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Modifying scripts

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This commit is contained in:
Carlos Gutierrez
2025-10-04 22:05:52 -04:00
parent c8077ae1ac
commit b69c9050f5
5 changed files with 106 additions and 106 deletions
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23
scripts/11_run_all.sh
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@@ -1,23 +0,0 @@
#!/bin/bash
set -eu
. "$(dirname "$0")/env.sh"
run_case () {
W=$1; CORE=$2; DV=$3; D=$4; L2=$5
sh "$(dirname "$0")/run_one.sh" "$W" "$CORE" "$DV" "$D" "$L2" 16GB
}
for W in tinyml_kws sensor_fusion aes_ccm attention_kernel; do
for DV in high low; do
for D in 0 1; do
for L2 in 512kB 1MB; do
run_case "$W" big "$DV" "$D" "$L2"
run_case "$W" little "$DV" "$D" "$L2"
run_case "$W" hybrid "$DV" "$D" "$L2"
done
done
done
done
echo "[run_all] ALL DONE"

63
scripts/40_energy_post.py
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@@ -1,48 +1,51 @@
#!/usr/bin/env python3
import csv, os, sys
import csv
import os
ROOT = "/home/carlos/projects/gem5"
OUT_DATA = os.path.join(ROOT, "gem5-data", "SmartEdgeAI", "results")
OUT_IOT = os.path.join(ROOT, "iot", "results")
OUT_IOT = os.path.join(ROOT, "iot", "results")
src = os.path.join(OUT_DATA, "summary.csv")
dst_data = os.path.join(OUT_DATA, "summary_energy.csv")
dst_iot = os.path.join(OUT_IOT, "summary_energy.csv")
dst_iot = os.path.join(OUT_IOT, "summary_energy.csv")
# modeling constants (document in your 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 drop when drowsy=1
# Your model constants (document in Methods)
EPI_PJ = {"big": 200.0, "little": 80.0, "hybrid": 104.0}
E_MEM_PJ = 600.0
DROWSY_SCALE = 0.85
rows=[]
rows = []
with open(src) as f:
r=csv.DictReader(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=EPI_PJ.get(core, EPI_PJ['little'])
mr=float(row['l2_miss_rate']) if row['l2_miss_rate'] else 0.0
insts = float(row["insts"])
secs = float(row["sim_seconds"])
core = row["core"]
drowsy = int(row["drowsy"])
epi = 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
energy_J = (epi*1e-12)*insts + (E_MEM_PJ*1e-12)*l2_misses
if drowsy==1:
energy_J *= DROWSY_SCALE
energy = (epi * 1e-12) * insts + (E_MEM_PJ * 1e-12) * l2_misses
if drowsy == 1:
energy *= DROWSY_SCALE
power = energy / secs if secs > 0 else 0.0
edp = energy * secs
power_W = energy_J/secs if secs>0 else 0.0
edp = energy_J * secs # J*s
row.update({
'energy_J': f"{energy_J:.6f}",
'power_W': f"{power_W:.6f}",
'edp': f"{edp:.6e}",
'epi_model_pJ': f"{epi:.1f}",
})
row.update(
{
"energy_J": f"{energy:.6f}",
"power_W": f"{power:.6f}",
"edp": f"{edp:.6e}",
"epi_model_pJ": f"{epi:.1f}",
}
)
rows.append(row)
for path in (dst_data, dst_iot):
with open(path, 'w', newline='') as f:
w=csv.DictWriter(f, fieldnames=list(rows[0].keys()))
w.writeheader(); w.writerows(rows)
with open(path, "w", newline="") as f:
w = csv.DictWriter(f, fieldnames=list(rows[0].keys()))
w.writeheader()
w.writerows(rows)
print(f"[energy] wrote {dst_data} and mirrored to {dst_iot}")

42
scripts/50_plot_epi.py
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@@ -1,30 +1,34 @@
#!/usr/bin/env python3
import os, csv
import matplotlib.pyplot as plt
import csv
import os
from collections import defaultdict
ROOT="/home/carlos/projects/gem5"
OUT_DATA=os.path.join(ROOT,"gem5-data","SmartEdgeAI","results")
OUT_IOT =os.path.join(ROOT,"iot","results")
src=os.path.join(OUT_DATA,"summary_energy.csv")
out_data=os.path.join(OUT_DATA,"fig_epi_across_workloads.png")
out_iot =os.path.join(OUT_IOT ,"fig_epi_across_workloads.png")
import matplotlib.pyplot as plt
epi_by_core=defaultdict(list)
ROOT = "/home/carlos/projects/gem5"
OUT_DATA = os.path.join(ROOT, "gem5-data", "SmartEdgeAI", "results")
OUT_IOT = os.path.join(ROOT, "iot", "results")
src = os.path.join(OUT_DATA, "summary_energy.csv")
out_data = os.path.join(OUT_DATA, "fig_epi_across_workloads.png")
out_iot = os.path.join(OUT_IOT, "fig_epi_across_workloads.png")
epi_by_core = defaultdict(list)
with open(src) as f:
r=csv.DictReader(f)
r = csv.DictReader(f)
for row in r:
insts=float(row['insts']); energy=float(row['energy_J'])
epi = 1e12*energy/insts if insts>0 else 0.0
epi_by_core[row['core']].append(epi)
insts = float(row["insts"])
energy = float(row["energy_J"])
epi = 1e12 * energy / insts if insts > 0 else 0.0
epi_by_core[row["core"]].append(epi)
cores=['big','little','hybrid']
vals=[sum(epi_by_core[c])/max(1,len(epi_by_core[c])) for c in cores]
cores = ["big", "little", "hybrid"]
vals = [sum(epi_by_core[c]) / max(1, len(epi_by_core[c])) for c in cores]
plt.figure()
plt.bar(cores, vals)
plt.ylabel('EPI (pJ/inst)')
plt.title('Energy per Instruction across workloads (avg by core mode)')
plt.tight_layout(); plt.savefig(out_data); plt.savefig(out_iot)
plt.ylabel("EPI (pJ/inst)")
plt.title("Energy per Instruction across workloads (avg by core mode)")
plt.tight_layout()
plt.savefig(out_data)
plt.savefig(out_iot)
print(f"[plot] wrote {out_data} and mirrored to {out_iot}")

