Adding scripts, commands, and logging scaffolding"

scripts/40_energy_post.py

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+#!/usr/bin/env python3
+import csv, sys, os
+
+root = os.path.dirname(os.path.dirname(__file__))
+src = os.path.join(root, "results", "phase3_summary.csv")
+dst = os.path.join(root, "results", "phase3_summary_energy.csv")
+
+# === your modeling constants (document in Methods) ===
+EPI_PJ = {'big': 200.0, 'little': 80.0, 'hybrid': 104.0}  # pJ/inst
+E_MEM_PJ = 600.0                                          # pJ per L2 miss
+DROWSY_SCALE = 0.85                                       # 15% energy reduction when drowsy=1
+
+rows=[]
+with open(src) as f:
+    r=csv.DictReader(f)
+    for row in r:
+        insts = float(row['insts'])
+        secs  = float(row['sim_seconds'])
+        core  = row['core']
+        drowsy= int(row['drowsy'])
+        epi_pJ= EPI_PJ.get(core, EPI_PJ['little'])
+
+        mr = float(row['l2_miss_rate']) if row['l2_miss_rate'] else 0.0
+        l2_misses = mr * insts  # proxy; replace with MPKI-based calc if available
+
+        energy_instr = (epi_pJ * 1e-12) * insts
+        energy_mem   = (E_MEM_PJ * 1e-12) * l2_misses
+        energy_J     = energy_instr + energy_mem
+        if drowsy == 1:
+            energy_J *= DROWSY_SCALE
+
+        power_W = energy_J / secs if secs > 0 else 0.0
+        edp = energy_J * secs   # CORRECT EDP
+
+        row.update({
+            'energy_J': f"{energy_J:.6f}",
+            'power_W':  f"{power_W:.6f}",
+            'edp':      f"{edp:.6e}",
+            'epi_model_pJ': f"{epi_pJ:.1f}",
+        })
+        rows.append(row)
+
+with open(dst, 'w', newline='') as f:
+    w=csv.DictWriter(f, fieldnames=list(rows[0].keys()))
+    w.writeheader(); w.writerows(rows)
+
+print(f"[energy] wrote {dst}")
+