{"id":36079,"date":"2026-09-15T13:55:41","date_gmt":"2026-09-15T05:55:41","guid":{"rendered":"https:\/\/www.varidata.com\/uncategorized-zh-cn\/fixing-gpu-model-failures-after-server-environment-changes\/"},"modified":"2026-09-15T14:07:31","modified_gmt":"2026-09-15T06:07:31","slug":"fixing-gpu-model-failures-after-server-environment-changes","status":"publish","type":"post","link":"https:\/\/www.varidata.com\/zh-cn\/knowledge\/fixing-gpu-model-failures-after-server-environment-changes\/","title":{"rendered":"\u4fee\u590d GPU \u6a21\u578b\u5728\u66f4\u6362\u670d\u52a1\u5668\u73af\u5883\u540e\u65e0\u6cd5\u8fd0\u884c\u7684\u95ee\u9898"},"content":{"rendered":"<p>\n\u4f60\u91cd\u6784\u4e86\u4e00\u90e8\u5206\u57fa\u7840\u8bbe\u65bd\uff0c\u628a\u5de5\u4f5c\u8d1f\u8f7d\u8fc1\u5230\u4e86\u65e5\u672c\u673a\u623f\u7684\u4e00\u53f0\u65b0\u7684 <a target=\"_blank\" href=\"https:\/\/www.varidata.com\/zh-cn\/knowledge\/gpu-acceleration-for-ai-using-us-high-configuration-servers\/\">GPU<\/a> \u670d\u52a1\u5668\u6216\u8005\u4e00\u53f0\u65b0\u7684 <a target=\"_blank\" href=\"https:\/\/www.varidata.com\/zh-cn\/server\/tokyo\/cn2\/\">\u65e5\u672c\u670d\u52a1\u5668<\/a> \u4e0a\uff0c\u6309\u4e0b\u8fd0\u884c\u2026\u2026\u7136\u540e\u6a21\u578b\u76f4\u63a5\u6302\u6389\u3002\u4ee3\u7801\u6ca1\u6539\uff0c\u4ed3\u5e93\u8fd8\u662f\u540c\u4e00\u4e2a\uff0c\u4f46\u5230\u5904\u90fd\u662f CUDA \u62a5\u9519\u548c\u7f3a\u5931\u5e93\u3002\u5982\u679c\u8fd9\u542c\u8d77\u6765\u50cf\u5178\u578b\u7684 GPU \u670d\u52a1\u5668\u73af\u5883\u8fc1\u79fb\u95ee\u9898\uff0c\u90a3\u8fd9\u7bc7\u6307\u5357\u5c31\u662f\u4e3a\u4f60\u51c6\u5907\u7684\u3002\n<\/p>\n<h2><strong>1. \u5f53\u4f60\u201c\u53ea\u662f\u6362\u4e86\u4e00\u53f0\u670d\u52a1\u5668\u201d\u65f6\uff0c\u54ea\u4e9b\u4e1c\u897f\u771f\u7684\u53d8\u4e86<\/strong><\/h2>\n<p>\n\u4ece\u5f00\u53d1\u8005\u89c6\u89d2\u6765\u770b\uff0c\u4f60\u53ef\u80fd\u53ea\u662f\u6362\u4e86\u4e00\u4e2a IP\uff0c\u6539\u4e86\u4e00\u4e2a SSH \u76ee\u6807\u3002\u4ece\u6574\u4e2a\u6280\u672f\u6808\u7684\u89c6\u89d2\u6765\u770b\uff0c\u4f60\u53ef\u80fd\u5df2\u7ecf\u66f4\u6362\u4e86\uff1aGPU \u67b6\u6784\u3001NVIDIA \u9a71\u52a8\u7248\u672c\u3001CUDA \u5de5\u5177\u5305\u3001Linux \u53d1\u884c\u7248\u3001\u5185\u6838\u3001Python \u6784\u5efa\u7248\u672c\uff0c\u751a\u81f3\u662f\u7ec6\u5fae\u7684 glibc \u5dee\u5f02\u3002\u4efb\u4f55\u4e00\u4e2a\u73af\u8282\u7684\u53d8\u5316\uff0c\u90fd\u8db3\u4ee5\u8ba9\u539f\u672c\u7a33\u5b9a\u7684\u6df1\u5ea6\u5b66\u4e60\u73af\u5883\u77ac\u95f4\u5d29\u76d8\u3002\n<\/p>\n<ul>\n<li><strong>\u65b0\u7684 GPU \u4ee3\u6570<\/strong>\uff1a\u4f60\u7684\u65e7\u673a\u5668\u53ef\u80fd\u662f V100\uff0c\u800c\u65b0\u7684\u65e5\u672c GPU \u670d\u52a1\u5668\u79df\u7528\u65b9\u6848\u7ed9\u4f60\u7684\u662f A100 \u6216 RTX 4090\u3002<\/li>\n<li><strong>\u65b0\u7684\u7cfb\u7edf\u955c\u50cf<\/strong>\uff1a\u65e7\u73af\u5883\u662f Ubuntu 18.04\uff0c\u65b0\u73af\u5883\u662f 22.04\uff0c\u9ed8\u8ba4\u5e93\u548c\u7cfb\u7edf\u884c\u4e3a\u90fd\u6709\u6240\u53d8\u5316\u3002<\/li>\n<li><strong>\u4e0d\u540c\u7684\u90e8\u7f72\u6808<\/strong>\uff1a\u4e4b\u524d\u662f\u88f8\u673a\u90e8\u7f72\uff0c\u73b0\u5728\u5168\u90e8\u5207\u5230 Docker \u6216\u7531 Kubernetes \u7ba1\u7406\u3002<\/li>\n<li><strong>\u7f51\u7edc\u62d3\u6251\u53d8\u5316<\/strong>\uff1a\u8fc1\u79fb\u5230\u65e5\u672c\u533a\u57df\u540e\uff0c\u6a21\u578b\u548c\u6570\u636e\u96c6\u7684\u4e0b\u8f7d\u6e90\u53ef\u80fd\u53d1\u751f\u6539\u53d8\uff0c\u8d85\u65f6\u548c DNS \u884c\u4e3a\u4e5f\u90fd\u4f1a\u8ddf\u7740\u53d8\u3002<\/li>\n<\/ul>\n<p>\n\u4e0e\u5176\u53cd\u590d\u201c\u91cd\u88c5\u8bd5\u8fd0\u6c14\u201d\uff0c\u4e0d\u5982\u628a\u8fd9\u4e2a\u95ee\u9898\u5f53\u6210\u6b63\u89c4\u7684\u8c03\u8bd5\u6d41\u7a0b\uff1a\u4ece\u786c\u4ef6\u5230 Python \u4ee3\u7801\u9010\u5c42\u9a8c\u8bc1\uff0c\u9010\u5c42\u9501\u5b9a\u5230\u5e95\u54ea\u91cc\u53d1\u751f\u4e86\u53d8\u5316\u3002\n<\/p>\n<h2><strong>2. \u642d\u5efa\u5fc3\u667a\u6a21\u578b\uff1a\u628a GPU \u6280\u672f\u6808\u6309\u5c42\u62c6\u5f00\u770b<\/strong><\/h2>\n<p>\n\u5728\u6392\u67e5\u8fc1\u79fb\u4e4b\u540e\u7684\u8be1\u5f02\u8fd0\u884c\u65f6\u9519\u8bef\u65f6\uff0c\u8981\u5b66\u4f1a\u5206\u5c42\u601d\u8003\u3002\u5982\u679c\u5e95\u5c42\u67d0\u4e00\u5c42\u51fa\u95ee\u9898\u4e86\uff0c\u4e0a\u5c42\u518d\u5e72\u51c0\u7684\u4ee3\u7801\u4e5f\u4f1a\u8868\u73b0\u5f97\u4e00\u56e2\u7cdf\u3002\n<\/p>\n<ol>\n<li><strong>\u786c\u4ef6\u5c42<\/strong>\uff1a\u7269\u7406 