GPU vs CPU Benchmark

import numpy as np
import matplotlib.pyplot as plt

np.random.seed(321)
BG_COLOR = '#0a0a0f'

# Processing time (seconds)
cpu = np.random.gamma(8, 1.5, 800)
gpu = np.random.gamma(2, 0.4, 800)

fig, ax = plt.subplots(figsize=(12, 7), facecolor=BG_COLOR)
ax.set_facecolor(BG_COLOR)

bins = np.linspace(0, 25, 35)
bin_width = bins[1] - bins[0]
centers = (bins[:-1] + bins[1:]) / 2

# CPU (top) - warm colors
h1, _ = np.histogram(cpu, bins=bins, density=True)
ax.bar(centers, h1, width=bin_width*0.85, color='#F54927', alpha=0.75,
       edgecolor='#F54927', linewidth=1, label=f'CPU (μ={np.mean(cpu):.1f}s)')

# GPU (bottom) - cool colors
h2, _ = np.histogram(gpu, bins=bins, density=True)
ax.bar(centers, -h2, width=bin_width*0.85, color='#6CF527', alpha=0.75,
       edgecolor='#6CF527', linewidth=1, label=f'GPU (μ={np.mean(gpu):.1f}s)')

ax.axhline(0, color='#555555', linewidth=2)

# Speedup calculation
speedup = np.mean(cpu) / np.mean(gpu)

# Big speedup annotation
ax.text(20, max(h1)*0.6, f'{speedup:.1f}x', fontsize=48, color='#6CF527',
        fontweight='bold', ha='center', alpha=0.8)
ax.text(20, max(h1)*0.35, 'FASTER', fontsize=14, color='#6CF527',
        fontweight='bold', ha='center', alpha=0.8)

# Arrow showing improvement
ax.annotate('', xy=(np.mean(gpu), -max(h2)*0.7), xytext=(np.mean(cpu), max(h1)*0.7),
            arrowprops=dict(arrowstyle='->', color='#F5D327', lw=3,
                          connectionstyle='arc3,rad=-0.2'))

# Stats
stats = f"CPU: μ={np.mean(cpu):.1f}s, σ={np.std(cpu):.1f}s | GPU: μ={np.mean(gpu):.2f}s, σ={np.std(gpu):.2f}s"
ax.text(0.5, 0.98, stats, transform=ax.transAxes, ha='center', va='top',
        fontsize=10, color='#888888', fontfamily='monospace',
        bbox=dict(boxstyle='round,pad=0.4', facecolor=BG_COLOR, edgecolor='#333333'))

ax.set_xlabel('Processing Time (seconds)', fontsize=12, color='white', fontweight='500')
ax.set_title('Deep Learning Training: CPU vs GPU', fontsize=16, color='white', fontweight='bold', pad=25)

ax.tick_params(colors='#888888', labelsize=10)
ax.set_yticks([])
for spine in ['top', 'right']:
    ax.spines[spine].set_visible(False)
for spine in ['bottom', 'left']:
    ax.spines[spine].set_color('#333333')
ax.legend(loc='upper right', facecolor=BG_COLOR, edgecolor='#333333', labelcolor='white', fontsize=10)

plt.tight_layout()
plt.show()