#!/usr/bin/env python3 """Run the fixed P3 lighting sweep and retain raw per-frame GPU measurements. The Forward+ threshold in the summary is a measurement result, not an automatic renderer switch. Apply it to the Linux physical reference GPU; keep other devices as separate functional/performance observations. """ from __future__ import annotations import argparse import csv import hashlib import json import math from pathlib import Path import statistics import subprocess import sys LIGHT_COUNTS = (0, 4, 16, 32, 64, 128) VISIBILITY_MODES = ("direct", "gpu-frustum", "gpu-occlusion") REPEATS = (1, 2, 3) # Pair a zero-light control with every independent repeat, keeping high-light # measurements nearby rather than comparing the first run with the last. MEASUREMENT_ORDER = (0, 32, 4, 64, 16, 128) WARMUP_FRAMES = 10 MEASURED_FRAMES = 30 WIDTH, HEIGHT = 1920, 1080 REQUIRED_COLUMNS = ( "light_count", "shadows", "visibility", "frame", "device", "driver", "commit", "gpu_main_raster_ms", "gpu_ms", "gpu_shadow_ms", "cpu_ms", "readback_cpu_ms", "validation_errors", "run_index", "effective_visibility", "lighting_path", "submitted_local_lights", "omitted_local_lights", "shadow_tiles", "draw_calls", "gpu_bytes", "validation_enabled", "width", "height", "build_configuration", "requested_local_shadow_faces", "rendered_local_shadow_faces", "dropped_shadow_faces", "shadow_atlas_full_drops", "gpu_post_raster_ms", "gpu_post_visible", ) TIMING_COLUMNS = ("gpu_main_raster_ms", "gpu_post_raster_ms", "gpu_ms", "gpu_shadow_ms", "cpu_ms", "readback_cpu_ms") TILED_TIMING_COLUMNS = ("gpu_light_tiles_ms", "gpu_build_plus_raster_ms") TILED_COLUMNS = ("requested_lighting", *TILED_TIMING_COLUMNS, "light_tile_count", "light_tile_counts_valid", "light_tile_candidate_count", "light_tile_overflow_count") SHADOW_COLUMNS = ("requested_local_shadow_faces", "rendered_local_shadow_faces", "shadow_tiles", "dropped_shadow_faces", "shadow_atlas_full_drops") def build_runs(shadows: str = "both") -> list[dict]: if shadows not in ("off", "on", "both"): raise ValueError(f"Unsupported shadow setting: {shadows}") settings = ("off", "on") if shadows == "both" else (shadows,) return [{"shadows": shadow, "visibility": mode, "light_count": lights, "repeat": repeat} for shadow in settings for repeat in REPEATS for mode in VISIBILITY_MODES for lights in MEASUREMENT_ORDER] def median(values: list[float]) -> float: if not values: raise ValueError("Cannot summarize empty measurements") return float(statistics.median(values)) def p95(values: list[float]) -> float: if not values: raise ValueError("Cannot summarize empty measurements") ordered = sorted(values) return ordered[math.ceil(.95 * len(ordered)) - 1] def _measurement(row: dict, name: str) -> float: try: value = float(row[name]) except (KeyError, TypeError, ValueError) as error: raise ValueError(f"Invalid {name} in benchmark CSV") from error if not math.isfinite(value) or value < 0: raise ValueError(f"Invalid {name} in benchmark CSV: {value}") return value def _timing(row: dict, name: str) -> float: if name == "forward_raster_ms": main = _measurement(row, "gpu_main_raster_ms") return main + (_measurement(row, "gpu_post_raster_ms") if row["visibility"] == "gpu-occlusion" else 0) return _measurement(row, name) def _count(row: dict, name: str) -> int: try: value = int(row[name]) except (KeyError, TypeError, ValueError) as error: raise ValueError(f"Invalid {name} in benchmark CSV") from error if value < 0: raise ValueError(f"Invalid {name} in benchmark CSV: {value}") return value def summarize_rows(rows: list[dict], evaluate_forward_plus_gate: bool = True) -> dict: """Use the median of each independent run's median, then compare like baselines.""" if not rows: raise ValueError("Cannot summarize empty measurements") tiled_metrics = all(all(name in row for name in TILED_TIMING_COLUMNS) for row in rows) if any(any(name in row for name in TILED_TIMING_COLUMNS) for row in rows) and not tiled_metrics: raise ValueError("Tiled timing columns are incomplete