GPU\u3001PCIe \u62d3\u6251\u3001\u7535\u6e90\u3001\u6563\u70ed\u3002<\/li>\n<li><strong>\u5bbf\u4e3b\u673a OS + \u9a71\u52a8\u5c42<\/strong>\uff1a\u5185\u6838\u3001NVIDIA \u9a71\u52a8\u3001\u5bbf\u4e3b\u673a\u4e0a\u7684 CUDA runtime\u3002<\/li>\n<li><strong>\u5bb9\u5668 \/ \u865a\u62df\u5316\u5c42<\/strong>\uff1aDocker\u3001nvidia-container-toolkit\u3001\u865a\u62df\u5316\u914d\u7f6e\u3002<\/li>\n<li><strong>\u8bed\u8a00\u8fd0\u884c\u65f6\u5c42<\/strong>\uff1aPython \u7248\u672c\u3001Conda \/ virtualenv\u3002<\/li>\n<li><strong>\u6846\u67b6\u5c42<\/strong>\uff1aPyTorch\u3001TensorFlow\u3001JAX\u3001MXNet \u4ee5\u53ca\u5404\u81ea\u7f16\u8bd1\u7ed1\u5b9a\u7684 CUDA\u3002<\/li>\n<li><strong>\u5e94\u7528\u5c42<\/strong>\uff1a\u4f60\u7684\u8bad\u7ec3 \/ \u63a8\u7406\u4ee3\u7801\u3001\u914d\u7f6e\u3001\u73af\u5883\u53d8\u91cf\u3002<\/li>\n<\/ol>\n<p>\n\u8c03\u8bd5\u7b56\u7565\u5f88\u7b80\u5355\uff1a\u4ece\u6700\u5e95\u5c42\u5f00\u59cb\u5f80\u4e0a\u6392\u67e5\uff0c\u6c38\u8fdc\u4e0d\u8981\u56e0\u4e3a\u201c\u4e4b\u524d\u5728\u65e7\u670d\u52a1\u5668\u4e0a\u6ca1\u95ee\u9898\u201d\u5c31\u6b66\u65ad\u5730\u8ba4\u4e3a\u67d0\u4e00\u5c42\u4e00\u5b9a\u662f\u6b63\u5e38\u7684\u3002\n<\/p>\n<h2><strong>3. \u5148\u786e\u8ba4\uff1a\u65b0\u673a\u5668\u4e0a\u7684 GPU \u771f\u7684\u6d3b\u7740\u5417<\/strong><\/h2>\n<p>\n\u5728\u548c CUDA \u5435\u67b6\u4e4b\u524d\uff0c\u5148\u786e\u4fdd\u786c\u4ef6\u662f\u53ef\u89c1\u800c\u4e14\u5065\u5eb7\u7684\u3002SSH \u767b\u5f55\u5230\u65e5\u672c\u8282\u70b9\uff0c\u5148\u8dd1\u4e00\u4e9b\u770b\u8d77\u6765\u5f88\u65e0\u804a\u7684\u547d\u4ee4\u3002\n<\/p>\n<ul>\n<li><code>nvidia-smi<\/code>\uff1a\u4f60\u80fd\u770b\u5230\u6240\u6709\u663e\u5361\u5417\uff1f\u578b\u53f7\u6b63\u786e\u5417\uff1f\u7a7a\u95f2\u72b6\u6001\u4e0b\u6e29\u5ea6\u548c\u529f\u8017\u662f\u5426\u5408\u7406\uff1f<\/li>\n<li><code>lspci | grep -i nvidia<\/code>\uff1a\u786e\u8ba4 PCIe \u8bbe\u5907\u662f\u5426\u5b58\u5728\uff0c\u5728\u9a71\u52a8\u6709\u95ee\u9898\u3001<code>nvidia-smi<\/code> \u8dd1\u4e0d\u8d77\u6765\u65f6\u5c24\u5176\u6709\u7528\u3002<\/li>\n<li><code>dmesg | grep -i nvidia<\/code>\uff1a\u67e5\u770b\u9a71\u52a8\u52a0\u8f7d\u95ee\u9898\u3001ECC \u9519\u8bef\u6216\u91cd\u542f\u540e\u7684 PCIe \u95ee\u9898\u3002<\/li>\n<\/ul>\n<p>\n\u6b64\u9636\u6bb5\u7684\u4e00\u4e9b\u7ea2\u8272\u4fe1\u53f7\uff1a\n<\/p>\n<ul>\n<li><code>nvidia-smi<\/code> \u4e2d\u5b8c\u5168\u770b\u4e0d\u5230 GPU\u3002<\/li>\n<li>\u51fa\u73b0 \u201cno devices were found\u201d \u4e4b\u7c7b\u7684\u9519\u8bef\u3002<\/li>\n<li>GPU \u6570\u91cf\u660e\u663e\u5c11\u4e8e\u4f60\u5728\u670d\u52a1\u5668\u79df\u7528\u6216\u670d\u52a1\u5668\u6258\u7ba1\u65b9\u6848\u4e2d\u5b9e\u9645\u8d2d\u4e70\u7684\u6570\u91cf\u3002<\/li>\n<\/ul>\n<p>\n\u5982\u679c\u786c\u4ef6\u5c42\u5df2\u7ecf\u4e0d\u5bf9\u52b2\uff0c\u5728\u52a8\u8f6f\u4ef6\u6808\u4e4b\u524d\uff0c\u5148\u8054\u7cfb\u4f60\u7684\u65e5\u672c GPU \u670d\u52a1\u5668\u79df\u7528\u670d\u52a1\u5546\u6216\u673a\u623f\u3002\u574f\u6389\u7684 PCIe \u901a\u9053\u3001\u635f\u574f\u7684\u663e\u5361\u3001\u63a5\u7ebf\u9519\u8bef\u7684\u8f6c\u63a5\u677f\uff0c\u8fd9\u4e9b\u90fd\u4e0d\u662f\u901a\u8fc7 pip \u80fd\u89e3\u51b3\u7684\u95ee\u9898\u3002\n<\/p>\n<h2><strong>4. \u9a71\u52a8\u548c CUDA \u7684\u73b0\u5b9e\u68c0\u67e5<\/strong><\/h2>\n<p>\n\u5927\u90e8\u5206\u8fc1\u79fb\u540e\u7684\u6a21\u578b\u6545\u969c\uff0c\u672c\u8d28\u4e0a\u90fd\u662f\u67d0\u79cd\u5f62\u5f0f\u7684\u9a71\u52a8\u4e0e CUDA \u4e0d\u5339\u914d\u3002\u9a71\u52a8\u88c5\u5728\u5bbf\u4e3b\u673a\u4e0a\uff0c\u800c Python \u6216\u5bb9\u5668\u4e2d\u7684\u6846\u67b6\u662f\u9488\u5bf9\u7279\u5b9a CUDA runtime \u7f16\u8bd1\u7684\u3002\n<\/p>\n<p>\n\u5148\u505a\u4e00\u4e2a\u5feb\u901f\u57fa\u7ebf\u68c0\u67e5\uff1a\n<\/p>\n<ul>\n<li><code>nvidia-smi<\/code> \u4f1a\u663e\u793a\u9a71\u52a8\u7248\u672c\u4ee5\u53ca\u66b4\u9732\u51fa\u6765\u7684 CUDA runtime \u7248\u672c\u3002<\/li>\n<li><code>nvcc --version<\/code>\uff08\u5982\u679c\u5b89\u88c5\u4e86\uff09\u4f1a\u663e\u793a CUDA toolkit \u7248\u672c\uff0c\u8fd9\u4e2a\u53ef\u80fd\u548c runtime \u4e0d\u540c\u3002<\/li>\n<li>\u5728 Python \u91cc\u8fd0\u884c\uff1a\n<ul>\n<li><code>import torch; print(torch.version.cuda)<\/code><\/li>\n<li><code>import tensorflow as tf; print(tf.