Parallel Programming in Python: Multithreading and Multiprocessing

Material for the threading and multiprocessing in python workshop (Fall of 2018).

Objectives

Learning Outcomes for attendees of this workshop:

• Able to understand the differences between multithreading and multiprocessing.
• Know which tasks are better suited for multithreading or multiprocessing
• Able to use threading and multiprocessing packages for appropriately suited tasks.

Outline

• Overview:
  • Jupyter Lab IDE & Notebook Basics
  • Overview of parallel computing with python
• Threading:
  • c-extension thread enabled libraries (numpy & scipy)
  • threading package
• Multiprocessing:
  • Process class
  • Pool class
• Other parallel libraries:
  • pymp -- OpenMP-like functionality for Python