across benchmark rows") timing_columns = (*TIMING_COLUMNS, *(TILED_TIMING_COLUMNS if tiled_metrics else ())) summary_timings = (*timing_columns, "forward_raster_ms") grouped: dict[tuple[str, str, int], dict[int, list[dict]]] = {} for row in rows: try: key = (row["shadows"], row["visibility"], int(row["light_count"])) repeat = int(row["run_index"]) except (KeyError, TypeError, ValueError) as error: raise ValueError("Benchmark row lacks shadow/mode/light/repeat identity") from error if key[0] not in ("off", "on") or key[1] not in VISIBILITY_MODES or repeat < 1: raise ValueError(f"Invalid benchmark configuration: {key}, repeat {repeat}") for name in timing_columns: _measurement(row, name) for name in SHADOW_COLUMNS: _count(row, name) grouped.setdefault(key, {}).setdefault(repeat, []).append(row) configurations = [] lookup = {} for (shadows, visibility, lights), repeats in sorted(grouped.items()): run_summaries = [] for repeat, samples in sorted(repeats.items()): run_summaries.append({ "run_index": repeat, "frames": len(samples), "median_ms": {name: median([_timing(row, name) for row in samples]) for name in summary_timings}, }) shadow_counts = {name: {_count(row, name) for samples in repeats.values() for row in samples} for name in SHADOW_COLUMNS} if any(len(values) != 1 for values in shadow_counts.values()): raise ValueError("Shadow counts changed within a fixed benchmark configuration") entry = { "shadows": shadows, "visibility": visibility, "light_count": lights, "runs": run_summaries, "shadow_counts": {name: next(iter(values)) for name, values in shadow_counts.items()}, "median_ms": {name: median([run["median_ms"][name] for run in run_summaries]) for name in summary_timings}, "p95_ms": {name: p95([_timing(row, name) for samples in repeats.values() for row in samples]) for name in summary_timings}, } configurations.append(entry) lookup[(shadows, visibility, lights)] = entry if not evaluate_forward_plus_gate: return {"configurations": configurations, "forward_plus_gate": None} candidates = [] evaluated = [] for entry in configurations: if entry["light_count"] not in (32, 64, 128): continue baseline = lookup.get((entry["shadows"], entry["visibility"], 0)) if baseline is None: raise ValueError("Forward+ gate requires a zero-light baseline for each mode/shadow setting") base_runs = {run["run_index"]: run for run in baseline["runs"]} paired = [(run, base_runs[run["run_index"]]) for run in entry["runs"] if run["run_index"] in base_runs] if len(paired) != len(entry["runs"]): raise ValueError("Forward+ gate requires a matched zero-light repeat for every run") zero_gpu = median([base["median_ms"]["gpu_ms"] for _, base in paired]) if zero_gpu <= 0: raise ValueError("Forward+ gate requires positive zero-light GPU frame timing") overhead = median([run["median_ms"]["forward_raster_ms"] - base["median_ms"]["forward_raster_ms"] for run, base in paired]) result = {"shadows": entry["shadows"], "visibility": entry["visibility"], "light_count": entry["light_count"], "overhead_ms": overhead, "raster_metric": ("main_plus_post" if entry["visibility"] == "gpu-occlusion" else "main"), "zero_light_gpu_ms": zero_gpu, "overhead_percent_of_zero_gpu": 100 * overhead / zero_gpu, "absolute_threshold_reached": overhead >= 1.0, "relative_threshold_reached": overhead >= .15 * zero_gpu} evaluated.append(result) if result["absolute_threshold_reached"] or result["relative_threshold_reached"]: candidates.append(result) return {"configurations": configurations, "forward_plus_gate": {"triggered": bool(candidates), "candidates": candidates, "evaluated": evaluated, "basis": "median of paired per-run raster overheads; same-mode/shadow/repeat zero-light GPU baseline"}} def _read_run_csv(path: Path, run: dict, commit: str, driver: str, validation: str, lighting: str | None = None) -> tuple[list[str], list[dict]]: with path.open(newline="", encoding="utf-8") as stream: reader = csv.DictReader(stream) columns = reader.fieldnames or [] missing = sorted(set(REQUIRED_COLUMNS) - set(columns)) if