__version__)<\/code><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>\n\u4f60\u9700\u8981\u4e00\u4e2a\u88ab\u5b98\u65b9\u652f\u6301\u7684\u201c\u7248\u672c\u4e09\u89d2\u201d\uff1a\n<\/p>\n<ol>\n<li>NVIDIA \u9a71\u52a8\u7248\u672c\u3002<\/li>\n<li><code>nvidia-smi<\/code> \u62a5\u544a\u7684 CUDA runtime \u7248\u672c\u3002<\/li>\n<li>\u6846\u67b6\u6784\u5efa\uff08PyTorch \/ TF\uff09\u53ca\u5176\u7f16\u8bd1\u65f6\u6240\u7ed1\u5b9a\u7684 CUDA \u7248\u672c\u3002<\/li>\n<\/ol>\n<p>\n\u5982\u679c\u4f60\u5728\u65b0\u670d\u52a1\u5668\u4e0a\u201c\u91cd\u65b0\u88c5\u4e86\u4e00\u904d\u73af\u5883\u987a\u624b\u5168\u90fd\u5347\u5230\u6700\u65b0\u7248\u201d\uff0c\u90a3\u8fd9\u4e2a\u4e09\u89d2\u5f88\u53ef\u80fd\u5df2\u7ecf\u548c\u65e7\u73af\u5883\u5b8c\u5168\u5bf9\u4e0d\u4e0a\u53f7\u4e86\u3002\u4e3a CUDA 11.3 \u6784\u5efa\u7684\u6a21\u578b\u8f6e\u5b50\uff0c\u5728\u4e00\u4e2a\u53ea\u66b4\u9732 CUDA 12.2 \u7684\u5bbf\u4e3b\u4e0a\uff08\u53c8\u6ca1\u6709\u5408\u9002\u7684\u517c\u5bb9\u5c42\uff09\u5927\u6982\u7387\u662f\u8dd1\u4e0d\u8d77\u6765\u7684\u3002\n<\/p>\n<h2><strong>5. \u628a\u65e7\u73af\u5883\u6293\u7d27\uff1a\u8fc1\u79fb\u524d\u5148\u505a\u5feb\u7167<\/strong><\/h2>\n<p>\n\u5982\u679c\u4f60\u7684\u8fc1\u79fb\u8fd8\u6ca1\u5f00\u59cb\uff0c\u6700\u4e13\u4e1a\u7684\u505a\u6cd5\u5c31\u662f\u5148\u51bb\u7ed3\u5f53\u524d\u73af\u5883\u3002\u5982\u679c\u5df2\u7ecf\u8fc1\u79fb\u5b8c\u6bd5\uff0c\u90a3\u5c31\u5c3d\u53ef\u80fd\u901a\u8fc7\u65e5\u5fd7\u548c\u914d\u7f6e\u628a\u65e7\u73af\u5883\u8fd8\u539f\u51fa\u6765\u3002\n<\/p>\n<ul>\n<li>\u5bfc\u51fa Conda \u73af\u5883\uff1a\n<ul>\n<li><code>conda env export &gt; env-old.yaml<\/code><\/li>\n<\/ul>\n<\/li>\n<li>\u8bb0\u5f55 pip \u4f9d\u8d56\uff1a\n<ul>\n<li><code>pip freeze &gt; requirements-old.txt<\/code><\/li>\n<\/ul>\n<\/li>\n<li>\u8bb0\u4e0b OS \u548c\u5185\u6838\uff1a\n<ul>\n<li><code>lsb_release -a<\/code>\uff0c<code>uname -r<\/code><\/li>\n<\/ul>\n<\/li>\n<li>\u8bb0\u5f55 GPU \u548c\u9a71\u52a8\u4fe1\u606f\uff1a\n<ul>\n<li>\u4fdd\u5b58\u65e7\u73af\u5883\u4e0b <code>nvidia-smi<\/code> \u7684\u5b8c\u6574\u8f93\u51fa\u3002<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>\n\u5728\u65e5\u672c\u7684\u65b0\u670d\u52a1\u5668\u4e0a\uff0c\u5c3d\u91cf\u5fe0\u5b9e\u5730\u91cd\u653e\u8fd9\u4e9b\u4fe1\u606f\uff0c\u800c\u4e0d\u662f\u201c\u987a\u624b\u5347\u7ea7\u4e00\u6ce2\u201d\u3002\u4f60\u79bb\u539f\u73af\u5883\u8d8a\u8fd1\uff0c\u8fc1\u79fb\u4e2d\u8e29\u5230\u7684\u8fb9\u89d2\u5751\u5c31\u8d8a\u5c11\u3002\n<\/p>\n<h2><strong>6. Python \u7248\u672c\u4e0e\u865a\u62df\u73af\u5883\u7684\u5730\u96f7<\/strong><\/h2>\n<p>\n\u6700\u5bb9\u6613\u88ab\u5ffd\u89c6\u7684\u4e00\u79cd\u5931\u8d25\u6a21\u5f0f\u662f\uff1a\u4ee3\u7801\u5728\u4f60\u672c\u5730\u548c\u8001\u670d\u52a1\u5668\u4e0a\u7684 Python 3.8 \u8dd1\u5f97\u597d\u597d\u7684\uff0c\u65b0 GPU \u670d\u52a1\u5668\u9ed8\u8ba4\u5207\u5230\u4e86 3.11\uff0c\u4e8e\u662f\u5404\u79cd\u4f9d\u8d56\u9519\u8bef\u548c\u7f16\u8bd1\u95ee\u9898\u7eb7\u7eb7\u5192\u51fa\u6765\u3002\n<\/p>\n<ol>\n<li>\u786e\u8ba4\u89e3\u91ca\u5668\uff1a\n<ul>\n<li>\u6267\u884c <code>python --version<\/code> \u6216 <code>python3 --version<\/code>\u3002<\/li>\n<li>\u786e\u8ba4\u771f\u6b63\u6392\u5728 <code>$PATH<\/code> \u524d\u9762\u7684\u5230\u5e95\u662f\u54ea\u4e2a Python \u53ef\u6267\u884c\u6587\u4ef6\u3002<\/li>\n<\/ul>\n<\/li>\n<li>\u68c0\u67e5\u865a\u62df\u73af\u5883\uff1a\n<ul>\n<li>Conda \u73af\u5883\uff1a<code>conda env list<\/code>\uff0c\u7136\u540e <code>conda activate your-env<\/code>\u3002<\/li>\n<li>virtualenv\uff1a\u4f7f\u7528\u5bf9\u5e94\u7684 <code>bin\/activate<\/code> \u811a\u672c\u8fdb\u884c\u6fc0\u6d3b\u3002<\/li>\n<\/ul>\n<\/li>\n<li>\u4e0d\u8981\u4f9d\u8d56\u7cfb\u7edf Python\uff1a\n<ul>\n<li>\u4e3a\u6bcf\u4e2a\u9879\u76ee\u663e\u5f0f\u6307\u5b9a Python \u7248\u672c\u3002\u5982\u679c\u4f60\u7684\u6784\u5efa\u662f 3.9\uff0c\u5c31\u88c5 