plot_gpu.py

import re
import matplotlib.pyplot as plt
import sys
import numpy as np
import datetime

plt.rcParams['axes.unicode_minus'] = False  # Show minus sign correctly

# 支持命令行参数 interval
interval = 5  # 默认5秒
if len(sys.argv) > 1:
    try:
        interval = int(sys.argv[1])
    except Exception:
        pass

# Log file path
log_file = "log"

gpu_utils = []
powers = []
timestamps = []

with open(log_file, "r") as f:
    for line in f:
        # Extract timestamp
        time_match = re.match(r"(\d{2}-\d{2}-\d{4} \d{2}:\d{2}:\d{2})", line)
        if not time_match:
            continue
        timestamps.append(time_match.group(1))
        # Extract GPU utilization
        gr3d_match = re.search(r"GR3D_FREQ (\d+)%", line)
        if gr3d_match:
            gpu_utils.append(int(gr3d_match.group(1)))
        else:
            gpu_utils.append(None)
        # Extract GPU power (VDD_GPU_SOC)
        power_match = re.search(r"VDD_GPU_SOC (\d+)mW", line)
        if power_match:
            powers.append(int(power_match.group(1)))
        else:
            powers.append(None)

# 横坐标为实际时间（秒，起点为0）
def parse_time(s):
    return datetime.datetime.strptime(s, "%m-%d-%Y %H:%M:%S")
if timestamps:
    t0 = parse_time(timestamps[0])
    x = [(parse_time(ts) - t0).total_seconds() for ts in timestamps]
else:
    x = list(range(1, len(gpu_utils) + 1))

# Plot
fig, ax1 = plt.subplots(figsize=(12, 6))
ax1.set_xlabel('Time (s)')
ax1.set_ylabel('GPU Utilization (%)', color='tab:blue')
ax1.plot(x, gpu_utils, color='tab:blue', label='GPU Utilization')
ax1.tick_params(axis='y', labelcolor='tab:blue')

ax2 = ax1.twinx()
ax2.set_ylabel('GPU Power (mW)', color='tab:red')
ax2.plot(x, powers, color='tab:red', label='GPU Power')
ax2.tick_params(axis='y', labelcolor='tab:red')

plt.title('GPU Utilization and Power Over Time (actual time)')
plt.tight_layout()
plt.savefig('gpu_util_power.png')

# 统计功耗信息并保存到图片
import numpy as np
valid_powers = [p for p in powers if p is not None]

# 开关：是否统计无波动区间（True=统计，False=不统计）
INCLUDE_STABLE = True  # 你可以根据需要改为 False

# 跳过前面功率无波动的区间
def find_first_fluctuate_idx(power_list):
    if not power_list:
        return 0
    base = power_list[0]
    for i, p in enumerate(power_list):
        if p != base:
            return i
    return len(power_list)  # 全部无波动

start_idx = find_first_fluctuate_idx(valid_powers)
fluctuate_powers = valid_powers[start_idx:]

if fluctuate_powers:
    avg_power = np.mean(fluctuate_powers)
    min_power = np.min(fluctuate_powers)
    max_power = np.max(fluctuate_powers)
    # 计算真实采样间隔
    if len(x) > start_idx + 1:
        real_interval = (x[start_idx+1] - x[start_idx])
    else:
        real_interval = interval
    total_energy_j = np.sum(fluctuate_powers) * real_interval / 1000  # mW*秒/1000 = J
    stat_text = (
        f"Power statistics (interval~{real_interval:.2f}s, skip {start_idx} stable points):\n"
        f"  Average Power: {avg_power:.2f} mW\n"
        f"  Min Power: {min_power} mW\n"
        f"  Max Power: {max_power} mW\n"
        f"  Total Energy: {total_energy_j:.2f} J\n"
        f"Note: X axis is actual time (seconds)."
    )
    print(stat_text)
elif INCLUDE_STABLE and valid_powers:
    # 全部无波动也统计
    avg_power = np.mean(valid_powers)
    min_power = np.min(valid_powers)
    max_power = np.max(valid_powers)
    if len(x) > 1:
        real_interval = (x[1] - x[0])
    else:
        real_interval = interval
    total_energy_j = np.sum(valid_powers) * real_interval / 1000
    stat_text = (
        f"Power statistics (interval~{real_interval:.2f}s, all points stable):\n"
        f"  Average Power: {avg_power:.2f} mW\n"
        f"  Min Power: {min_power} mW\n"
        f"  Max Power: {max_power} mW\n"
        f"  Total Energy: {total_energy_j:.2f} J\n"
        f"Note: X axis is actual time (seconds)."
    )
    print(stat_text)
else:
    stat_text = "No valid power data found after skipping stable period.\nNote: X axis is actual time (seconds)."
    print(stat_text)

# 在图上添加统计信息文本
fig2, ax = plt.subplots(figsize=(7, 3))
ax.axis('off')
ax.text(0.01, 0.99, stat_text, fontsize=13, va='top', ha='left', family='monospace')
plt.tight_layout()
plt.savefig('gpu_power_stats.png')