lighting is not None: missing += sorted(set(TILED_COLUMNS) - set(columns)) if missing: raise ValueError(f"{path}: missing CSV column(s): {', '.join(missing)}") rows = list(reader) if len(rows) != MEASURED_FRAMES: raise ValueError(f"{path}: expected {MEASURED_FRAMES} measured frames, got {len(rows)}") frames = set() for row in rows: expected = {"light_count": str(run["light_count"]), "shadows": run["shadows"], "visibility": run["visibility"], "run_index": str(run["repeat"]), "commit": commit, "width": str(WIDTH), "height": str(HEIGHT)} for name, value in expected.items(): if row[name] != value: raise ValueError(f"{path}: {name} mismatch: expected {value}, got {row[name]}") if row["build_configuration"] != "Release": raise ValueError(f"{path}: Forward+ sweep requires a Release benchmark binary") if row["driver"] != driver: raise ValueError(f"{path}: driver differs from the declared driver identity") if row["validation_enabled"] != ("1" if validation == "on" else "0"): raise ValueError(f"{path}: validation_enabled differs from the requested setting") if row["effective_visibility"] != run["visibility"]: raise ValueError(f"{path}: effective_visibility fell back from {run['visibility']}") if row["submitted_local_lights"] != str(run["light_count"]) or row["omitted_local_lights"] != "0": raise ValueError(f"{path}: submitted_local_lights or omitted_local_lights disagrees with the workload") if lighting is not None: if row["requested_lighting"] != lighting: raise ValueError(f"{path}: requested_lighting disagrees with --lighting {lighting}") expected_path = "forward" if lighting == "forward" or run["light_count"] == 0 else "tiled" if lighting != "auto" and row["lighting_path"] != expected_path: raise ValueError(f"{path}: lighting_path fell back from {lighting}") if row["lighting_path"] not in ("forward", "tiled"): raise ValueError(f"{path}: unknown lighting_path") tile_time = _measurement(row, "gpu_light_tiles_ms") build_plus_raster = _measurement(row, "gpu_build_plus_raster_ms") raster = (_measurement(row, "gpu_main_raster_ms") + _measurement(row, "gpu_post_raster_ms")) if abs(build_plus_raster - (raster + tile_time)) > 0.000005: raise ValueError(f"{path}: gpu_build_plus_raster_ms disagrees with pass timings") tile_count = _count(row, "light_tile_count") counts_valid = _count(row, "light_tile_counts_valid") candidates = _count(row, "light_tile_candidate_count") overflows = _count(row, "light_tile_overflow_count") if counts_valid not in (0, 1) or overflows > tile_count: raise ValueError(f"{path}: invalid light tile counters") if row["lighting_path"] == "tiled" and (tile_count == 0 or tile_time == 0): raise ValueError(f"{path}: tiled path lacks tiles or GPU build timing") if row["lighting_path"] == "forward" and (tile_count or tile_time or candidates or overflows): raise ValueError(f"{path}: forward path unexpectedly built light tiles") if not counts_valid and (candidates or overflows): raise ValueError(f"{path}: light tile counts reported without diagnostic readback") try: frame = int(row["frame"]) errors = int(row["validation_errors"]) except ValueError as error: raise ValueError(f"{path}: invalid frame or validation error count") from error if frame in frames or errors != 0: raise ValueError(f"{path}: duplicate frame or Vulkan validation error") frames.add(frame) if not row["device"] or not row["driver"] or not row["lighting_path"]: raise ValueError(f"{path}: device, driver and effective lighting path are required") requested = _count(row, "requested_local_shadow_faces") rendered = _count(row, "rendered_local_shadow_faces") tiles = _count(row, "shadow_tiles") dropped = _count(row, "dropped_shadow_faces") atlas_drops = _count(row, "shadow_atlas_full_drops") expected_faces = 6 * run["light_count"] if run["shadows"] == "on" else 0 if (requested != expected_faces or rendered > tiles or tiles > min(requested, 16) or dropped > requested or atlas_drops > dropped): raise ValueError(f"{path}: requested/effective shadow face counts disagree with the