Software Management on REPACSS¶
This section covers all aspects of software management on REPACSS, organized by package management approach and use case.
🎯 Software Management Categories¶
1. HPC Applications & System Software → Spack + Module System¶
System-provided software - Users simply load what they need.
For HPC applications, compilers, libraries, and system-level software managed through Spack and loaded via the Lmod environment module system. No installation required - just load the modules you need.
Start here: Module System
2. Data Science Applications → Conda/MiniForge¶
User-installed software - Users install locally, then add packages.
For Python/R-based data science, machine learning, and scientific computing packages using MiniForge (conda) environments. Requires local installation of MiniForge, then install packages like Jupyter Notebook for interactive development.
Start here: Getting Started with MiniForge
3. User Self-Installed Software → Custom Solutions¶
User-installed software - Users install their own software using:
3.1 Containers (Apptainer) → Pre-built Binaries¶
For pre-built applications, complex software stacks, and reproducible environments. Examples include Ollama for AI applications.
Start here: Using Containers
3.2 Building from Source → Custom Compilation¶
For software that needs to be compiled from source code with specific configurations.
Start here: Building from Source
🚀 Popular User Applications¶
Commonly Used Software → User-Installed Applications¶
Popular applications that users frequently install and use, demonstrating how to use the package management methods above:
- Running Jupyter Notebook - Using conda (category 2) for interactive development
- Running Ollama - Using containers (category 3.1) for AI applications
📋 Quick Reference¶
| Category | Installation Type | Use Case | Solution | Documentation |
|---|---|---|---|---|
| HPC Applications | System-provided | Compilers, MPI, scientific libraries | Module system | Module System |
| Data Science | User-installed | Python/R packages, ML frameworks | MiniForge (conda) | Getting Started with MiniForge |
| Pre-built Applications | User-installed | Complex software stacks | Apptainer containers | Using Containers |
| Custom Software | User-installed | Source compilation, specialized tools | Build from source | Building from Source |
Popular User Applications¶
| Application | Package Management Method | Installation Type | Documentation |
|---|---|---|---|
| Jupyter Notebook | Conda (Data Science) | User-installed | Running Jupyter Notebook |
| Ollama | Containers (User Self-Install) | User-installed | Running Ollama |
🚀 Getting Started¶
- HPC applications? Check available modules:
module avail(system-provided) - Data science work? Set up MiniForge: See Getting Started with MiniForge (user-installed)
- Custom software? Choose containers or source build based on your needs (user-installed)
- Want popular applications? See commonly used software: Popular User Applications
📚 Documentation Structure¶
Package Management Methods¶
- Module System - System-provided HPC applications via Spack + Lmod
- Getting Started with MiniForge - User-installed data science with conda
- Using Containers - User-installed Apptainer/Singularity containers
- Building from Source - User-installed source compilation
Popular User Applications¶
- Running Jupyter Notebook - Using conda for interactive development
- Running Ollama - Using containers for AI applications
🆘 Need Help?¶
For software-related issues or to request new software installations, contact:
repacss.support@ttu.edu