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  • Easley User’s Guide
    • Introduction
    • Accessing Easley
    • Locations & Resources
    • Job Scheduling & Resource Allocation
    • Software
    • GPUs
    • Easley Cluster Training: Fundamentals
    • Programming Environments
      • R Programming Environment
      • Python on AU HPC Systems
      • Python Virtual Environments
      • Python Fundamentals Training
    • Python Fundamentals Training
    • Data Transfer
    • GPU Workloads
    • MPI Workloads
    • Containers and HPC
  • Easley Cluster Quick Start Guide
Auburn University HPC Documentation
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Programming Environments¶

  • R Programming Environment
    • Finding a Version
    • Creating a Custom Package Library
    • Automatically Load Custom Library Paths
    • Custom Build Settings
  • Python on AU HPC Systems
  • Python Virtual Environments
    • Python 3 with pip
      • Step 1: Get Home
      • Step 2: Set the Python Environment
      • Step 3: Create the Virtual Environment
      • Step 4: Activate the Virtual Environment
      • Step 5: Install Packages
    • Anaconda Python 3 with conda
      • Step 1: Housekeeping
      • Step 2: Load Anaconda
      • Step 3: Create a New Virtual Environment
      • Step 4: Activate the Environment
      • Step 5: Install Packages
      • Step 6: Exiting
  • Python Fundamentals Training
    • Introduction
    • Listing Available packages
    • Python or Anaconda?
    • Virtual Environments and installing packages locally
      • Python 3 with pip
      • Anaconda Python 3 with conda
    • Python Concurrency and Parallelism
      • Sample Code
    • Multithreading with Python
    • Multiprocessing with Python
    • Job Submission
    • Additional Services
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