Docker container for CESM compset B1850 resolution f09_g17
CESM docker container for F1850 compset and resolution f09_g17 using bioconda cesm docker as a base image.
- Input dataset is stored and available in zenodo.
You need to pass parallel_studio_xe_2018_update1_cluster_edition.tgz
for being able to compile with intel compilers.
We are using a trial license for this test (see silent.cfg
). However, you should update silent.cfg
to pass a proper license for running on your platform.
- Intel compilers:
wget http://registrationcenter-download.intel.com/akdlm/irc_nas/tec/12374/parallel_studio_xe_2018_update1_cluster_edition.tgz
- First clone this repository:
git clone https://github.com/NordicESMhub/B1850_docker_intel.git
-
Then make sure you move
parallel_studio_xe_2018_update1_cluster_edition.tgz
inB1850_docker_intel
folder as it will be used for building the container. -
Then build the container:
docker build -t nordicesmhub/cesm_b1850:intel .
Make sure inputdata is available (it won't download it as we suppose it is already on disk).
- The location of the inputdata is
/opt/uio/inputdata
mkdir /opt/uio
wget https://zenodo.org/record/3526181/files/inputdata_B1850.tar.gz
tar zxf inputdata_B1850.tar.gz
mv inputdata_container inputdata
- Model outputs are stored in
/opt/uio/archive
along with thecase
folder (it can be interesting to check timing).
docker run -i -v /opt/uio/inputdata:/home/cesm/inputdata -v /opt/uio/archive:/home/cesm/archive -t nordicesmhub/cesm_b1850:intel
Once you start your container, use run_b1850
or any available sub-cases (run_b1850case1
to run_b1850_case6
), depending on the number of processors you wish to use.
Update CESM_PES
in run_b1850
to change the number of processors per node. We ran this test on [PiZ-Dain] on GPU partitions (12 processors per node).