LARCC User Documentation

• Accounts and Support
  • Request an account
    • Accounts for UofL individuals
  • UofL VPN Connection
  • Request Support (Tickets)
• Getting Started
  • Usage Agreement
  • HPC system overview
    • About the cluster
    • About Scientific Software
    • About Jobs
  • Quickstart
    • Logging into the cluster
    • Copying files to/from the cluster
    • Using software installed in the cluster
    • Queues and jobs
  • Policies
    • Installing packages system-wide
    • Running applications on the login nodes
    • Resource restrictions
• Guides
  • HPC System Guide
    • Introduction
    • Connecting to the Cluster
    • Understanding Filesystems
  • Slurm Queueing System Guide
    • Basic Slurm Terminology
    • Job Types and Job Submission
    • Job Environment
    • Strategies When Submitting Slurm Jobs
  • Storage Guide
    • Understanding Storage on Compute Nodes
    • Recommended Workflow
• Software
  • Conda (Anaconda/Miniconda/Miniforge)
    • Basics
    • Using Conda
    • Conda in a batch job
    • Conda in an interactive job
  • Gaussian
    • Running Gaussian
  • Jupyter
    • Launching Jupyter through a batch job
    • Launching Jupyter through an interactive job
    • Transitioning from Jupyter to Python Script
  • MATLAB
    • Basics
    • Submitting a batch job
    • Creating a cluster profile for LARCC
  • LAMMPS
    • Running LAMMPS
    • Building LAMMPS
  • LIGGGHTS
    • Running LIGGHTS
  • PyTorch
    • Verifying GPU Availability
    • Using GPUs in PyTorch
    • Multi-GPU Usage in PyTorch
  • R
    • Using R
    • Installing R Packages
    • Installing R packages in custom locations
    • Installing R Packages with External Library Dependencies
    • Using the pak Package Manager
  • RStudio
    • Pre-launch
    • Launch RStudio Server
  • Tensorflow
    • Verifying GPU Availability
    • Single Node, Multi-GPU Training
  • VASP
    • License Restrictions
    • Running VASP
• AI Use Cases
  • Pneumonia detection based on Chest X-Ray
    • 1. Ingesting the data
    • 2. Training the models
    • 3. Visualize Metrics
    • 4. Save your results for further analyses
  • Med-BERT