File size: 1,973 Bytes
864f933 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 | import subprocess, time, os, sys
import numpy as np
sys.path.insert(0, os.path.expanduser('~/projects/machineai'))
os.chdir(os.path.expanduser('~/projects/machineai'))
from stable_baselines3 import PPO
from ir_feature_extractor import extract_features
import glob
SOURCE_FILES = glob.glob("benchmarks/*.c")
model = PPO.load("models/x86v2_base")
passes = {0:"",1:"loop-vectorize",2:"inline,loop-vectorize",
3:"loop-unroll,loop-vectorize",4:"inline,loop-unroll,loop-vectorize",5:"loop-unroll"}
def measure(exe, n=9):
times = []
for _ in range(n):
t0 = time.perf_counter()
r = subprocess.run([exe], capture_output=True)
t1 = time.perf_counter()
if r.returncode == 0:
times.append(t1 - t0)
return float(np.median(times)) if times else 999.0
print("=" * 60)
print(" BENCHMARK RESULTS — AI vs -O1 baseline")
print("=" * 60)
total_pct = []
for src in SOURCE_FILES:
bc = src.replace(".c", ".bc")
subprocess.run(["clang", "-O1", "-emit-llvm", "-c", src, "-o", bc], capture_output=True)
obs = extract_features(bc)
action, _ = model.predict(obs, deterministic=True)
out_bc = bc.replace(".bc", "_ai.bc")
p = passes[int(action)]
if p:
subprocess.run(["opt", f"--passes={p}", bc, "-o", out_bc], capture_output=True)
else:
out_bc = bc
base_exe = src.replace(".c", "_o1_exe")
ai_exe = src.replace(".c", "_ai_exe")
subprocess.run(["clang", "-O1", bc, "-o", base_exe, "-lm"], capture_output=True)
subprocess.run(["clang", "-O1", out_bc, "-o", ai_exe, "-lm"], capture_output=True)
t_base = measure(base_exe)
t_ai = measure(ai_exe)
pct = (t_base - t_ai) / (t_base + 1e-9) * 100
total_pct.append(pct)
name = os.path.basename(src)
print(f" {name:<20} action={action} base={t_base*1000:.1f}ms ai={t_ai*1000:.1f}ms {pct:+.1f}%")
print("=" * 60)
print(f" 평균 speedup: {np.mean(total_pct):+.1f}%")
print("=" * 60)
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