Last updated March 06, 2024

These guides provide an overview on common software and their use in high-performance computing.

0.0.1 Software Module System

Learn how to use CARC’s software module system based on Lmod.

0.0.2 Using Conda

Conda is a package and environment manager primarily used for open-source data science packages for the Python and R programming languages.

0.0.3 Installing Jupyter Kernels

Instructions for installing Jupyter kernels when using JupyterLab via CARC OnDemand.

0.0.4 Using Singularity

Singularity is an open-source application for creating and running software containers, designed primarily for high-performance computing on shared Linux-based computing clusters like CARC systems.

0.0.5 Building Software with CMake

Instructions for installing and using CMake, a cross-platform build system.

0.0.6 Using Git

Git is an open-source version control system primarily used for software development.

0.0.7 Using Tmux

Tmux is a terminal multiplexer enabling a number of terminals to be created, accessed, and controlled from a single screen.

0.0.8 Using Launcher

Launcher is a utility for performing simple, data parallel, high-throughput computing (HTC) workflows on clusters, massively parallel processor (MPP) systems, work-groups of computers, and personal machines.