Codes produced for research purposes will sometimes be expected to perform complex or extensive tasks which can require a lot of time to run. Profiling a piece of code allows us to identify why a code takes a long time to run and optimisation allows us to reduce this running time. 

This course discusses the role of profiling and optimisation in the software development cycle and encourages students to consider when and where profiling and optimisation are appropriate for a project. Profiling tools relating to both run-time and memory are introduced, and various optimisation strategies are demonstrated. The course will conclude with asking students to profile and optimise a piece of sample code.

Syllabus:

• What are profiling and optimisation?
• What are the costs and benefits of profiling and optimisation?
• When are profiling and optimisation justified in the software development cycle?
• Profiling tools available in Python
• Optimisation strategies in Python

The course will be delivered through a combination of slides, discussions, demonstrations and hands on practicals.

Learning Outcomes:

After completing this workshop, you will be better able to:

• Determine when profiling and optimisation is appropriate for a project
• Use selected profilers to examine the impact of sections of code on run-time and the memory usage
• Utilise profiler outputs to identify problematic areas of code
• Apply common optimisation techniques to improve code performance
  
  

Dates & Booking Information

There are no further sessions taking place this academic year. Course dates for 2024-25 will be available to book from late September.

To book your place, please follow the booking process advertised on the main programme page