机器学习环境搭建

发表于 更新于 阅读次数： Artalk：

系统

系统方面，目前经基本测试，最好选择ubuntu 22 LTS。
图省事的话，可以直接选择desktop 22 LTS版本，英伟达驱动基本自动能装好,
硬件设备：intel 14、3090 24GB

测试驱动是否安装成功

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nvidia-smi

应该显示类似输出

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+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 550.107.02             Driver Version: 550.107.02     CUDA Version: 12.4     |
|-----------------------------------------+------------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id          Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |           Memory-Usage | GPU-Util  Compute M. |
|                                         |                        |               MIG M. |
|=========================================+========================+======================|
|   0  NVIDIA GeForce RTX 3090        Off |   00000000:01:00.0 Off |                  N/A |
|  0%   44C    P8             26W /  350W |     109MiB /  24576MiB |      0%      Default |
|                                         |                        |                  N/A |
+-----------------------------------------+------------------------+----------------------+

+-----------------------------------------------------------------------------------------+
| Processes:                                                                              |
|  GPU   GI   CI        PID   Type   Process name                              GPU Memory |
|        ID   ID                                                               Usage      |
|=========================================================================================|
|    0   N/A  N/A      1304      G   /usr/lib/xorg/Xorg                             86MiB |
+-----------------------------------------------------------------------------------------+

驱动

1.参考英伟达官方教程
2.参考英伟达CUDA Toolkit
3.参考英伟达cuDNN

安装cuda驱动

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wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get -y install cuda-toolkit-12-6

安装cuDDN驱动

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wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb
sudo dpkg -i cuda-keyring_1.1-1_all.deb
sudo apt-get update
sudo apt-get -y install cudnn

docker

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sudo apt install -y nvidia-docker2
sudo systemctl restart docker

torch

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pip3 install torch torchvision torchaudio

tensorflow

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pip3 install tensorflow