System specific Builds

The UCVM software is used on a variety of computer platforms, from web-browsers to laptops to supercomputers. For overviews of the registered velocity models, the SCEC Community Model website may be easiest to use. For use on laptops, the UCVM Docker images may be easiest to use. For large-scale users, that want to query millions of data points, or build large-scale velocity meshes, users will want to build UCVM on a Linux servers or a supercomputers. UCVM has MPI libraries for building large velocity meshes in parallel.

On system that include MPI libraries, the UCVM installation script will detect the MPI libraries and will build the UCVM MPI utilities. If these MPI executables are built, they will be installed in the UCVM bin directory.

The following section describes details about building UCVM on specific Linux systems, and supercomputers.

== Generic Linux Distribution == Step-by-step algorithm for building UCVM is described in the create_ucvm_docker Dockerfile. The Dockerfile used for the current release build UCVM using a version of rocklinux:8.5, then loading libraries that include gcc, gcc-fortran, fftw-devel, and python38.

The UCVM Docker build process has an added complexity because it includes the UCVM plotting libraries. The core UCVM install script uses python3, but the UCVM plotting libraries still use python2. So the UCVM Dockerfile installs both versions of python, and it is configured so that python2 is the default version when the Docker image is run. This is because python3 is only required by the UCVM installation script, and python2 is required to run the plotting routines.

The UCVM MPI libraries are not built in the UCVM Docker images.

== Building on USC Discovery == UCVM is tested on the USC Discovery system. Discovery is Linux cluster that uses a module load system to manage the libraries available by application programs built and run on the system.