This page contains a guide for building and using OpenIFS 48r1 at model version 48R1.1 in a linux based container using Docker.
While this page focuses on the containerised installation, the details presented can be used as a recipe for the underlying dependencies required to install and run OpenIFS 48r1 on a linux system.
Contents:
The first step is to make a directory from which the OpenIFS container can be created and cd
into that directory, e.g.
mkdir <openifs-docker-build-dir> cd <openifs-docker-build-dir> |
Once inside the <openifs-docker-build-dir>
clone or branch from the git repository with the OpenIFS release package, e.g.
git clone --single-branch --branch release ssh://git@git.ecmwf.int/oifs/openifs-48r1.1.git |
|
Once OpenIFS 48r1 has been extracted to your <openifs-docker-build-dir>
, then copy the Dockerfile
from the release to <openifs-docker-build-dir>
cp <openifs-docker-build-dir>/openifs-48r1.1/scripts/docker/gcc-docker-48r1.1/Dockerfile <openifs-docker-build-dir>/. |
This cp
step is important because the Dockerfile
and the OpenIFS release, i.e., openifs-48r1.1
, need to be in the same directory to build the container (see the openifs-48r1.1/scripts/docker/gcc-docker-48r1.1/Dockerfile
)
The following command builds the docker image
docker build --tag "openifs-48r1.1" . |
Note the trailing '.' to build in the current dir, which is required.
This command runs the build process for the OpenIFS image using gcc:11.2.0-bullseye as the base image, which is a debian Linux distribution with gcc 11.2 (at the time of writing, similar to the gcc on the ATOS). After downloading the image, the Dockerfile
installs the following software
apt install -y git && \ apt install -y cmake && \ apt install -y python3 python3-ruamel.yaml python3-yaml python3-venv && \ apt install -y libomp-dev && \ apt install -y libboost-dev libboost-date-time-dev libboost-filesystem-dev libboost-serialization-dev libboost-program-options-dev&& \ apt install -y netcdf-bin libnetcdf-dev libnetcdff-dev && \ apt install -y libatlas-base-dev && \ apt install -y liblapack-dev && \ apt install -y libeigen3-dev && \ apt install -y bison && \ apt install -y flex && \ apt install -y vim && \ apt install -y wget bc |
Once these packages are installed, open-mpi
is downloaded and built, the openifs
user is created and the openifs-48r1.1
directory is copied to the image.
On a Macbook pro (M1) the initial build of the container, takes about 5 minutes. If you decide to change the Dockerfile
following a build, you can just execute the same command and, depending on what you change, subsequent builds can be a lot quicker.
|
Once a build has completed, the image can be checked by typing docker images
, e.g.,
docker images REPOSITORY TAG IMAGE ID CREATED SIZE openifs-48r1.1 latest f72ea92f010f 5 hours ago 2.15GB |
And the container can be run using the following
docker run -it 'openifs-48r1.1' |
This command will open an interactive session in the new container, in which the entry directory is the openifs-48r1.1 directory, e.g.
docker run -it 'openifs-48r1.1' OpenIFS environment variables are: ------------------------------------------------------ OIFS_CYCLE=48r1 OIFS_DATA_DIR=/perm/openifs/oifs_data/48r1/48r1 OIFS_HOME=/home/openifs/openifs-48r1.1 OIFS_LOGFILE=/home/openifs/openifs-48r1.1/oifs_test_log.txt openifs@d1bd89ccc47f:~/openifs-48r1.1$ ls CHANGES COPYING NOTICE arch ifs-source oifs-config.edit_me.sh scripts CITE LICENSE README bundle.yml ifs-test openifs-bundle |
|
Once inside the container, the openifs-test.sh
script can be run, e.g.,
openifs@d1bd89ccc47f:~/openifs-48r1.1$ ./scripts/openifs-test.sh -cbt -s docker |
where :
-c
will clean the directory (not necessary for a fresh image or new container)
-b
will configure the bundle and build OpenIFS, i.e.,
$OIFS_HOME/build/bin
.$OIFS_HOME/build/bin
.-t will run the ifs-test
-s docker
defines the system as docker, which makes the script use the correct build commands
On a Macbook pro (M1) the build of OpenIFS, takes about 10 minutes, while successful completion of ifstest takes just over 3 minutes.
exit
from the active container. Once exited all data and changes made within the container will be lost. Hence, if necessary, it is important todocker cp
Executing docker run
will always create a new container, hence we recommend