On a high-performance computing system, it is seldom the case that the software we want to use is available when we log in. It is installed, but we will need to “load” it before it can run.
Before we start using individual software packages, however, we should understand the reasoning behind this approach. The three biggest factors are:
- software incompatibilities
Software incompatibility is a major headache for programmers. Sometimes the presence (or absence) of a software package will break others that depend on it. Two of the most famous examples are Python 2 and 3 and C compiler versions. Python 3 famously provides a
python command that conflicts with that provided by Python 2. Software compiled against a newer version of the C libraries and then used when they are not present will result in a nasty
'GLIBCXX_3.4.20' not found error, for instance.
Software versioning is another common issue. A team might depend on a certain package version for their research project – if the software version was to change (for instance, if a package was updated), it might affect their results. Having access to multiple software versions allow a set of researchers to prevent software versioning issues from affecting their results.
Dependencies are where a particular software package (or even a particular version) depends on having access to another software package (or even a particular version of another software package).
Environment modules are the solution to these problems. A module is a self-contained description of a software package – it contains the settings required to run a software package and, usually, encodes required dependencies on other software packages.
Software in Zorba is categorized into two groups:
- bioSW: includes all software tools targeted for bioinformatics analyses, and
- envSW: includes system software tools, such as compilers, interpreters, programming/scripting languages and other parallelization frameworks.