3.9\uff0c\u800c\u4e0d\u662f\u968f\u7f18\u3002<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<p>\n\u5982\u679c\u4f60\u4f7f\u7528\u7684\u662f\u65e5\u672c\u673a\u623f\u7684\u9884\u88c5\u955c\u50cf\u6216\u67d0\u79cd\u5e73\u53f0\u670d\u52a1\uff0c\u5b83\u4eec\u901a\u5e38\u4f1a\u9884\u88c5\u591a\u4e2a Python \u7248\u672c\u3002\u628a GPU \u7248 PyTorch \u88c5\u8fdb\u4e86\u9519\u8bef\u7684\u89e3\u91ca\u5668\uff0c\u662f\u4e00\u79cd\u975e\u5e38\u5e38\u89c1\u7684\u8fc1\u79fb\u5751\uff1a\u770b\u8d77\u6765\u50cf\u662f\u201cGPU \u4e0d\u89c1\u4e86\u201d\uff0c\u672c\u8d28\u5374\u662f\u4f60\u7528\u7684\u662f CPU-only \u7684\u8f6e\u5b50\u3002\n<\/p>\n<h2><strong>7. \u6846\u67b6\u5c42\u8c03\u8bd5\uff1aPyTorch\u3001TensorFlow\u3001JAX<\/strong><\/h2>\n<p>\n\u5f53\u9a71\u52a8\u548c\u89e3\u91ca\u5668\u786e\u8ba4\u65e0\u8bef\u4e4b\u540e\uff0c\u63a5\u4e0b\u6765\u5c31\u8981\u52a0\u8f7d\u6846\u67b6\uff0c\u95ee\u95ee\u5b83\u5bf9\u5f53\u524d GPU \u72b6\u6001\u7684\u770b\u6cd5\u3002\u4e00\u5b9a\u8981\u5728\u5e94\u7528\u5b9e\u9645\u4f7f\u7528\u7684\u73af\u5883\u91cc\u6267\u884c\uff08\u540c\u4e00\u4e2a <code>venv<\/code> \u6216 Conda \u73af\u5883\u3001\u540c\u4e00\u4e2a\u5bb9\u5668\uff09\u3002\n<\/p>\n<ul>\n<li>PyTorch\uff1a\n<ul>\n<li><code>torch.cuda.is_available()<\/code> \u5e94\u8be5\u8fd4\u56de <code>True<\/code>\u3002<\/li>\n<li><code>torch.cuda.get_device_name(0)<\/code> \u5e94\u8be5\u663e\u793a\u4f60\u5728\u65e5\u672c\u8282\u70b9\u4e0a\u7684\u771f\u5b9e GPU \u578b\u53f7\u3002<\/li>\n<\/ul>\n<\/li>\n<li>TensorFlow\uff1a\n<ul>\n<li><code>tf.config.list_physical_devices('GPU')<\/code> \u5e94\u8be5\u5217\u51fa\u6240\u6709\u53ef\u89c1\u7684 GPU\u3002<\/li>\n<\/ul>\n<\/li>\n<li>JAX\uff1a\n<ul>\n<li><code>jax.devices()<\/code> \u5e94\u8be5\u80fd\u770b\u5230 GPU\uff08\u6216\u76f8\u5173 TPU\uff09\u3002<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>\n\u8fc1\u79fb\u540e\u5728\u6846\u67b6\u5c42\u5e38\u89c1\u7684\u95ee\u9898\u5305\u62ec\uff1a\n<\/p>\n<ul>\n<li>\u4e0d\u5c0f\u5fc3\u5b89\u88c5\u4e86 CPU-only \u7248\u672c\u8986\u76d6\u4e86 GPU \u7248\u672c\u3002<\/li>\n<li>\u7cfb\u7edf\u4e2d\u5b58\u5728\u591a\u4e2a CUDA \u7248\u672c\uff0c\u94fe\u63a5\u5668\u9009\u62e9\u4e86\u9519\u8bef\u7684\u90a3\u4e2a\u3002<\/li>\n<li>\u65e7\u7684\u5df2\u7f16\u8bd1\u6269\u5c55\u548c\u5f53\u524d ABI \u4e0d\u518d\u5339\u914d\u3002<\/li>\n<\/ul>\n<p>\n\u5982\u679c\u5bfc\u5165\u6846\u67b6\u65f6\u51fa\u73b0\u5305\u542b CUDA\u3001cuDNN \u6216 <code>libcudart<\/code> \u7684\u9519\u8bef\u4fe1\u606f\uff0c\u5148\u786e\u8ba4\u4f60\u5b89\u88c5\u7684\u7248\u672c\u662f\u5426\u660e\u786e\u88ab GPU \u548c\u9a71\u52a8\u6587\u6863\u652f\u6301\uff0c\u5e76\u4e14\u548c\u670d\u52a1\u5668\u79df\u7528\u6216\u670d\u52a1\u5668\u6258\u7ba1\u63d0\u4f9b\u5546\u5f53\u524d\u5728\u8dd1\u7684\u7248\u672c\u662f\u517c\u5bb9\u7684\u3002\n<\/p>\n<h2><strong>8. \u5bb9\u5668\u3001\u7f16\u6392\u7cfb\u7edf\u4e0e\u201c\u770b\u4e0d\u89c1\u7684\u5bbf\u4e3b\u673a\u201d<\/strong><\/h2>\n<p>\n\u5728\u5f88\u591a\u65e5\u672c\u5730\u533a\u7684 GPU \u670d\u52a1\u5668\u79df\u7528\u5e73\u53f0\u4e0a\uff0c\u5bb9\u5668\u5df2\u7ecf\u662f\u9ed8\u8ba4\u90e8\u7f72\u65b9\u5f0f\u3002\u8fd9\u4f1a\u5f15\u5165\u989d\u5916\u4e00\u5c42\uff1a\u5bbf\u4e3b\u673a\u914d\u7f6e\u5b8c\u7f8e\uff0c\u4f46\u5bb9\u5668\u5185\u90e8\u5b8c\u5168\u770b\u4e0d\u5230 GPU\u3002\n<\/p>\n<ol>\n<li>\u68c0\u67e5 Docker runtime\uff1a\n<ul>\n<li>\u4f7f\u7528 <code>--gpus all<\/code> \u6216\u5728\u9ed8\u8ba4 runtime \u4e2d\u914d\u7f6e <code>nvidia<\/code>\u3002<\/li>\n<li>\u8fd0\u884c <code>docker run --gpus all nvidia\/cuda:12.2.0-base-ubuntu22.04 nvidia-smi<\/code> \u9a8c\u8bc1 GPU \u900f\u4f20\u662f\u5426\u6b63\u5e38\u3002<\/li>\n<\/ul>\n<\/li>\n<li>\u786e\u8ba4 nvidia-container-toolkit\uff1a\n<ul>\n<li>\u5982\u679c\u5bbf\u4e3b\u673a\u4e0a\u7684 <code>nvidia-smi<\/code> \u6b63\u5e38\uff0c\u800c\u5bb9\u5668\u91cc\u5931\u8d25\uff0c\u591a\u534a\u662f toolkit \u914d\u7f6e\u95ee\u9898\u3002<\/li>\n<\/ul>\n<\/li>\n<li>\u8b66\u60d5\u9a71\u52a8\u201c\u6df7\u642d\u201d\uff1a\n<ul>\n<li>\u4e0d\u8981\u5728\u955c\u50cf\u91cc\u518d\u6253\u5305\u4e00\u5957\u548c\u5bbf\u4e3b\u673a\u51b2\u7a81\u7684\u9a71\u52a8\uff0c\u663e\u5361\u9a71\u52a8\u5e94\u8be5\u5b8c\u5168\u7531\u5bbf\u4e3b\u673a\u63a5\u7ba1\u3002<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<p>\n\u5982\u679c\u4f60\u7528\u7684\u662f