tree: 6cd67c997583e796a85a2225f4030f4bd1460b9c [path history] [tgz]
  1. devel/
  2. runtime/

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:1.2.0-cpu-devel-ubuntu18.04 
# or
docker pull apache/singa:1.2.0-cuda10.0-cudnn7.4.2-devel-ubuntu18.04

For more versions see [here](

Run the docker container using

docker run -it apache/singa:1.2.0-cpu-devel-ubuntu18.04 /bin/bash
# or
nvidia-docker run -it apache/singa:1.2.0-cuda10.0-cudnn7.4.2-devel-ubuntu18.04 /bin/bash

The latest SINGA code is under the singa folder.

Warning The code will be under root/singa for 1.2.0-cpu-devel-ubuntu18.04.

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 apache/singa:<TAG> -f Dockerfile

The <TAG> is named as

  • VERSION: e.g., 3.0.0
  • 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.