workload") _count(row, "gpu_post_visible") for name in TIMING_COLUMNS: _measurement(row, name) return columns, rows def _git_revision() -> str: root = Path(__file__).resolve().parents[1] return subprocess.check_output(["git", "-C", str(root), "rev-parse", "HEAD"], text=True).strip() def _binary_sha256(path: Path) -> str: with path.open("rb") as stream: return hashlib.file_digest(stream, "sha256").hexdigest() def _shader_bundle_manifest(executable: Path) -> dict[str, str] | None: # Test fixtures are Python programs. A native renderer loads SPIR-V from # the shader directory beside its executable before checking other roots. if executable.suffix.lower() == ".py": return None directory = executable.parent / "shaders" required = ("vertexMain.spv", "fragmentMain.spv") if not all((directory / name).is_file() for name in required): raise ValueError(f"Benchmark shader bundle is missing beside {executable}") files = sorted((path for path in directory.iterdir() if path.is_file() and (path.suffix == ".spv" or path.name.endswith(".reflection.json"))), key=lambda path: path.name) return {path.name: _binary_sha256(path) for path in files} def _clean_source_revision(root: Path, expected: str) -> str: revision = subprocess.check_output(["git", "-C", str(root), "rev-parse", "HEAD"], text=True).strip() if revision != expected: raise ValueError(f"Source revision {revision} disagrees with benchmark commit {expected}") status = subprocess.check_output(["git", "-C", str(root), "status", "--porcelain", "--untracked-files=all"], text=True) if status: raise ValueError("Benchmark source checkout is dirty; commit sources before measurement") return revision def sweep(executable: Path, output: Path, shadows: str, commit: str, validation: str = "off", driver: str | None = None, source_root: Path | None = None, lighting: str | None = None) -> dict: if not executable.is_file(): raise ValueError(f"Benchmark executable does not exist: {executable}") if driver is None or not driver.strip() or driver.strip().lower() == "unknown": raise ValueError("A measured sweep requires an explicit --driver identity") if lighting not in (None, "auto", "forward", "tiled"): raise ValueError(f"Unknown lighting mode: {lighting}") source = (source_root or Path(__file__).resolve().parents[1]).resolve() revision = _clean_source_revision(source, commit) binary_sha256 = _binary_sha256(executable) shader_manifest = _shader_bundle_manifest(executable) if output.exists() and any(output.iterdir()): raise ValueError(f"Output directory must be new or empty: {output}") raw = output / "raw" raw.mkdir(parents=True) all_rows = [] columns = None identity = None lighting_paths: set[str] = set() runs = build_runs(shadows) command_prefix = [sys.executable, str(executable)] if executable.suffix.lower() == ".py" else [str(executable)] run_order = [] for acquisition_index, run in enumerate(runs): filename = (f"shadows-{run['shadows']}_{run['visibility']}_" f"lights-{run['light_count']:03d}_run-{run['repeat']}.csv") target = raw / filename command = command_prefix + [ "--lights", str(run["light_count"]), "--shadows", run["shadows"], "--visibility", run["visibility"], "--csv", str(target), "--run-index", str(run["repeat"]), "--commit", commit, "--validation", validation, "--width", str(WIDTH), "--height", str(HEIGHT), "--warmup", str(WARMUP_FRAMES), "--frames", str(MEASURED_FRAMES), ] if driver is not None: command += ["--driver", driver] if lighting is not None: command += ["--lighting", lighting] result = subprocess.run(command, capture_output=True, text=True, encoding="utf-8", errors="replace", timeout=180) if result.returncode != 0: raise RuntimeError(f"Benchmark failed for {filename}: {result.stderr[-2000:]}") run_columns, samples = _read_run_csv(target, run, commit, driver, validation, lighting) if columns is None: columns = run_columns elif columns != run_columns: raise ValueError(f"{target}: CSV schema differs from other runs") for row in samples: actual = (row["device"], row["driver"], row["validation_enabled"], row["build_configuration"]) if