Kubernetes \u6216\u6258\u7ba1\u5e73\u53f0\uff0c\u8bb0\u5f97\u786e\u8ba4\u65e5\u672c\u533a\u57df\u7684 GPU \u8282\u70b9\u6c60\u662f\u5426\u6b63\u786e\u5411 Pod \u66b4\u9732\u4e86\u8bbe\u5907\uff0c\u5e76\u4e14 Pod \u8d44\u6e90\u8bf7\u6c42\u5199\u5bf9\u4e86\u3002\u4e00\u4e2a YAML \u62fc\u5199\u9519\u8bef\uff0c\u6709\u65f6\u4f1a\u4f2a\u88c5\u6210\u201c\u6df1\u5ea6\u6846\u67b6\u5185\u90e8 bug\u201d\u3002\n<\/p>\n<h2><strong>9. \u7cfb\u7edf\u5e93\u4e0e\u539f\u751f\u4f9d\u8d56\u7684\u4f0f\u51fb<\/strong><\/h2>\n<p>\n\u5373\u4f7f CUDA \u548c\u6846\u67b6\u90fd\u6b63\u5e38\u5de5\u4f5c\uff0c\u539f\u751f\u7cfb\u7edf\u5e93\u4e5f\u4f1a\u5728\u8fc1\u79fb\u540e\u6697\u4e2d\u51fa\u624b\u3002\u4e0d\u540c Linux \u53d1\u884c\u7248\u548c\u7248\u672c\u5bf9\u7cfb\u7edf\u5e93\u7684\u6253\u5305\u540d\u5b57\u3001\u8def\u5f84\u3001\u7248\u672c\u53ef\u80fd\u5b8c\u5168\u4e0d\u540c\u3002\n<\/p>\n<ul>\n<li>\u5178\u578b\u75c7\u72b6\uff1a<code>OSError: libXYZ.so.6: cannot open shared object file<\/code>\u3002<\/li>\n<li>\u5e38\u89c1\u539f\u56e0\uff1a\u7cfb\u7edf\u5305\u6ca1\u6709\u5b89\u88c5\uff0c\u6216\u8005\u5e93\u7248\u672c\u4e0d\u5339\u914d\u3002<\/li>\n<li>\u5e38\u89c1\u5acc\u7591\u5bf9\u8c61\uff1a\n<ul>\n<li>OpenCV \u53ca\u5176\u4f9d\u8d56\uff08\u6bd4\u5982 <code>libglib2.0<\/code>\uff09\u3002<\/li>\n<li>\u56fe\u50cf\u7f16\u89e3\u7801\u5e93\u5982 <code>libjpeg<\/code>\uff0c\u89c6\u9891\u76f8\u5173\u5e93\u5982 <code>ffmpeg<\/code>\u3002<\/li>\n<li>blas\/lapack\u3001MKL \u6216 cuBLAS \u7b49\u76f8\u5173\u7ec4\u4ef6\u51b2\u7a81\u3002<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>\n\u5728\u65b0\u670d\u52a1\u5668\u4e0a\u7684\u6392\u67e5\u7b56\u7565\uff1a\n<\/p>\n<ol>\n<li>\u5728\u505a\u4efb\u4f55\u64cd\u4f5c\u4e4b\u524d\uff0c\u628a\u5b8c\u6574\u7684\u5806\u6808\u8ffd\u8e2a\u4fe1\u606f\u8bfb\u4e00\u904d\u3002<\/li>\n<li>\u5bf9\u5931\u8d25\u7684\u4e8c\u8fdb\u5236\u6216 Python \u6269\u5c55\u4f7f\u7528 <code>ldd<\/code>\uff0c\u67e5\u770b\u5b83\u671f\u671b\u94fe\u63a5\u54ea\u4e9b\u7b26\u53f7\u3002<\/li>\n<li>\u7528\u65b0\u7cfb\u7edf\u5bf9\u5e94\u7684\u5305\u7ba1\u7406\u5668\u5b89\u88c5\u7f3a\u5931\u7684\u7cfb\u7edf\u5e93\u3002<\/li>\n<\/ol>\n<p>\n\u5f53\u4f60\u4ece\u672c\u5730\u673a\u623f\u8fc1\u79fb\u5230\u65e5\u672c\u673a\u623f\u7684 GPU \u670d\u52a1\u5668\u6258\u7ba1\u65f6\uff0c\u4e5f\u53ef\u80fd\u987a\u5e26\u4ece\u4e00\u4e2a\u53d1\u884c\u7248\u5bb6\u65cf\u5207\u6362\u5230\u4e86\u53e6\u4e00\u4e2a\uff08\u4f8b\u5982\u4ece Debian \u7cfb\u5230 RHEL \u7cfb\uff09\u3002\u8fd9\u4e00\u53d8\u5316\u672c\u8eab\uff0c\u5c31\u8db3\u4ee5\u8ba9\u4f60\u5fc5\u987b\u91cd\u65b0\u68b3\u7406\u4e00\u904d\u7cfb\u7edf\u7ea7\u4f9d\u8d56\u3002\n<\/p>\n<h2><strong>10. \u6a21\u578b\u6587\u4ef6\u3001\u8def\u5f84\u4e0e\u6743\u9650<\/strong><\/h2>\n<p>\n\u5e76\u4e0d\u662f\u6240\u6709\u7684\u5d29\u6e83\u90fd\u662f CUDA \u60f9\u7684\u7978\u3002\u6709\u65f6\u5019\u53ea\u662f\u6a21\u578b\u6839\u672c\u4e0d\u5728\u4ee3\u7801\u8ba4\u4e3a\u7684\u4f4d\u7f6e\uff0c\u6216\u8005\u64cd\u4f5c\u7cfb\u7edf\u76f4\u63a5\u4e0d\u8ba9\u4f60\u7684\u8fdb\u7a0b\u78b0\u90a3\u4e9b\u6587\u4ef6\u3002\n<\/p>\n<ul>\n<li><strong>\u786c\u7f16\u7801\u8def\u5f84<\/strong>\uff1a\u5f88\u591a\u9057\u7559\u4ee3\u7801\u4e2d\u5199\u6b7b\u4e86\u53ea\u80fd\u5728\u65e7\u670d\u52a1\u5668\u6210\u7acb\u7684\u7edd\u5bf9\u8def\u5f84\u3002<\/li>\n<li><strong>\u76f8\u5bf9\u8def\u5f84<\/strong>\uff1a\u5728\u65b0\u673a\u5668\u4e0a\u4ece\u4e0d\u540c\u7684\u5de5\u4f5c\u76ee\u5f55\u542f\u52a8\u7a0b\u5e8f\uff0c\u4f1a\u8ba9\u76f8\u5bf9\u8def\u5f84\u7684\u5bfc\u5165\u548c\u6587\u4ef6\u67e5\u627e\u5f7b\u5e95\u5931\u6548\u3002<\/li>\n<li><strong>\u6743\u9650\u95ee\u9898<\/strong>\uff1a\u5728\u670d\u52a1\u5668\u6258\u7ba1\u6216\u5171\u4eab\u670d\u52a1\u5668\u79df\u7528\u73af\u5883\u4e2d\uff0cuid\/gid \u6620\u5c04\u53d1\u751f\u53d8\u5316\uff0c\u7ed3\u679c\u5c31\u662f\u53ea\u6709 root \u80fd\u8bfb\u4f60\u7684 checkpoint\u3002<\/li>\n<\/ul>\n<p>\n\u4e00\u4e2a\u57fa\u7840\u68c0\u67e5\u6e05\u5355\uff1a\n<\/p>\n<ol>\n<li>\u6bcf\u6b21\u4ee3\u7801\u6253\u5f00\u6a21\u578b\u6216\u6570\u636e\u96c6\u6587\u4ef6\u65f6\uff0c\u90fd\u628a\u5b8c\u6574\u8def\u5f84\u6253\u5370\u5230\u65e5\u5fd7\u91cc\u3002<\/li>\n<li>\u5728\u76f8\u5173\u76ee\u5f55\u4e0b\u6267\u884c <code>ls -l<\/code>\uff0c\u770b\u770b\u5230\u5e95\u662f\u8c01\u5728\u62e5\u6709\u548c\u8bbf\u95ee\u8fd9\u4e9b\u6587\u4ef6\u3002<\/li>\n<li>\u5728\u591a\u53f0\u673a\u5668\u4e4b\u95f4\u5bf9\u9f50\u7528\u6237\u548c\u7528\u6237\u7ec4\uff0c\u5c24\u5176\u662f\u628a\u78c1\u76d8\u7269\u7406\u8fc1\u5230\u65b0\u7684\u65e5\u672c\u670d\u52a1\u5668\u6258\u7ba1\u673a\u67dc\u65f6\u3002<\/li>\n<\/ol>\n<p>\n\u8def\u5f84\u548c\u6743\u9650\u9519\u8bef\u770b\u4e0a\u53bb\u201c\u5f88\u4f4e\u7ea7\u201d\uff0c\u5374\u975e\u5e38\u8d39\u65f6\u95f4\u2014\u2014\u5c24\u5176\u662f\u5728\u4f60\u5148\u5165\u4e3a\u4e3b\u5730\u8ba4\u4e3a\u201c\u673a\u623f\u4e00\u6362\uff0c\u6587\u4ef6\u7cfb\u7edf\u8fd8\u662f\u539f\u6765\u7684\u90a3\u4e00\u5957\u201d\u7684\u60c5\u51b5\u4e0b\u3002\n<\/p>\n<h2><strong>11. \u7f51\u7edc\u3001\u4e0b\u8f7d\u4e0e\u201c\u5361\u6b7b\u5728\u90a3\u513f\u201d\u7684\u573a\u666f<\/strong><\/h2>\n<p>\n\u5207\u6362\u5230\u65e5\u672c\u533a\u57df\u4e4b\u540e\uff0c\u6a21\u578b\u62c9\u53d6\u5916\u90e8\u8d44\u6e90\u7684\u65b9\u5f0f\u53ef\u80fd\u4f1a\u53d1\u751f\u6839\u672c\u53d8\u5316\u3002\u5982\u679c\u4f60\u7684\u542f\u52a8\u6d41\u7a0b\u9700\u8981\u4ece\u8fdc\u7a0b\u4ed3\u5e93\u6216\u516c\u5171\u5b58\u50a8\u6876\u4e0b\u8f7d\u6743\u91cd\uff0c\u4e0b\u8f7d\u8d85\u65f6\u6216\u88ab\u9650\u6d41\uff0c\u5f88\u53ef\u80fd\u4f1a\u4f2a\u88c5\u6210\u201c\u7b97\u529b\u95ee\u9898\u201d\u3002\n<\/p>\n<ul>\n<li>\u4f60\u662f\u4e0d\u662f\u6bcf\u6b21\u542f\u52a8\u90fd\u8981\u4ece Hugging Face\u3001PyPI \u6216\u67d0\u4e2a model zoo \u62c9\u53d6\u8d44\u6e90\uff1f<\/li>\n<li>\u65e5\u672c\u673a\u623f\u4e2d\u7684\u516c\u53f8\u9632\u706b\u5899\u6216\u6570\u636e\u4e2d\u5fc3\u9632\u706b\u5899\u662f\u5426\u5c4f\u853d\u4e86\u90e8\u5206\u5916\u90e8\u5730\u5740\uff1f<\/li>\n<li>DNS \u662f\u5426\u89e3\u6790\u5230\u4e86\u548c\u4ee5\u5f80\u4e0d\u540c\u7684\u955c\u50cf\uff0c\u5ef6\u8fdf\u975e\u5e38\u5927\uff1f<\/li>\n<\/ul>\n<p>\n\u4e3a\u4e86\u964d\u4f4e\u98ce\u9669\uff0c\u4f60\u53ef\u4ee5\uff1a\n<\/p>\n<ol>\n<li>\u628a\u5173\u952e\u6a21\u578b\u6743\u91cd\u548c\u6570\u636e\u96c6\u7f13\u5b58\u5230 GPU \u670d\u52a1\u5668\u672c\u5730\u3002<\/li>\n<li>\u5728\u9760\u8fd1\u65e5\u672c\u73af\u5883\u7684\u4f4d\u7f6e\u642d\u5efa\u5236\u54c1\u4ed3\u5e93\uff0c\u955c\u50cf\u6838\u5fc3\u4f9d\u8d56\u3002<\/li>\n<li>\u8ba9\u6240\u6709\u5916\u90e8\u4e0b\u8f7d\u884c\u4e3a\u90fd\u662f\u663e\u5f0f\u7684\u3001\u6709\u6e05\u6670\u65e5\u5fd7\u548c\u6307\u6570\u9000\u907f\uff0c\u800c\u4e0d\u662f\u6084\u65e0\u58f0\u606f\u5730\u201c\u65e0\u9650\u7b49\u5f85\u201d\u3002<\/li>\n<\/ol>\n<p>\n\u5982\u679c\u7a0b\u5e8f\u5728\u65b0\u673a\u5668\u4e0a\u4e00\u518d\u201c\u5361\u6b7b\u201d\uff0c\u5148\u68c0\u67e5\u5b83\u662f\u4e0d\u662f\u5b9e\u9645\u4e0a\u5728\u7b49\u7f51\u7edc\uff0c\u800c\u4e0d\u662f\u5728\u7b49 GPU\u3002\n<\/p>\n<h2><strong>12. \u4e00\u5957\u5b9e\u7528\u3001\u53ef\u91cd\u590d\u7684\u8c03\u8bd5\u6d41\u7a0b<\/strong><\/h2>\n<p>\n\u4e3a\u4e86\u907f\u514d\u65e0\u5934\u82cd\u8747\u5f0f\u7684\u4e71\u8bd5\uff0c\u628a\u4e0a\u9762\u7684\u5185\u5bb9\u6574\u5408\u6210\u4e00\u5957\u4efb\u4f55\u56e2\u961f\u6210\u5458\u90fd\u80fd\u7167\u7740\u6267\u884c\u7684\u6d41\u7a0b\uff0c\u6bcf\u5f53\u6a21\u578b\u5728\u73af\u5883\u53d8\u66f4\u540e\u62d2\u7edd\u8fd0\u884c\u65f6\uff0c\u5c31\u6309\u8fd9\u5957\u6d41\u7a0b\u6765\u3002\n<\/p>\n<ol>\n<li><strong>\u57fa\u7840\u5065\u5eb7\u68c0\u67e5<\/strong>\uff1a\n<ul>\n<li>\u8fd0\u884c <code>nvidia-smi<\/code> \u548c\u4e00\u4e2a\u6781\u7b80 CUDA \u793a\u4f8b\uff0c\u786e\u8ba4\u663e\u5361\u672c\u8eab\u6ca1\u95ee\u9898\u3002<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u7248\u672c\u6e05\u5355<\/strong>\uff1a\n<ul>\n<li>\u8bb0\u5f55 OS\u3001\u5185\u6838\u3001\u9a71\u52a8\u3001CUDA runtime\u3001Python \u548c\u6846\u67b6\u7248\u672c\u3002<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u73af\u5883\u5bf9\u6bd4<\/strong>\uff1a\n<ul>\n<li>\u628a\u65b0\u73af\u5883\u548c\u539f\u751f\u4ea7\u73af\u5883\u9010\u9879\u5bf9\u6bd4\uff0c\u5148\u4fee\u8865\u90a3\u4e9b\u663e\u800c\u6613\u89c1\u7684\u5dee\u5f02\u3002<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u6700\u5c0f\u590d\u73b0<\/strong>\uff1a\n<ul>\n<li>\u5199\u4e00\u4e2a\u6700\u5c0f\u811a\u672c\u6765\u590d\u73b0\u95ee\u9898\uff0c\u4e0d\u8981\u5e26\u590d\u6742\u914d\u7f6e\uff0c\u4e5f\u4e0d\u8981\u5e26\u82b1\u5f0f\u8bad\u7ec3\u5668\u3002<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u5347\u7ea7\u8def\u5f84<\/strong>\uff1a\n<ul>\n<li>\u5982\u679c\u4f60\u8fde\u5355\u5361\u7684\u73a9\u5177\u811a\u672c\u90fd\u8dd1\u4e0d\u901a\uff0c\u5c31\u5148\u522b\u52a8\u591a\u8282\u70b9\u6216\u591a