49 lines
1.6 KiB
Python
Executable File
49 lines
1.6 KiB
Python
Executable File
#!/usr/bin/env python3
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import csv, os, sys
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ROOT = "/home/carlos/projects/gem5"
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OUT_DATA = os.path.join(ROOT, "gem5-data", "SmartEdgeAI", "results")
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OUT_IOT = os.path.join(ROOT, "iot", "results")
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src = os.path.join(OUT_DATA, "summary.csv")
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dst_data = os.path.join(OUT_DATA, "summary_energy.csv")
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dst_iot = os.path.join(OUT_IOT, "summary_energy.csv")
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# modeling constants (document in your Methods)
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EPI_PJ = {'big':200.0,'little':80.0,'hybrid':104.0} # pJ/inst
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E_MEM_PJ = 600.0 # pJ per L2 miss
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DROWSY_SCALE = 0.85 # 15% energy drop when drowsy=1
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rows=[]
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with open(src) as f:
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r=csv.DictReader(f)
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for row in r:
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insts=float(row['insts'])
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secs=float(row['sim_seconds'])
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core=row['core']; drowsy=int(row['drowsy'])
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epi=EPI_PJ.get(core, EPI_PJ['little'])
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mr=float(row['l2_miss_rate']) if row['l2_miss_rate'] else 0.0
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l2_misses = mr * insts
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energy_J = (epi*1e-12)*insts + (E_MEM_PJ*1e-12)*l2_misses
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if drowsy==1:
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energy_J *= DROWSY_SCALE
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power_W = energy_J/secs if secs>0 else 0.0
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edp = energy_J * secs # J*s
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row.update({
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'energy_J': f"{energy_J:.6f}",
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'power_W': f"{power_W:.6f}",
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'edp': f"{edp:.6e}",
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'epi_model_pJ': f"{epi:.1f}",
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})
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rows.append(row)
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for path in (dst_data, dst_iot):
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with open(path, 'w', newline='') as f:
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w=csv.DictWriter(f, fieldnames=list(rows[0].keys()))
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w.writeheader(); w.writerows(rows)
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print(f"[energy] wrote {dst_data} and mirrored to {dst_iot}")
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