搭建nvidia-docker运行环境-Ubutu16.04
安装 nvidia-docker
# If you have nvidia-docker 1.0 installed: we need to remove it and all existing GPU containersdocker volume ls -q -f driver=nvidia-docker | xargs -r -I{} -n1 docker ps -q -a -f volume={} | xargs -r docker rm -f
sudo apt-get purge -y nvidia-docker# Add the package repositoriescurl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
curl -s -L https://nvidia.github.io/nvidia-docker/ubuntu16.04/amd64/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
sudo apt-get update# Install nvidia-docker2 and reload the Docker daemon configurationsudo apt-get install -y nvidia-docker2
sudo pkill -SIGHUP dockerd
//安装ubuntu,配置caffe所需环境
sudo nvidia-docker search ubuntu
sudo nvidia-docker pull ubuntu
使用dockerfile生成镜像
本文使用的dockerfile文件如下：
FROM laika/ubuntu:base_image
LABEL maintainer 'wanghq'
ENV PYTHONPATH=‘/install_src/pyfaster-rcnn/python’
运行：sudo docker build -t "ubuntu:V1"
//启动容器
sudo nvidia-docker run -it--privileged=true--name=wanghq ubuntu:V1 /bin/bash
//注意：此处必须添加--privileged=true使得容器真正获取主机硬件资源，包括GPU显卡资源
rtaneja@DGX:~$ nvidia-docker
开发GPU应用程序
对于CUDA开发，你可以先从Dockerhub提取nvidia / cuda镜像。
rtaneja@DGX:~$ nvidia-docker run --rm -ti nvidia/cuda:8.0 nvidia-smi8.0: Pulling from nvidia/cuda