Embedded Files
Research Computing Software
Research Computing Software
The Research Computing (RC) computational systems host a wide variety of software for diverse academic research use and provide compilers and ample storage in home directories so users can install their own software.
For many research packages and libraries RC provides the Spack tool for building many science and math systems in user space. Spack is written and supported at Lawrence Livermore National Lab and provides access to hundreds of packages developed at national labs and universities. See the Spack docs and Spack below for more info. See spack for using Spack in the RC compute environment.
If there is a package or library that is not listed below, please submit an issue here.
The following is a (non-exhaustive) list of the software available on our Linux Systems and usage guides.
For complete listings of installations, log in to the cluster and use module avail to view all possible environment modules.
Any software packages that are strikeout have not been migrated to the new Rocky OS, or are deprecated. Submit a help request if you need one of these packages.
Application Software
Application Software
General
Genomics and Bioinformatics
GIS and Spatial
Machine and Deep Learning
Modelling Software
Delft3D-FM 2017 and 2020
Chemistry Software
Math Software
Computational Fluid Dynamics (CFD)
Environment Tutorials
Environment Tutorials
Utilities
Utilities
General
These are primarily used as dependencies for other software, but they can be used by users as well.
Data Transfer
Globus (for large scale data transfers across systems)
FAQ
FAQ
Keeping up to date: Compilers and Interpreters
Keeping up to date: Compilers and Interpreters
We have the latest major versions of GCC, Intel's compilter suite, Python, and R.
What's the difference between a compiler and an interpreter?
What's the difference between a compiler and an interpreter?
In short, a compiler takes a program and builds an executable which can then be ran, whereas an interpreter takes a program and runs it immediately.
What can be installed to the RC systems?
What can be installed to the RC systems?
The software will need to be compatible with Linux (CentOS in particular). The RC team will happily spend four work hours on an installation, but if it takes longer than that, we will explore in more detail t the installation and review the installation. By default, we highly recommend you make a request and work with us to get something installed.
Which version should be used? What build with several compilers should be used?
Which version should be used? What build with several compilers should be used?
The RC systems may contain many different versions of various software installations. The primary reason behind keeping all the old versions is because some applications cannot or do not update to the most recent version, so the modules are kept for legacy support. Additionally, there may be bugs in the current stable release that cause it to be undesirable for some. In general, it is best to use the most recent major release, unless some software requires a different version.
If there are builds of a software with different compilers, it is generally better to use the GCC build, unless there is a reason to be using Intel's compiler suite.
If there are builds with MPI libraries, use those on the clusters if MPI is desired.
If there is a package for a module that has several versions (such as Python or Miniconda), which will it be installed to?
If there is a package for a module that has several versions (such as Python or Miniconda), which will it be installed to?
Any packages installed to Python or Miniconda or similar modules will have the package installed to the two latest versions for each compiler (GCC or Intel's compiler suite) used.
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