显卡仪表盘.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time\n",
    "from IPython.display import clear_output\n",
    "import subprocess\n",
    "import psutil\n",
    "from tqdm import tqdm\n",
    "\n",
    "interval = 0.5\n",
    "# 获取初始的网络 I/O 统计信息\n",
    "prev_net_io = psutil.net_io_counters()\n",
    "prev_bytes_sent = prev_net_io.bytes_sent\n",
    "prev_bytes_recv = prev_net_io.bytes_recv\n",
    "\n",
    "prev_disk_io = psutil.disk_io_counters()\n",
    "prev_disk_write = prev_disk_io.write_bytes\n",
    "prev_disk_read = prev_disk_io.read_bytes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wed Dec 11 18:18:43 2024       \n",
      "+---------------------------------------------------------------------------------------+\n",
      "| NVIDIA-SMI 530.30.02              Driver Version: 530.30.02    CUDA Version: 12.1     |\n",
      "|-----------------------------------------+----------------------+----------------------+\n",
      "| GPU  Name                  Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
      "| Fan  Temp  Perf            Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
      "|                                         |                      |               MIG M. |\n",
      "|=========================================+======================+======================|\n",
      "|   0  NVIDIA GeForce RTX 2080 Ti      Off| 00000000:04:00.0 Off |                  N/A |\n",
      "|  0%   30C    P8               25W / 300W|   7409MiB / 11264MiB |      0%      Default |\n",
      "|                                         |                      |                  N/A |\n",
      "+-----------------------------------------+----------------------+----------------------+\n",
      "|   1  NVIDIA GeForce RTX 2080 Ti      Off| 00000000:21:00.0 Off |                  N/A |\n",
      "|  0%   49C    P2              260W / 300W|  10025MiB / 11264MiB |     94%      Default |\n",
      "|                                         |                      |                  N/A |\n",
      "+-----------------------------------------+----------------------+----------------------+\n",
      "                                                                                         \n",
      "+---------------------------------------------------------------------------------------+\n",
      "| Processes:                                                                            |\n",
      "|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |\n",
      "|        ID   ID                                                             Usage      |\n",
      "|=======================================================================================|\n",
      "|    0   N/A  N/A    331182      C   python                                     4198MiB |\n",
      "|    0   N/A  N/A    343707      C   python                                     3208MiB |\n",
      "|    1   N/A  N/A    432453      C   python                                     9930MiB |\n",
      "+---------------------------------------------------------------------------------------+\n",
      "\n",
      "CPU 占用率: 10.5%\n",
      "每秒网络发送(MB): 0.03740692138671875\n",
      "每秒网络接收(MB): 0.05481719970703125\n",
      "进程号: 432453, 进程名：python, 内存使用: 52450.59 MB\n",
      "进程号: 470217, 进程名：pt_data_worker, 内存使用: 5790.54 MB\n",
      "进程号: 470173, 进程名：pt_data_worker, 内存使用: 5789.50 MB\n",
      "进程号: 470242, 进程名：pt_data_worker, 内存使用: 5789.38 MB\n",
      "进程号: 470410, 进程名：pt_data_worker, 内存使用: 5787.40 MB\n",
      "进程号: 470198, 进程名：pt_data_worker, 内存使用: 5787.27 MB\n",
