雲服務:Google Cloud Platform
作業系統:ubuntu 18.04 LTS
顯示卡:TESLA T4
安裝 GPU
以下皆在 root 下執行
1 2 3
| $ sudo apt-get update $ sudo apt-get install -y ubuntu-drivers-common $ ubuntu-drivers devices
|
輸出看到可以安裝 440 的驅動版本
1 2 3 4 5 6
| == /sys/devices/pci0000:00/0000:00:04.0 == modalias : pci:v000010DEd00001EB8sv000010DEsd000012A2bc03sc02i00 vendor : NVIDIA Corporation driver : nvidia-driver-435 - distro non-free driver : nvidia-driver-440 - distro non-free recommended driver : xserver-xorg-video-nouveau - distro free builtin
|
安裝驅動
1
| $ sudo ubuntu-drivers autoinstall
|
安裝 cuda 10.2 & cuDNN
安裝 cuda 10.2 軟件包
1 2 3 4
| $ cd /tmp $ wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.2.89-1_amd64.deb $ sudo dpkg -i cuda-repo-ubuntu1804_10.2.89-1_amd64.deb $ sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub
|
安裝 cuDNN v7.6.5 軟件包
cuDNN 軟件包到 這裡下載,載 Runtime 與 Developer
- cuDNN Runtime Library for Ubuntu18.04 (Deb)
- cuDNN Developer Library for Ubuntu18.04 (Deb)
安裝軟件包
1 2
| $ sudo dpkg -i libcudnn7_7.6.5.32-1+cuda10.2_amd64.deb $ sudo dpkg -i libcudnn7-dev_7.6.5.32-1+cuda10.2_amd64.deb
|
執行安裝後重開機
1 2 3 4 5 6
| $ sudo apt-get update $ sudo apt-get install --no-install-recommends \ cuda-10-2 \ libcudnn7=7.6.5.32-1+cuda10.2 \ libcudnn7-dev=7.6.5.32-1+cuda10.2 $ sudo reboot
|
重開機後測試
安裝 Miniconda
1 2
| $ cd /tmp && curl -O https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh $ sudo bash Miniconda3-latest-Linux-x86_64.sh
|
安裝位置 /opt/miniconda3
,並將路徑新增至 .bashrc
1
| export PATH="/opt/miniconda3/bin:$PATH"
|
安裝 tensorflow
1 2 3
| pip install --upgrade --user pip pip install tensorflow-gpu python -c 'import tensorflow as tf; tf.test.gpu_device_name()'
|
輸出結果為