAMES[policy]}-r{replicate}" + ("-audit" if audit else "")
|
|
trace = TRACE_DIR / f"{label}.trace.jsonl"
|
|
abslog = TRACE_DIR / f"{label}.log"
|
|
stdout = TRACE_DIR / f"{label}.stdout.log"
|
|
output = HOST_PLUGIN_SAVED / "output" / label
|
|
userdir = HOST_SAVED / "user" / label
|
|
zendata = HOST_SAVED / "zen" / label
|
|
ddc = HOST_SAVED / "DDC"
|
|
for directory in (TRACE_DIR, output, userdir, zendata, ddc):
|
|
directory.mkdir(parents=True, exist_ok=True)
|
|
spawn_cm = ",".join(f"{value * 100.0:.3f}" for value in SPAWN_M)
|
|
command = [
|
|
str(EDITOR), str(HOST / "VFHost.uproject"), "-nullrhi", "-unattended",
|
|
"-nop4", "-nosplash", "-NoSound", "-corelimit=12", "-NoZenAutoLaunch",
|
|
"-notraceserver", "-nocrashreports", "-DisablePlugins=AndroidFileServer",
|
|
"-ddc=NoZenLocalFallback", f"-userdir={userdir}", f"-ZenDataPath={zendata}",
|
|
f"-LocalDataCachePath={ddc}", "-run=VoxelForgeExplore", "-seed=0",
|
|
"-archetype=TunnelNetwork", "-slot=0", "-modes=export", "-gameconfig=1",
|
|
"-coreworldtest=1", "-ownerfourstrateplan=1", "-corevoxelsizecm=25",
|
|
"-coreislandtest=0", "-corefallbacktest=0", "-coreofftest=0", "-coreplantest=0",
|
|
"-settingsref=/Game/VoxelForge/DA_Settings.DA_Settings", "-corehybridmesher=0",
|
|
f"-out={output}", "-voxel.StreamingCoarseFirst=1",
|
|
"-voxel.StreamingDynamicNearReserve=1", "-voxel.StreamingLegacyPendingResultCap=0",
|
|
"-voxel.CoreRegionConcurrentAdmission=1", "-voxel.StreamingResultBacklogCap=256",
|
|
"-voxel.StreamingReadyQueueDepth=8", "-voxel.StreamingBackgroundWorkerCap=1",
|
|
"-voxel.CoreColumnCacheDirectMapped=0", "-voxel.CoreMCGradientMemoization=1",
|
|
"-voxel.StreamingCollisionLookahead=1", "-voxel.TestMove=1",
|
|
f"-voxel.TestMoveSpeedCmPerSecond={SPEEDS[speed_name]:.1f}",
|
|
f"-voxel.TestMoveStartSeconds={MOVE_START_S:.1f}",
|
|
f"-voxel.TestExitSeconds={EXIT_S:.1f}", "-voxel.TestMoveDirection=1,0,0",
|
|
f"-voxel.StreamingSchedulerPolicy={policy}", "-voxel.TestExitOnSteady=0",
|
|
"-coreworldstreamtrace=1", f"-voxel.StartupTraceSpawnCm={spawn_cm}",
|
|
"-voxel.StartupTraceUntilEndPlay=1", "-voxel.StartupTraceThroughCrossing=1",
|
|
"-voxel.StartupTraceMaxTiles=16384", f"-voxel.StartupTraceFile={trace}",
|
|
f"-abslog={abslog}",
|
|
]
|
|
if audit:
|
|
command.extend(("-voxel.TestVisualStaleness=2", "-voxel.TestVisualGapAudit=1"))
|
|
wrapped = ["taskset", "-c", "0-11", "prlimit", "--as=6442450944", "--",
|
|
"timeout", "1740s", *command]
|
|
started = time.monotonic()
|
|
with stdout.open("w", encoding="utf-8") as stream:
|
|
result = subprocess.run(wrapped, cwd=ROOT, stdout=stream,
|
|
stderr=subprocess.STDOUT, check=False, timeout=1740)
|
|
run_info = {
|
|
"label": label, "policy": policy, "policy_name": POLICY_NAMES[policy],
|
|
"speed": speed_name, "speed_cm_s": SPEEDS[speed_name], "replicate": replicate,
|
|
"audit": audit, "exit_code": result.returncode,
|
|
"elapsed_s": round(time.monotonic() - started, 3),
|
|
"trace": str(trace.relative_to(ROOT)), "abslog": str(abslog.relative_to(ROOT)),
|
|
"stdout": str(stdout.relative_to(ROOT)), "abslog_path": abslog,
|
|
}
|
|
samples, summary = parse_trace(trace, run_info)
|
|
run_info.update(summary)
|
|
del run_info["abslog_path"]
|
|
print("[L79MoveRun] " + json.dumps(run_info, sort_keys=True), flush=True)
|
|
return run_info, samples
|
|
|
|
|
|
def main() -> int:
|
|
if not EDITOR.is_file():
|
|
raise SystemExit(f"missing Unreal commandlet executable: {EDITOR}")
|
|
TRACE_DIR.mkdir(parents=True, exist_ok=True)
|
|
results: list[dict] = []
|
|
sample_rows: list[dict] = []
|
|
schedule = []
|
|
for replicate, policies in ((1, (0, 1, 2)), (2, (2, 1, 0))):
|
|
speeds = ("walk", "fast") if replicate == 1 else ("fast", "walk")
|
|
for policy in policies:
|
|
for speed in speeds:
|
|
schedule.append((policy, speed, replicate, False))
|
|
schedule.append((2, "fast", 3, True))
|
|
for policy, speed, replicate, audit in schedule:
|
|
row, samples = run(policy, speed, replicate, audit)
|
|
results.append(row)
|
|
sample_rows.extend(samples)
|
|
(PLUGIN_SAVED / "movement/runs-partial.json").write_text(
|
|
json.dumps(results, indent=2) + "\n", encoding="utf-8")
|
|
(PLUGIN_SAVED / "movement/summary.json").write_text(
|
|
json.dumps({"runs": results}, indent=2) + "\n", encoding="utf-8")
|
|
sample_path = PLUGIN_SAVED / "movement/samples.csv"
|
|
if sample_rows:
|
|
with sample_path.open("w", newline="", encoding="utf-8") as stream:
|
|
writer = csv.DictWriter(stream, fieldnames=list(sample_rows[0]))
|
|
writer.writeheader()
|
|
writer.writerows(sample_rows)
|
|
return 0 if all(row["exit_code"] == 0 and row["moving_samples"] > 0
|
|
for row in results) else 2
|
|
|
|
|
|
if __name__ == "__main__":
|
|
raise SystemExit(main())
|