1. Preliminary comments
  3. Core book
  4. 1. Chapter 1: High Performance Computing (HPC)
    1. 1.1. Introduction to Uninett Sigma2
    2. 1.2. Navigating in Sigma2
    3. 1.3. Job scripts
  6. 2. Chapter 2: Containers
    1. 2.1. Walk through Singularity
    2. 2.2. Using Singularity
  8. 3. Chapter 3: File management on HPC clusters
    1. 3.1. Copying files over to HPC clusters
    2. 3.2. Using filesystem
  10. 4. Chapter 4: Case study
    1. 4.1. Setting up the environment
    2. 4.2. Training model locally
    3. 4.3. Training model on SIGMA2
  12. 5. Chapter 5: Advanced topics
    1. 5.1. Parallelising the workflow
    2. 5.2. Ray tune
  14. 6. Aknowledgments
  16. Vocabulary
  17. 7. List of acronyns
  19. Appendix
  20. 8. Appendix A: list of referenced softwares & services

Documentation on using HPC and containers for Machine Learning