In this article we explain how to use OpenIFS 43r3 in a container environment. At present this has been tested in two different ways using Docker on a Linux workstation:

1. The user works interactively from inside the container and the external experiment directory is mounted as a sub-directory inside the container environment. Depending on the set up the user can either have access to the entire OpenIFS installation or the user may be prevented from accessing the source code. 
    
2. The user works from the experiment directory, and instead of running the model binary the OpenIFS run script starts up a container environment wherein the experiment runs in isolation. Immediately after the experiment has completed the container is removed. 

Motivation

Setting up the computing environment (libraries, directory structure, etc) required by OpenIFS can present a challenge when it is necessary to run the model on different hardware infrastructure, for instance during workshops and training events. It is time consuming to install the model and all its required software packages, and the libraries that are available on the local system may not be compatible with the model requirements. Many of these issues can be avoided by running a containerised version of the model which is a self-sufficient code package that can be used in a consistent way on different hardware platforms. The computational overhead of the container environment itself is often outweighed by the local availability and direct access to all required libraries within the container.

We have used the Docker platform to produce a container image for OpenIFS. This requires the design of a "Dockerfile" which describes the build process for the model code and all its dependent libraries, and which results in a binary Docker image. This image can be uploaded onto other computers that make use of the Docker platform or which use other compatible software. A “container” is the running instance of the Docker image. Pre-compiled OpenIFS Docker images will be stored in a cloud repository from which they can be downloaded and run on the local computer hardware without the need to install and compile any software.