identity is None: identity = actual elif identity != actual: changed = next(name for name, before, after in zip( ("device", "driver", "validation_enabled", "build_configuration"), identity, actual) if before != after) raise ValueError(f"{target}: {changed} changed during the sweep") lighting_paths.add(row["lighting_path"]) if lighting is None and len(lighting_paths) > 1: raise ValueError(f"{target}: lighting_path changed during the sweep") all_rows.append({**row, "source_csv": filename, "acquisition_index": acquisition_index}) run_order.append(filename) merged = output / "merged.csv" with merged.open("w", newline="", encoding="utf-8") as stream: writer = csv.DictWriter(stream, fieldnames=[*(columns or []), "source_csv", "acquisition_index"]) writer.writeheader() writer.writerows(all_rows) if (_binary_sha256(executable) != binary_sha256 or _shader_bundle_manifest(executable) != shader_manifest or _clean_source_revision(source, commit) != revision): raise ValueError("Benchmark binary, shader bundle or source changed during the sweep") summary = {"format": "faset.p3-lighting-benchmark", "version": 2 if lighting else 1, "commit": commit, "warmup_frames_per_run": WARMUP_FRAMES, "measured_frames_per_run": MEASURED_FRAMES, "width": WIDTH, "height": HEIGHT, "validation": validation, "driver": driver, "source_revision": revision, "source_root": str(source), "source_dirty": False, "benchmark_sha256": binary_sha256, "shader_bundle": shader_manifest, "device": identity[0], "lighting_path": next(iter(lighting_paths)) if len(lighting_paths) == 1 else "mixed", "requested_lighting": lighting, "validation_enabled": identity[2] == "1", "build_configuration": identity[3], "run_order": run_order, "runs_completed": len(runs), "rows": len(all_rows), **summarize_rows(all_rows, evaluate_forward_plus_gate=lighting != "tiled")} (output / "summary.json").write_text(json.dumps(summary, indent=2) + "\n", encoding="utf-8") return summary def compare_sweeps(forward: dict, tiled: dict) -> dict: """Compare matched Release configurations from one binary and shader bundle.""" if forward.get("requested_lighting") != "forward" or tiled.get("requested_lighting") != "tiled": raise ValueError("Comparison requires explicit forward and tiled sweeps") identity_fields = ("source_revision", "benchmark_sha256", "shader_bundle", "device", "driver", "validation", "width", "height", "warmup_frames_per_run", "measured_frames_per_run", "build_configuration", "runs_completed", "rows") for name in identity_fields: if name not in forward or name not in tiled or forward[name] != tiled[name]: raise ValueError(f"Forward/tiled comparison has different {name}") if forward["build_configuration"] != "Release": raise ValueError("Forward/tiled comparison requires Release") def keyed(summary: dict) -> dict[tuple[str, str, int], dict]: configurations = summary.get("configurations") if not isinstance(configurations, list) or not configurations: raise ValueError("Comparison has no measured configurations") result = {} for entry in configurations: key = (entry["shadows"], entry["visibility"], int(entry["light_count"])) if key in result: raise ValueError(f"Comparison has duplicate configuration {key}") result[key] = entry return result forward_configs, tiled_configs = keyed(forward), keyed(tiled) if forward_configs.keys() != tiled_configs.keys(): raise ValueError("Forward/tiled comparison has unmatched configurations") comparisons = [] for key in sorted(forward_configs): f, t = forward_configs[key], tiled_configs[key] f_runs = {int(run["run_index"]): run for run in f["runs"]} t_runs = {int(run["run_index"]): run for run in t["runs"]} if not f_runs or f_runs.keys() != t_runs.keys(): raise ValueError(f"Comparison has unmatched repeats for {key}") differences = [] for repeat in sorted(f_runs): f_run, t_run = f_runs[repeat], t_runs[repeat] if f_run["frames"] != t_run["frames"] or f_run["frames"] != forward["measured_frames_per_run"]: raise ValueError(f"Comparison has unmatched frame counts for {key}") f_time = _measurement(f_run["median_ms"], "gpu_build_plus_raster_ms") t_time = _measurement(t_run["median_ms"], "gpu_build_plus_raster_ms") if f_time <= 0 or t_time <= 0: raise ValueError(f"Comparison needs positive GPU timing for {key}") differences.append(t_time - f_time) f_median = median([_measurement(run["median_ms"], "gpu_build_plus_raster_ms") for run in f_runs.values()]) t_median = median([_measurement(run["median_ms"], "gpu_build_plus_raster_ms") for run in t_runs.values()]) delta = median(differences) comparisons.append({"shadows": key[0], "visibility": key[1], "light_count": key[2], "median_forward_ms": f_median, "median_tiled_ms": t_median, "delta_tiled_minus_forward_ms": delta, "relative_change_percent": 100 * delta / f_median, "repeat_deltas_ms": differences}) return {"format": "faset.p3-lighting-comparison", "version": 1, "source_revision": forward["source_revision"], "benchmark_sha256": forward["benchmark_sha256"], "shader_bundle": forward["shader_bundle"], "device": forward["device"], "driver": forward["driver"], "configurations": len(comparisons), "comparisons": comparisons} def main() -> int: parser = argparse.ArgumentParser(description=__doc__) mode = parser.add_mutually_exclusive_group(required=True) mode.add_argument("--list-runs", action="store_true", help="Print the deterministic sweep matrix as JSON") mode.add_argument("--sweep", action="store_true", help="Run every configuration and retain raw CSV") mode.add_argument("--compare", action="store_true", help="Compare two measured sweep summaries") parser.add_argument("--shadows", choices=("off", "on", "both"), default="both") parser.add_argument("--executable", type=Path, help="Built C++ benchmark executable") parser.add_argument("--output", type=Path, help="New or empty evidence directory") parser.add_argument("--commit", help="Source revision; defaults to this checkout's HEAD") parser.add_argument("--source-root", type=Path, help="Clean source checkout used to build the benchmark; defaults to this repo") parser.add_argument("--driver", help="Required driver identity for a measured sweep") parser.add_argument("--validation", choices=("on", "off"), default="off") parser.add_argument("--lighting", choices=("auto", "forward", "tiled"), help="Explicit rendering path for a post-Forward+ sweep") parser.add_argument("--forward-summary", type=Path) parser.add_argument("--tiled-summary", type=Path) parser.add_argument("--comparison-output", type=Path) args = parser.parse_args() if args.list_runs: print(json.dumps({"format": "faset.p3-lighting-run-matrix", "version": 1, "runs": build_runs(args.shadows)}, indent=2)) return 0 if args.compare: if args.forward_summary is None or args.tiled_summary is None: parser.error("--compare requires --forward-summary and --tiled-summary") try: forward = json.loads(args.forward_summary.read_text(encoding="utf-8")) tiled = json.loads(args.tiled_summary.read_text(encoding="utf-8")) result = compare_sweeps(forward, tiled) rendered = json.dumps(result, indent=2) + "\n" if args.comparison_output is not None: args.comparison_output.write_text(rendered, encoding="utf-8") else: print(rendered, end="") except (OSError, ValueError, KeyError, TypeError) as error: print(f"P3 lighting comparison failed: {error}", file=sys.stderr) return 1 return 0 if args.executable is None or args.output is None: parser.error("--sweep requires --executable and --output") try: summary = sweep(args.executable.resolve(), args.output.resolve(), args.shadows, args.commit or _git_revision(), args.validation, args.driver, args.source_root, args.lighting) except (OSError, ValueError, RuntimeError, subprocess.CalledProcessError) as error: print(f"P3 lighting benchmark failed: {error}", file=sys.stderr) return 1 print(json.dumps({"summary": str(args.output.resolve() / "summary.json"), "runs_completed": summary["runs_completed"], "forward_plus_threshold_reached": (summary["forward_plus_gate"] or {}).get("triggered")})) return 0 if __name__ == "__main__": raise SystemExit(main())