# Docker Images ([简体中文](DOCKER_IMAGES_CN.md)|English) This document maintains a list of docker images provided by Paddle Serving. ## Get docker image You can get images in two ways: 1. Pull image directly from `hub.baidubce.com ` or `docker.io` through TAG: ```shell docker pull hub.baidubce.com/paddlepaddle/serving: # hub.baidubce.com docker pull paddlepaddle/serving: # hub.docker.com ``` 2. Building image based on dockerfile Create a new folder and copy Dockerfile to this folder, and run the following command: ```shell docker build -t : . ``` ## Image description Runtime images cannot be used for compilation. | Description | OS | TAG | Dockerfile | | :----------------------------------------------------------: | :-----: | :--------------------------: | :----------------------------------------------------------: | | CPU runtime | CentOS7 | latest | [Dockerfile](../tools/Dockerfile) | | CPU development | CentOS7 | latest-devel | [Dockerfile.devel](../tools/Dockerfile.devel) | | GPU (cuda9.0-cudnn7) runtime | CentOS7 | latest-cuda9.0-cudnn7 | [Dockerfile.cuda9.0-cudnn7](../tools/Dockerfile.cuda9.0-cudnn7) | | GPU (cuda9.0-cudnn7) development | CentOS7 | latest-cuda9.0-cudnn7-devel | [Dockerfile.cuda9.0-cudnn7.devel](../tools/Dockerfile.cuda9.0-cudnn7.devel) | | GPU (cuda10.0-cudnn7) runtime | CentOS7 | latest-cuda10.0-cudnn7 | [Dockerfile.cuda10.0-cudnn7](../tools/Dockerfile.cuda10.0-cudnn7) | | GPU (cuda10.0-cudnn7) development | CentOS7 | latest-cuda10.0-cudnn7-devel | [Dockerfile.cuda10.0-cudnn7.devel](../tools/Dockerfile.cuda10.0-cudnn7.devel) | | CPU development (Used to compile packages on Ubuntu) | CentOS6 | | [Dockerfile.centos6.devel](../tools/Dockerfile.centos6.devel) | | GPU (cuda9.0-cudnn7) development (Used to compile packages on Ubuntu) | CentOS6 | | [Dockerfile.centos6.cuda9.0-cudnn7.devel](../tools/Dockerfile.centos6.cuda9.0-cudnn7.devel) | ## Requirements for running CUDA containers Running a CUDA container requires a machine with at least one CUDA-capable GPU and a driver compatible with the CUDA toolkit version you are using. The machine running the CUDA container **only requires the NVIDIA driver**, the CUDA toolkit doesn't have to be installed. For the relationship between CUDA toolkit version, Driver version and GPU architecture, please refer to [nvidia-docker wiki](https://github.com/NVIDIA/nvidia-docker/wiki/CUDA).