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# 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 `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:<TAG> -f Dockerfile
The `<TAG>` 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`.