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There are various ways to install software onto the cluster, including:

• Via Conda Environments: See the Intro to Using Conda: Creating Python/R and other Application Environments workshop.

• Create and/or import Singularity images.

• Compiling/Building software with a variety compilers and make/cmake tools. While making use of the various scientific libraries we currently have installed.

• Installing Python/R packages, and similar packages for other languages.

Users are encouraged to install their required software within the project space, under a specific /project/<project-name>/software/ folder allowing the management and sharing of commonly used project based software. If ARCC assists any user/project with a software installation, this will be the location used unless somewhere else is explicitly requested.

Since this will use up project related storage space, the default project space has been increased to accommodate this.