| |
| from __future__ import annotations |
|
|
| import json |
| from pathlib import Path |
|
|
| import matplotlib |
| matplotlib.use("Agg") |
| import matplotlib.pyplot as plt |
| import pandas as pd |
| import sqlite3 |
|
|
|
|
| WNS_KEYS = [ |
| "timing__setup__wns", |
| "timing__setup__WNS", |
| "finish__timing__setup__wns", |
| "timing__setup__ws", |
| "finish__timing__setup__ws", |
| "route__timing__setup__ws", |
| "cts__timing__setup__ws", |
| "detailedplace__timing__setup__ws", |
| "floorplan__timing__setup__ws", |
| "globalplace__timing__setup__ws", |
| "globalroute__timing__setup__ws", |
| "placeopt__timing__setup__ws", |
| ] |
|
|
| AREA_KEYS = [ |
| "finish__design__die__area", |
| "globalroute__design__die__area", |
| "placeopt__design__die__area", |
| "detailedplace__design__die__area", |
| "floorplan__design__die__area", |
| "design__die__area", |
| ] |
|
|
|
|
| def pick_first(metrics: dict, keys: list[str]) -> float | None: |
| for k in keys: |
| if k in metrics: |
| try: |
| return float(metrics[k]) |
| except Exception: |
| return None |
| lower = {kk.lower(): kk for kk in metrics.keys()} |
| for k in keys: |
| kk = lower.get(k.lower()) |
| if kk: |
| try: |
| return float(metrics[kk]) |
| except Exception: |
| return None |
| return None |
|
|
|
|
| def load_metrics(mj: str | None) -> dict | None: |
| if not mj: |
| return None |
| try: |
| return json.loads(mj) |
| except Exception: |
| return None |
|
|
|
|
| def main() -> None: |
| import argparse |
|
|
| p = argparse.ArgumentParser(description="Generate Pareto scatter (area vs WNS)") |
| p.add_argument("--db", default="runs/sweep_finish.sqlite", help="SQLite database path") |
| p.add_argument("--out", default="runs/sweep_finish/plots/pareto_area_vs_wns", help="Output path without extension") |
| args = p.parse_args() |
|
|
| con = sqlite3.connect(args.db) |
| df = pd.read_sql_query("SELECT * FROM trials", con) |
| con.close() |
|
|
| rows = [] |
| for _, row in df.iterrows(): |
| metrics = load_metrics(row.get("metrics_json")) |
| if not metrics: |
| continue |
| wns = pick_first(metrics, WNS_KEYS) |
| area = pick_first(metrics, AREA_KEYS) |
| if wns is None or area is None: |
| continue |
| rows.append({"wns": wns, "area": area, "fidelity": row.get("fidelity", "unknown")}) |
|
|
| if not rows: |
| print("No points with both WNS and area found.") |
| return |
|
|
| plot_df = pd.DataFrame(rows) |
| colors = { |
| "synth": "#999999", |
| "place": "#4B8BBE", |
| "route": "#306998", |
| "finish": "#E07B39", |
| "unknown": "#666666", |
| } |
| markers = { |
| "synth": "o", |
| "place": "s", |
| "route": "^", |
| "finish": "D", |
| "unknown": "o", |
| } |
|
|
| fig, ax = plt.subplots(figsize=(6.4, 4.6)) |
| for fid, group in plot_df.groupby("fidelity"): |
| ax.scatter( |
| group["area"], |
| group["wns"], |
| label=fid, |
| color=colors.get(fid, "#666666"), |
| marker=markers.get(fid, "o"), |
| alpha=0.75, |
| edgecolors="none", |
| ) |
|
|
| ax.axhline(0.0, color="#333333", linewidth=0.8, linestyle="--") |
| ax.set_xlabel("Die area (um^2)") |
| ax.set_ylabel("WNS (ns)") |
| ax.set_title("Area vs WNS (Pareto scatter)") |
| ax.legend(frameon=False, fontsize=8, loc="best") |
| fig.tight_layout() |
|
|
| out_base = Path(args.out) |
| out_base.parent.mkdir(parents=True, exist_ok=True) |
| fig.savefig(out_base.with_suffix(".png"), dpi=300) |
| fig.savefig(out_base.with_suffix(".pdf")) |
| plt.close(fig) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
