Wallclock time plots

wallclock_time_plots.py

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+import re
+import polars as pl
+import seaborn as sns
+import matplotlib.pyplot as plt
+from datetime import timedelta
+
+from pathlib import Path
+
+stats_dir = Path("pim_out")
+
+runtime_dict: dict[str, list[any]] = {}
+
+for element in stats_dir.iterdir():
+    print(element.name)
+    matches = re.search(r'(\w+)_(\w+)_(\w*-*\w*)_(\w+)', element.name)
+    workload, level, system, freq = matches.group(1), matches.group(2), matches.group(3), matches.group(4)
+
+    with open(element / "stats.txt") as f:
+        regex = re.compile(r'hostSeconds\ +(\d+.\d+).*')
+        for line in f:
+            result = regex.search(line)
+            if result is not None:
+                # implicitly only get last match in file...
+                runtime = result.group(1)
+
+    runtime_dict.setdefault("workload", []).append(workload)
+    runtime_dict.setdefault("level", []).append(level)
+    runtime_dict.setdefault("system", []).append(system)
+    runtime_dict.setdefault("freq", []).append(freq)
+    runtime_dict.setdefault("runtime", []).append(float(runtime))
+
+df = pl.DataFrame(runtime_dict)
+df = df.filter((pl.col("freq") == "100GHz") & (pl.col("level") == "X3"))
+df = df.drop("freq")
+print(df)
+
+plot = sns.catplot(
+    data=df.to_pandas(),
+    kind="bar",
+    x="system",
+    y="runtime",
+    hue="workload",
+    palette="dark",
+    alpha=0.6,
+    height=6,
+)
+plot.set_axis_labels("PIM vs. Non-PIM", "Runtime [s]")
+plot.set(title="Wallclock Time")
+
+plot.fig.subplots_adjust(top=0.95)
+
+plt.show()