      "进程号: 470319, 进程名：pt_data_worker, 内存使用: 5787.10 MB\n",
      "进程号: 470162, 进程名：pt_data_worker, 内存使用: 5786.80 MB\n",
      "内存占用率: 82.0%\n",
      "每秒io写入(MB): 1.1875\n",
      "每秒io读取(MB): 9.734375\n"
     ]
    }
   ],
   "source": [
    "while True:\n",
    "    # 清空输出区域\n",
    "    clear_output(wait=True)\n",
    "    # 使用 nvidia-smi 命令获取显卡状态\n",
    "    result = subprocess.run([\"nvidia-smi\"], stdout=subprocess.PIPE)\n",
    "    # 获取 CPU 占用率\n",
    "    cpu_usage = psutil.cpu_percent(interval=interval)\n",
    "    # 获取内存占用率\n",
    "    memory_info = psutil.virtual_memory()\n",
    "    memory_usage = memory_info.percent\n",
    "\n",
    "    # 获取当前的网络 I/O 统计信息\n",
    "    current_net_io = psutil.net_io_counters()\n",
    "    current_bytes_sent = current_net_io.bytes_sent\n",
    "    current_bytes_recv = current_net_io.bytes_recv\n",
    "\n",
    "    # 获取硬盘 I/O 信息\n",
    "    current_disk_io = psutil.disk_io_counters()\n",
    "    current_disk_write = current_disk_io.write_bytes\n",
    "    current_disk_read = current_disk_io.read_bytes\n",
    "    \n",
    "    # 计算每秒的网络发送和接收字节数\n",
    "    bytes_sent_per_sec = (current_bytes_sent - prev_bytes_sent) / interval\n",
    "    bytes_recv_per_sec = (current_bytes_recv - prev_bytes_recv) / interval\n",
    "    \n",
    "    # 计算每秒的io发送和接收字节数\n",
    "    disk_write = (current_disk_write - prev_disk_write) / interval\n",
    "    disk_read = (current_disk_read - prev_disk_read) / interval\n",
    "    \n",
    "    # 更新上一次统计信息\n",
    "    prev_bytes_sent = current_bytes_sent\n",
    "    prev_bytes_recv = current_bytes_recv\n",
    "    prev_disk_write = current_disk_write\n",
    "    prev_disk_read = current_disk_read\n",
    "\n",
    "    print(result.stdout.decode(\"utf-8\"))\n",
    "    print(f\"CPU 占用率: {cpu_usage}%\")\n",
    "    print(f\"每秒网络发送(MB): {bytes_sent_per_sec / 1024 ** 2}\")\n",
    "    print(f\"每秒网络接收(MB): {bytes_recv_per_sec / 1024 ** 2}\")\n",
    "    # 获取所有进程\n",
    "    all_processes = psutil.process_iter([\"pid\", \"name\", \"memory_info\"])\n",
    "    # 存储符合条件的进程信息\n",
    "    python_processes = []\n",
    "    # 过滤出名称包含 'python' 或 'pt' 的进程\n",
    "    for proc in all_processes:\n",
    "        try:\n",
    "            if (\n",
    "                \"milvus\" in proc.info[\"name\"].lower()\n",
    "                or \"pt_\" in proc.info[\"name\"].lower()\n",
    "                or \"python\" in proc.info[\"name\"].lower()\n",
    "            ):\n",
    "                name = proc.info[\"name\"]\n",
    "                pid = proc.info[\"pid\"]\n",
    "                memory_info = proc.info[\"memory_info\"]\n",
    "                memory_usage_mb = memory_info.rss / 1024 / 1024  # 以MB为单位\n",
    "                python_processes.append((pid, name, memory_usage_mb))\n",
    "        except (psutil.NoSuchProcess, psutil.AccessDenied, psutil.ZombieProcess):\n",
    "            pass\n",
    "    # 按内存使用从高到低排序\n",
    "    python_processes.sort(key=lambda x: x[2], reverse=True)\n",
    "\n",
    "    # 打印排序后的进程信息\n",
    "    for pid, name, memory_usage_mb in python_processes[:8]:\n",
    "        print(f\"进程号: {pid}, 进程名：{name}, 内存使用: {memory_usage_mb:.2f} MB\")\n",
    "    # 每隔一秒输出一次\n",
    "    print(f\"内存占用率: {memory_usage}%\")\n",
    "    print(f\"每秒io写入(MB): {disk_write / 1024 ** 2}\")\n",
    "    print(f\"每秒io读取(MB): {disk_read / 1024 ** 2}\")\n",
    "    time.sleep(interval)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "base",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}