Software

Last updated March 06, 2024

Table of Contents

0.0.1 Software Module System
0.0.2 Using Conda
0.0.3 Installing Jupyter Kernels
0.0.4 Using Singularity
0.0.5 Building Software with CMake
0.0.6 Using Git
0.0.7 Using Tmux
0.0.8 Using Launcher

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.

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.