Evaluator GUI Now Dockerized
Our evaluator can help researchers to quickly, conveniently, and thoroughly analyze the data obtained from experiments with optimization or machine learning algorithms. Our software is a Java 7 software which requires a LaTeX installation (such as TeX Live or MiKTeX), ideally including XeLaTeX and LuaTeX, Ghostscript, and R with several Machine Learning packages. This means that installing this software in a fully functional way may be cumbersome. This problem has now been solved for our Linux users (and probably the Mac users as well, but I am not sure).
The system is now “dockerized”!
Docker is an application that allows you to define, publish, and run containers. Containers are something like lightweight VMs, they live as normal processes on the same kernel as the OS under Linux and as small Virtual Box VMs under Windows and Mac OS. Docker can be installed following the guidelines below:
- for Linux, you can run
curl -fsSL https://get.docker.com/ | shon your command line and everything is done automatically (if you have
curlinstalled, which is normally the case),
- for Windows
- for Mac OS
After doing this, you can start our container by typing the following command into a normal terminal (Linux), the Docker Quickstart Terminal (Mac OS), or the Docker Toolbox Terminal (Windows):
docker run -t -d -p 9999:8080/tcp optimizationbenchmarking/evaluator-gui
The first time you run the program, this will download the software once (and only once). Once the container is started, you can access it with your browser at address
- http://localhost:9999 under Linux or
http://<dockerIP>:9999under Windows and Mac OS, where
dockerIPis the IP address of your Docker container. This address is displayed when you run the container. You can also obtain it with the command
docker-machine ip default.
The container contains a full installation of my system, including the
Java 8 OpenJDK,
R, the needed
R packages, and
ghostscript. No further setup is needed. It is thus about 600 MB in size.
If you want to uninstall the software image afterwards, use
docker rmi -f optimizationbenchmarking/evaluator-gui
I hope that this makes it much easier to use our software.