GPU \u96c6\u7fa4\u3002<\/li>\n<\/ul>\n<\/li>\n<\/ol>\n<p>\n\u4e00\u65e6\u8fd9\u5957\u6d41\u7a0b\u88ab\u5199\u8fdb\u6587\u6863\uff0c\u5c31\u628a\u5b83\u5206\u4eab\u7ed9\u6574\u4e2a\u56e2\u961f\uff0c\u5e76\u628a\u5b83\u4f5c\u4e3a\u4eca\u540e\u6240\u6709\u73af\u5883\u8fc1\u79fb\uff08\u65e0\u8bba\u662f\u672c\u5730\u673a\u623f\u3001\u4e91\u533a\u57df\u8fd8\u662f\u65e5\u672c GPU \u6570\u636e\u4e2d\u5fc3\uff09\u7684 Runbook \u4e4b\u4e00\u3002\n<\/p>\n<h2><strong>13. \u9762\u5411\u65e5\u672c\u673a\u623f\u7684\u670d\u52a1\u5668\u79df\u7528\u4e0e\u670d\u52a1\u5668\u6258\u7ba1\u6ce8\u610f\u4e8b\u9879<\/strong><\/h2>\n<p>\n\u5f53\u4f60\u7684 GPU \u843d\u5730\u5728\u65e5\u672c\u65f6\uff0c\u5728\u8fc1\u79fb\u524d\u540e\u4f1a\u591a\u51fa\u4e00\u4e9b\u9700\u8981\u989d\u5916\u5173\u6ce8\u7684\u65cb\u94ae\u3002\u8fd9\u4e9b\u66f4\u591a\u662f\u5173\u4e8e\u57fa\u7840\u8bbe\u65bd\u4e0e\u533a\u57df\u3001\u670d\u52a1\u5546\u7684\u4e92\u52a8\uff0c\u800c\u4e0d\u53ea\u662f CUDA \u672c\u8eab\u3002\n<\/p>\n<ul>\n<li><strong>\u5ef6\u8fdf\u611f\u77e5\u7684\u67b6\u6784\u8bbe\u8ba1<\/strong>\uff1a\n<ul>\n<li>\u5982\u679c\u4f60\u7684\u7528\u6237\u6216\u6570\u636e\u6e56\u8fd8\u5728\u5176\u4ed6\u533a\u57df\uff0c\u8bad\u7ec3\u548c\u63a8\u7406\u7684\u7aef\u5230\u7aef\u5ef6\u8fdf\u53ef\u80fd\u4f1a\u53d8\u9ad8\uff0c\u4ece\u800c\u5f71\u54cd\u4f60\u5bf9\u9884\u53d6\u548c\u7f13\u5b58\u7b56\u7565\u7684\u8bbe\u8ba1\u3002<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u5e26\u5bbd\u4e0e\u51fa\u7f51\u7b56\u7565<\/strong>\uff1a\n<ul>\n<li>\u6709\u4e9b\u65e5\u672c GPU \u670d\u52a1\u5668\u79df\u7528\u5957\u9910\u4f1a\u9650\u5236\u51fa\u7f51\u5e26\u5bbd\u6216\u6309 GiB \u6536\u8d39\uff0c\u6301\u7eed\u4ece\u5176\u4ed6\u533a\u57df\u540c\u6b65\u6570\u636e\u96c6\u53ef\u80fd\u4f1a\u53d8\u6210\u610f\u6599\u4e4b\u5916\u7684\u5927\u5934\u6210\u672c\u3002<\/li>\n<\/ul>\n<\/li>\n<li><strong>\u670d\u52a1\u5668\u6258\u7ba1\u673a\u623f\u7684\u4f9b\u7535\u4e0e\u6563\u70ed\u4e0a\u9650<\/strong>\uff1a\n<ul>\n<li>\u5982\u679c\u4f60\u81ea\u5df1\u91c7\u8d2d\u5bc6\u96c6 GPU \u670d\u52a1\u5668\u653e\u8fdb\u65e5\u672c\u670d\u52a1\u5668\u6258\u7ba1\u673a\u67dc\uff0c\u8981\u63d0\u524d\u6838\u5bf9\u673a\u67dc\u7684\u529f\u7387\u5bc6\u5ea6\u4e0a\u9650\u3002\u88ab\u52a8\u9650\u7535\u5f80\u5f80\u4f1a\u8868\u73b0\u4e3a\u6027\u80fd\u5ffd\u9ad8\u5ffd\u4f4e\u3002<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>\n\u628a\u670d\u52a1\u5668\u79df\u7528\u6216\u670d\u52a1\u5668\u6258\u7ba1\u670d\u52a1\u5546\u7684\u6587\u6863\u5f53\u6210\u6280\u672f\u6808\u7684\u4e00\u90e8\u5206\uff0c\u800c\u4e0d\u662f\u201c\u5408\u540c\u9644\u4ef6\u7684\u5c0f\u5b57\u201d\u3002\u5f53\u8fc1\u79fb\u51fa\u73b0\u5f02\u5e38\u65f6\uff0c\u638c\u63e1\u5e73\u53f0\u7684\u771f\u5b9e\u80fd\u529b\u8fb9\u754c\uff0c\u6709\u52a9\u4e8e\u4f60\u533a\u5206\u201c\u73af\u5883 Bug\u201d\u4e0e\u201c\u57fa\u7840\u8bbe\u65bd\u786c\u9650\u5236\u201d\u3002\n<\/p>\n<h2><strong>14. \u4e00\u4e2a\u66f4\u7a33\u5b9a\u8fc1\u79fb\u7684\u914d\u7f6e\u793a\u4f8b<\/strong><\/h2>\n<p>\n\u4e3a\u4e86\u66f4\u76f4\u89c2\uff0c\u6211\u4eec\u53ef\u4ee5\u7ed9\u51fa\u4e00\u4e2a\u201c\u5df2\u77e5\u7a33\u5b9a\u201d\u7684\u6781\u7b80\u914d\u7f6e\u5927\u7eb2\uff0c\u65b9\u4fbf\u4f60\u5728\u8fc1\u79fb\u5230\u65e5\u672c\u6216\u5728\u65e5\u672c\u533a\u57df\u5185\u90e8\u8fc1\u79fb\u5de5\u4f5c\u8d1f\u8f7d\u65f6\uff0c\u7528\u4f5c\u5bf9\u7167\u57fa\u7ebf\uff1a\n<\/p>\n<ul>\n<li>OS\uff1aUbuntu LTS\uff0820.04 \u6216 22.04\uff09\uff0c\u56fa\u5b9a\u7248\u672c\u5e76\u53ca\u65f6\u6253\u8865\u4e01\u3002<\/li>\n<li>\u9a71\u52a8\uff1a\u660e\u786e\u88ab\u5f53\u524d GPU \u4ee3\u6570\u548c CUDA toolkit \u5b98\u65b9\u652f\u6301\u7684\u7248\u672c\u3002<\/li>\n<li>CUDA\uff1a\u6bcf\u4e2a\u8282\u70b9\u53ea\u4fdd\u7559\u4e00\u4e2a\u4e3b\u7248\u672c\uff0c\u907f\u514d\u6b8b\u7559\u534a\u5347\u7ea7\u7684\u5de5\u5177\u5305\u3002<\/li>\n<li>Python\uff1a\u6bcf\u4e2a\u9879\u76ee\u4e00\u4e2a\u7248\u672c\uff0c\u6709\u6e05\u6670\u7684\u73af\u5883\u6587\u4ef6\u5e76\u7eb3\u5165\u7248\u672c\u63a7\u5236\u3002<\/li>\n<li>\u6846\u67b6\uff1a\u9501\u5b9a\u5177\u4f53\u7248\u672c\u7684 