# Docker Images ## Available tags * `devel`, with SINGA and the development packages installed on Ubuntu16.04 (no GPU) * `devel-cuda`, with SINGA, CUDA8.0, CUDNN5, and other development packages installed on Ubuntu16.04 ## Use the existing Docker images Users can pull the Docker images from Dockerhub via docker pull apache/singa:devel # or docker pull apache/singa:devel-cuda Run the docker container using docker run -it apache/singa:devel /bin/bash # or docker run -it apache/singa:devel-cuda /bin/bash The latest SINGA code is under the `incubator-singa` folder. ## Create new Docker images from Dockerfile New Docker images could be created by executing the following command within the Dockerfile folder, e.g., tool/docker/devel/ docker build -t singa: -f Dockerfile The `` is named as devel|runtime[-CUDA|CPU][-CUDNN] * devel: development images with all dependent libs' header files installed and SINGA's source code; runtime: the minimal images which can run SINGA programs. * CUDA: cuda10.0, cuda9.0 * CUDNN: cudnn7 Here are some example tags: `devel-cuda9-cudnn7`, `devel-cuda9-cudnn7`, `devel-cuda10-cudnn7`, `devel-cpu`, `runtime-gpu` and `runtime-cpu` Please follow the existing Dockefiles under tool/docker/ to create other Dockefiles. The folder structure is like level1: devel|runtime level2: Dockerfile, OS level3: Dockerfile, CUDA|MKLDNN For example, the path of the Dockerfile for `devel-cuda9-cudnn7` is `tool/docker/devel/ubuntu/cuda9/Dockerfile`.