37
scripts/51_plot_edp_tinyml.py
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@@ -1,27 +1,32 @@
#!/usr/bin/env python3
import os, csv
import csv
import os
import matplotlib.pyplot as plt
ROOT="/home/carlos/projects/gem5"
OUT_DATA=os.path.join(ROOT,"gem5-data","SmartEdgeAI","results")
OUT_IOT =os.path.join(ROOT,"iot","results")
src=os.path.join(OUT_DATA,"summary_energy.csv")
out_data=os.path.join(OUT_DATA,"fig_tinyml_edp.png")
out_iot =os.path.join(OUT_IOT ,"fig_tinyml_edp.png")
ROOT = "/home/carlos/projects/gem5"
OUT_DATA = os.path.join(ROOT, "gem5-data", "SmartEdgeAI", "results")
OUT_IOT = os.path.join(ROOT, "iot", "results")
src = os.path.join(OUT_DATA, "summary_energy.csv")
out_data = os.path.join(OUT_DATA, "fig_tinyml_edp.png")
out_iot = os.path.join(OUT_IOT, "fig_tinyml_edp.png")
labels=[]; edps=[]
labels = []
edps = []
with open(src) as f:
r=csv.DictReader(f)
r = csv.DictReader(f)
for row in r:
if row['workload']!='tinyml_kws': continue
if row["workload"] != "tinyml_kws":
continue
labels.append(f"{row['core']}-{row['dvfs']}-L2{row['l2']}-d{row['drowsy']}")
edps.append(float(row['edp']))
edps.append(float(row["edp"]))
plt.figure()
plt.bar(labels, edps)
plt.ylabel('EDP (J·s)')
plt.title('TinyML: EDP by configuration')
plt.xticks(rotation=60, ha='right')
plt.tight_layout(); plt.savefig(out_data); plt.savefig(out_iot)
plt.ylabel("EDP (J·s)")
plt.title("TinyML: EDP by configuration")
plt.xticks(rotation=60, ha="right")
plt.tight_layout()
plt.savefig(out_data)
plt.savefig(out_iot)
print(f"[plot] wrote {out_data} and mirrored to {out_iot}")

47
scripts/70_diff_table.py
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@@ -1,34 +1,45 @@
#!/usr/bin/env python3
import csv, os
import csv
import os
root = os.path.dirname(os.path.dirname(__file__))
src = os.path.join(root, "results", "phase3_summary_energy.csv")
dst = os.path.join(root, "results", "phase3_drowsy_deltas.csv")
# group by key without drowsy; compare d0 vs d1
from collections import defaultdict
bykey = defaultdict(dict)
with open(src) as f:
r=csv.DictReader(f)
r = csv.DictReader(f)
for row in r:
key = (row['workload'], row['core'], row['dvfs'], row['l2'])
bykey[key][row['drowsy']] = row
key = (row["workload"], row["core"], row["dvfs"], row["l2"])
bykey[key][row["drowsy"]] = row
rows=[]
rows = []
for k, d in bykey.items():
if '0' in d and '1' in d:
a=d['0']; b=d['1']
e0=float(a['energy_J']); e1=float(b['energy_J'])
edp0=float(a['edp']); edp1=float(b['edp'])
rows.append({
'workload':k[0],'core':k[1],'dvfs':k[2],'l2':k[3],
'energy_drop_%': f"{100*(e0-e1)/e0:.2f}",
'edp_drop_%': f"{100*(edp0-edp1)/edp0:.2f}"
})
if "0" in d and "1" in d:
a = d["0"]
b = d["1"]
e0 = float(a["energy_J"])
e1 = float(b["energy_J"])
edp0 = float(a["edp"])
edp1 = float(b["edp"])
rows.append(
{
"workload": k[0],
"core": k[1],
"dvfs": k[2],
"l2": k[3],
"energy_drop_%": f"{100*(e0-e1)/e0:.2f}",
"edp_drop_%": f"{100*(edp0-edp1)/edp0:.2f}",
}
)
with open(dst,'w',newline='') as f:
w=csv.DictWriter(f, fieldnames=list(rows[0].keys()))
w.writeheader(); w.writerows(rows)
with open(dst, "w", newline="") as f:
w = csv.DictWriter(f, fieldnames=list(rows[0].keys()))
w.writeheader()
w.writerows(rows)
print(f"[delta] wrote {dst}")