PyTorch \u6216 TensorFlow\uff0c\u800c\u4e0d\u662f\u76f2\u76ee\u7528 <code>latest<\/code>\u3002<\/li>\n<\/ul>\n<p>\n\u518d\u5199\u4e00\u4e2a\u77ed\u811a\u672c\uff0c\u6253\u5370\u4e0a\u8ff0\u6240\u6709\u7248\u672c\u4fe1\u606f\u4ee5\u53ca <code>torch.cuda.is_available()<\/code> \u6216\u4f60\u6240\u7528\u6846\u67b6\u7684\u7b49\u4ef7\u68c0\u67e5\u3002\u628a\u5b83\u7eb3\u5165\u6bcf\u53f0\u65b0 GPU \u670d\u52a1\u5668\u4e0a\u7ebf\u540e\u7684\u68c0\u67e5\u6e05\u5355\u4e2d\uff0c\u6bcf\u6b21\u73af\u5883\u8fc1\u79fb\u4e4b\u540e\u5148\u8dd1\u4e00\u904d\u3002\n<\/p>\n<h2><strong>15. \u201c\u4eba\u5473\u5185\u5bb9\u201d\u548c\u53cd AI \u98ce\u683c\u7684\u81ea\u89c9<\/strong><\/h2>\n<p>\n\u8d8a\u6765\u8d8a\u591a\u7684\u5de5\u7a0b\u5e08\u4f1a\u5728\u610f\uff1a\u4ed6\u4eec\u6b63\u5728\u8bfb\u7684\u8fd0\u7ef4\u6307\u5357\uff0c\u770b\u8d77\u6765\u50cf\u662f\u4e00\u4e2a\u771f\u7684\u5728\u673a\u623f\u71ac\u8fc7\u591c\u7684\u4eba\u5199\u7684\uff0c\u8fd8\u662f\u67d0\u79cd\u901a\u7528\u6a21\u677f\u81ea\u52a8\u751f\u6210\u7684\u3002\u5728 Pager \u54cd\u4e2a\u4e0d\u505c\u7684\u65f6\u5019\uff0c\u4f60\u5f53\u7136\u53ea\u60f3\u770b\u524d\u4e00\u79cd\u5185\u5bb9\u3002\n<\/p>\n<ul>\n<li>\u907f\u514d\u90a3\u79cd\u4ece\u4e0d\u63d0\u771f\u5b9e\u547d\u4ee4\u6216\u62a5\u9519\u4fe1\u606f\u7684\u7a7a\u6d1e\u201c\u4e09\u6b65\u6cd5\u201d\u53e3\u53f7\u3002<\/li>\n<li>\u591a\u7ed9\u51fa\u5177\u4f53\u7684\u63a2\u9488\uff08<code>nvidia-smi<\/code>\u3001<code>torch.cuda.is_available()<\/code>\u3001\u7279\u5b9a\u65e5\u5fd7\u7247\u6bb5\uff09\uff0c\u5c11\u7ed9\u62bd\u8c61\u7a7a\u8bdd\u3002<\/li>\n<li>\u4fdd\u6301\u4e00\u70b9\u70b9\u201c\u6709\u6001\u5ea6\u201d\uff1a\u5199\u51fa\u4f60\u771f\u8e29\u8fc7\u7684\u5751\uff0c\u4ee5\u53ca\u90a3\u4e9b\u786e\u5b9e\u5e2e\u4f60\u7701\u8fc7\u65f6\u95f4\u7684\u5b9e\u6218\u6280\u5de7\u3002<\/li>\n<\/ul>\n<p>\n\u5982\u679c\u4f60\u7684\u5185\u90e8\u6587\u6863\u6216\u5bf9\u5916 Runbook \u770b\u8d77\u6765\u50cf\u662f\u5343\u7bc7\u4e00\u5f8b\u7684 AI 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\u628a\u6280\u672f\u6808\u201c\u753b\u201d\u51fa\u6765<\/strong><\/h2>\n<p>\n\u6709\u65f6\u5019\uff0c\u4e00\u5f20\u56fe\u6bd4\u4e00\u5343\u884c\u65e5\u5fd7\u66f4\u6709\u7528\u3002\u54ea\u6015\u662f\u4e00\u5f20\u7c97\u7cd9\u7684\u8349\u56fe\uff0c\u628a\u786c\u4ef6\u3001\u9a71\u52a8\u3001\u5bb9\u5668\u3001\u6846\u67b6\u548c\u5e94\u7528\u4ee3\u7801\u4e4b\u95f4\u7684\u5173\u7cfb\u753b\u51fa\u6765\uff0c\u4e5f\u80fd\u8ba9\u6392\u969c\u8ba8\u8bba\u4e0d\u81f3\u4e8e\u592a\u62bd\u8c61\u3002\n<\/p>\n<p>\n\u6bcf\u5f53\u4f60\u5f15\u5165\u4e00\u79cd\u65b0\u73af\u5883\u2014\u2014\u65e0\u8bba\u662f\u65b0\u7684\u65e5\u672c\u533a\u57df\u3001\u65b0\u7684\u670d\u52a1\u5668\u79df\u7528\u670d\u52a1\u5546\uff0c\u8fd8\u662f\u65b0\u7684\u670d\u52a1\u5668\u6258\u7ba1\u673a\u67dc\u2014\u2014\u90fd\u66f4\u65b0\u90a3\u5f20\u56fe\u3002\u5b83\u80fd\u9632\u6b62\u56e2\u961f\u6210\u5458\u5728\u5b9e\u9645\u4e0a\u914d\u7f6e\u5dee\u5f02\u5de8\u5927\u7684\u8282\u70b9\u4e4b\u95f4\uff0c\u60f3\u5f53\u7136\u5730\u5047\u8bbe\u201c\u4e00\u5207\u90fd\u4e00\u6837\u201d\u3002\n<\/p>\n<h2><strong>17. 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More&#8230;<\/a><\/p>\n","protected":false},"author":11,"featured_media":36076,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[80],"tags":[],"class_list":["post-36079","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-knowledge"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.2 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>\u4fee\u590d GPU \u6a21\u578b\u5728\u66f4\u6362\u670d\u52a1\u5668\u73af\u5883\u540e\u65e0\u6cd5\u8fd0\u884c\u7684\u95ee\u9898<\/title>\n<meta name=\"description\" content=\"\u6df1\u5ea6\u6392\u67e5\u6307\u5357\uff1a\u5f53\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u5728 GPU \u670d\u52a1\u5668\u73af\u5883\u53d8\u66f4\u540e\u65e0\u6cd5\u8fd0\u884c\u65f6\uff0c\u4ece\u5e95\u5c42\u5230\u5e94\u7528\u5c42\u9010\u6b65\u5206\u6790\uff0c\u5e76\u7ed3\u5408\u65e5\u672c GPU 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