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Author: Yuy1L1

script/plot_real_device_suite.py

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+#!/usr/bin/env python3
+
+import argparse
+import csv
+from pathlib import Path
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+
+LABELS = {
+    "gromacs": "GROMACS",
+    "tigon_tpcc": "Tigon TPCC",
+    "mlc_idle": "MLC idle",
+    "wrf_short": "WRF-short",
+    "gapbs_bfs": "GAPBS BFS",
+    "gapbs_pr": "GAPBS PR",
+    "gapbs_cc": "GAPBS CC",
+    "gapbs_sssp": "GAPBS SSSP",
+}
+
+
+def load_records(summary_csv: Path) -> list[dict[str, str]]:
+    with summary_csv.open() as fh:
+        return list(csv.DictReader(fh))
+
+
+def compute_normalized(records: list[dict[str, str]], baseline_node: int, compare_node: int) -> list[dict[str, object]]:
+    by_workload: dict[str, dict[int, dict[str, str]]] = {}
+    for record in records:
+        if record["status"] != "ok":
+            continue
+        workload = record["workload"]
+        node = int(record["node"])
+        by_workload.setdefault(workload, {})[node] = record
+
+    normalized: list[dict[str, object]] = []
+    for workload, nodes in by_workload.items():
+        if baseline_node not in nodes or compare_node not in nodes:
+            continue
+        baseline = float(nodes[baseline_node]["metric_value"])
+        compare = float(nodes[compare_node]["metric_value"])
+        higher_is_better = nodes[baseline_node]["higher_is_better"].lower() == "true"
+        ratio = compare / baseline if higher_is_better else baseline / compare
+        normalized.append(
+            {
+                "workload": workload,
+                "label": LABELS.get(workload, workload),
+                "ratio": ratio,
+                "baseline": baseline,
+                "compare": compare,
+                "unit": nodes[baseline_node]["unit"],
+                "higher_is_better": higher_is_better,
+            }
+        )
+    return normalized
+
+
+def plot(normalized: list[dict[str, object]], output_dir: Path, baseline_node: int, compare_node: int) -> None:
+    output_dir.mkdir(parents=True, exist_ok=True)
+    labels = [entry["label"] for entry in normalized]
+    ratios = np.array([entry["ratio"] for entry in normalized], dtype=float)
+    colors = ["#0b6e4f" if ratio >= 1.0 else "#c84c09" for ratio in ratios]
+
+    fig, ax = plt.subplots(figsize=(8, 4), constrained_layout=True)
+    bars = ax.bar(labels, ratios, color=colors, width=0.68)
+    ax.axhline(1.0, color="#222222", linewidth=1.2, linestyle="--")
+    ax.set_ylabel(f"Normalized performance (node{compare_node} vs node{baseline_node})")
+    ax.set_title("Real-device benchmark comparison")
+    ax.set_ylim(0, max(1.4, ratios.max() * 1.18))
+    ax.tick_params(axis="x", rotation=20)
+
+    for bar, entry in zip(bars, normalized, strict=True):
+        height = bar.get_height()
+        ax.text(
+            bar.get_x() + bar.get_width() / 2.0,
+            height + 0.02,
+            f"{height:.2f}x",
+            ha="center",
+            va="bottom",
+            fontsize=9,
+        )
+        raw = f"n{baseline_node}={entry['baseline']:.1f} {entry['unit']}\n" f"n{compare_node}={entry['compare']:.1f} {entry['unit']}"
+        ax.text(
+            bar.get_x() + bar.get_width() / 2.0,
+            0.03,
+            raw,
+            ha="center",
+            va="bottom",
+            fontsize=7,
+            color="#333333",
+            rotation=90,
+        )
+
+    stem = output_dir / "real_device_normalized_performance"
+    fig.savefig(stem.with_suffix(".png"), dpi=220)
+    fig.savefig(stem.with_suffix(".pdf"))
+
+
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(description="Plot normalized real-device benchmark results")
+    parser.add_argument("summary_csv", type=Path, help="Path to summary.csv from run_real_device_suite.py")
+    parser.add_argument("--baseline-node", type=int, default=1, help="Baseline node for normalization")
+    parser.add_argument("--compare-node", type=int, default=2, help="Compared node for normalization")
+    parser.add_argument("--out-dir", type=Path, default=None, help="Figure output directory")
+    return parser.parse_args()
+
+
+def main() -> int:
+    args = parse_args()
+    records = load_records(args.summary_csv)
+    normalized = compute_normalized(records, args.baseline_node, args.compare_node)
+    if not normalized:
+        raise SystemExit("No comparable successful records found in summary.csv")
+    out_dir = args.out_dir or args.summary_csv.parent / "figures"
+    plot(normalized, out_dir, args.baseline_node, args.compare_node)
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())