One of the major advantages of
compass over Legacy COMPASS is that it
attempts to be aware of the capabilities of the machine it is running on. This
is a particular advantage for so-called “supported” machines with a config file
defined for them in the
compass package. But even for “unknown” machines,
it is not difficult to set a few config options in your user config file to
describe your machine. Then,
compass can use this data to make sure test
cases are configured in a way that is appropriate for your machine.
The config options typically defined for a machine are:
# The paths section describes paths that are used within the ocean core test # cases. [paths] # The root to a location where the mesh_database, initial_condition_database, # and bathymetry_database for MPAS-Ocean will be cached ocean_database_root = /usr/projects/regionalclimate/COMMON_MPAS/ocean/grids/ # The root to a location where the mesh_database and initial_condition_database # for MALI will be cached landice_database_root = /usr/projects/regionalclimate/COMMON_MPAS/mpas_standalonedata/mpas-albany-landice # the path to the base conda environment where compass environments have # been created compass_envs = /usr/projects/climate/SHARED_CLIMATE/compass/badger/base # Options related to deploying a compass conda environment on supported # machines [deploy] # the compiler set to use for system libraries and MPAS builds compiler = intel # the system MPI library to use for intel compiler mpi_intel = impi # the system MPI library to use for gnu compiler mpi_gnu = mvapich # the base path for spack environments used by compass spack = /usr/projects/climate/SHARED_CLIMATE/compass/badger/spack # whether to use the same modules for hdf5, netcdf-c, netcdf-fortran and # pnetcdf as E3SM (spack modules are used otherwise) use_e3sm_hdf5_netcdf = False
paths section provides local paths to the root of the “databases”
(local caches) of data files for each MPAS core. These are generally in a
shared location for the project to save space. Similarly,
is a location where shared conda environments will be created for
releases for users to share.
deploy section is used to help
compass create development and
release conda environments and activation scripts. It says which compiler set
is the default, which MPI library is the default for each supported compiler,
and where libraries built with system MPI will be placed.
Some config options come from a package, mache
that is a dependency of
mache is designed to detect and
provide a machine-specific configuration for E3SM supported machines. Typical
config options provided by
mache that are relevant to
# The parallel section describes options related to running jobs in parallel [parallel] # parallel system of execution: slurm, cobalt or single_node system = slurm # whether to use mpirun or srun to run a task parallel_executable = srun # cores per node on the machine cores_per_node = 36 # account for running diagnostics jobs account = e3sm # quality of service (default is the first) qos = regular, interactive
parallel section defined properties of the machine, to do with parallel
runs. Currently, machine files are defined for high-performance computing (HPC)
machines with multiple nodes. These machines all use Slurm job queueing to submit
parallel jobs. They also all use the
srun command to run individual
tasks within a job. The number of
cores_per_node vary between machines,
as does the account that typical
compass users will have access to on the
Slurm job queueing¶
Most HPC systems now use the slurm workload manager. Here are some basic commands:
salloc -N 1 -t 2:0:0 # interactive job (see machine specific versions below) sbatch script # submit a script squeue # show all jobs squeue -u <my_username> # show only your jobs scancel jobID # cancel a job
On each supported machine, users will be able to source a script to activate
the appropriate compass environment and compilers. Most machines support 2
compilers, each with one or more variants of MPI and the required NetCDF,
pNetCDF and SCORPIO libraries. These scripts will first load the conda
compass, then it will load modules and set environment
variables that will allow you to build and run the MPAS model.
A table with the full list of supported machines, compilers, MPI variants, and MPAS-model build commands is found in Supported Machines in the Developer’s Guide. In the links below, we list only the commands needed to use the default MPI variant for each compiler on each machine.
If you are working on an “unknown” machine, you will need to define some of the config options that would normally be in a machine’s config file yourself in your user config file:
[paths] # The root to a location where the mesh_database, initial_condition_database, # and bathymetry_database for MPAS-Ocean will be cached ocean_database_root = /home/xylar/data/mpas/mpas_standalonedata/mpas-ocean # The root to a location where the mesh_database and initial_condition_database # for MALI will be cached landice_database_root = /home/xylar/data/mpas/mpas_standalonedata/mpas-albany-landice # The parallel section describes options related to running tests in parallel [parallel] # parallel system of execution: slurm or single_node system = single_node # whether to use mpirun or srun to run the model parallel_executable = mpirun -host localhost # cores per node on the machine, detected automatically by default # cores_per_node = 4
The paths for the MPAS core “databases” can be any emtpy path to begin with.
If the path doesn’t exist,
compass will create it.
If you’re not working on an HPC machine, you will probably not have multiple
nodes or Slurm job queueing. You will probably install
MPICH or OpenMPI,
probably via a
In this case, the
To install the compass package into a conda environment, you will first need to install Miniconda3 (if miniconda is not already installed), then add the conda-forge channel:
conda config --add channels conda-forge conda config --set channel_priority strict
Then, you will run one of the following three commands, depending on how you would like to handle MPI support in the conda packages.
To create a conda environment called “compass” with MPI from the
conda create -n compass -c conda-forge -c e3sm/label/compass python=3.9 "compass=*=mpi_mpich*"
This is the recommended default for single-node Linux and OSX machines.
To create a conda environment called “compass” with MPI from the
conda create -n compass -c conda-forge -c e3sm/label/compass python=3.9 "compass=*=mpi_openmpi*"
No MPI from conda-forge¶
To create a conda environment called “compass” without any MPI package from conda-forge, run:
conda create -n compass -c conda-forge -c e3sm/label/compass python=3.9 "compass=*=nompi*"
This would be the starting point for working with
compass on an unknown
HPC machine. From there, you would also need to load modules and set
environment variables so that MPAS components can be built with system NetCDF,
pNetCDF and SCORPIO. This will likely require working with an MPAS developer.