File size: 5,730 Bytes
6d6f4dd | 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 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 | #!/usr/bin/env python3
import torch
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from datetime import datetime
import subprocess
import time
import psutil
import re
from collections import deque
import threading
class GPUBenchmark:
def __init__(self):
self.max_temp = 85
self.temperatures = deque(maxlen=100)
self.tflops_history = deque(maxlen=100)
self.times = deque(maxlen=100)
self.peak_tflops = 0
self.running = True
self.stress_size = 8192
self.fig, (self.ax1, self.ax2) = plt.subplots(2, 1, figsize=(12, 8))
self.fig.suptitle('Benchmark TFLOPS - Radeon Pro VII', fontsize=16)
def get_gpu_temp(self):
try:
result = subprocess.run(['sensors'], capture_output=True, text=True, timeout=1)
for line in result.stdout.split('\n'):
if 'edge:' in line.lower():
match = re.search(r'([+-]?\d+\.?\d*)\s*°C', line)
if match:
return float(match.group(1))
except:
return 0
return 0
def check_system_responsiveness(self):
try:
start = time.time()
_ = psutil.cpu_percent(interval=0.1)
return (time.time() - start) < 0.5
except:
return False
def calculate_tflops(self, matrix_size, elapsed_time):
operations = 2 * (matrix_size ** 3)
return (operations / elapsed_time) / 1e12
def stress_gpu(self):
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
if device.type == 'cpu':
print("ERRO: GPU não detectada!")
self.running = False
return
print(f"GPU detectada: {torch.cuda.get_device_name(0)}")
print("Iniciando benchmark...\n")
while self.running:
temp = self.get_gpu_temp()
if temp >= self.max_temp:
print(f"\n⚠ TEMPERATURA LIMITE: {temp}°C")
self.running = False
break
if not self.check_system_responsiveness():
print("\n⚠ SISTEMA TRAVANDO")
self.running = False
break
try:
torch.cuda.synchronize()
start = time.time()
a = torch.randn(self.stress_size, self.stress_size, device=device)
b = torch.randn(self.stress_size, self.stress_size, device=device)
c = torch.mm(a, b)
torch.cuda.synchronize()
elapsed = time.time() - start
tflops = self.calculate_tflops(self.stress_size, elapsed)
self.temperatures.append(temp)
self.tflops_history.append(tflops)
self.times.append(datetime.now())
if tflops > self.peak_tflops:
self.peak_tflops = tflops
print(f"TFLOPS: {tflops:.2f} | Temp: {temp}°C | Peak: {self.peak_tflops:.2f}", end='\r')
if temp < 75 and tflops < self.peak_tflops * 0.9:
self.stress_size = min(self.stress_size + 256, 16384)
elif temp > 80:
self.stress_size = max(self.stress_size - 256, 4096)
time.sleep(0.1)
except Exception as e:
print(f"\n⚠ ERRO: {e}")
self.running = False
break
def update_plot(self, frame):
if not self.running and len(self.tflops_history) == 0:
return
self.ax1.clear()
self.ax2.clear()
if len(self.tflops_history) > 0:
self.ax1.plot(list(self.tflops_history), 'b-', linewidth=2, label='TFLOPS atual')
self.ax1.axhline(y=self.peak_tflops, color='g', linestyle='--',
label=f'Peak: {self.peak_tflops:.2f} TFLOPS')
self.ax1.set_ylabel('TFLOPS', fontsize=12)
self.ax1.set_title('Desempenho em Tempo Real')
self.ax1.legend()
self.ax1.grid(True, alpha=0.3)
if len(self.temperatures) > 0:
self.ax2.plot(list(self.temperatures), 'r-', linewidth=2, label='Temperatura')
self.ax2.axhline(y=self.max_temp, color='orange', linestyle='--',
label=f'Limite: {self.max_temp}°C')
self.ax2.set_ylabel('Temperatura (°C)', fontsize=12)
self.ax2.set_xlabel('Amostras', fontsize=12)
self.ax2.legend()
self.ax2.grid(True, alpha=0.3)
if not self.running:
self.ax1.text(0.5, 0.5, f'PEAK TFLOPS: {self.peak_tflops:.2f}',
transform=self.ax1.transAxes, fontsize=20,
ha='center', color='green', weight='bold')
def run(self):
stress_thread = threading.Thread(target=self.stress_gpu)
stress_thread.daemon = True
stress_thread.start()
ani = animation.FuncAnimation(self.fig, self.update_plot,
interval=500, cache_frame_data=False)
plt.tight_layout()
plt.show()
stress_thread.join(timeout=2)
print(f"\n\n{'='*50}")
print(f"RESULTADO FINAL")
print(f"{'='*50}")
print(f"🏆 PEAK TFLOPS: {self.peak_tflops:.2f}")
print(f"🌡️ Temp máxima: {max(self.temperatures) if self.temperatures else 0:.1f}°C")
print(f"{'='*50}\n")
if __name__ == "__main__":
benchmark = GPUBenchmark()
benchmark.run()
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