07. Computational Complexity [HPC in Julia]

In this video we will briefly introduce some theory that helps us classify the resource requirements of our algorithms in a generic way. We discuss the idea of computational complexity, which is usually expressed as the "Big Oh" runtime / memory requirements of an algorithm. This video marks the first part of our week on optimisation, which will start with some theory and end with practical tips for making your code execute faster. This module was designed as an MPAGS (Midlands Physics Alliance Graduate School) module and aimed at postgraduates and early career researchers. Timecodes: 00:00:00 Introduction 00:00:55 Bubble Sort 00:05:44 Big O 00:08:26 Common Complexities 00:10:40 Example Big O Calculation 00:13:27 Quicksort 00:14:46 Performance Comparison 00:16:36 Outro Other videos on this topic: https://www.youtube.com/watch?v=Q_1M2JaijjQ https://www.youtube.com/watch?v=7NC-iyZ7vpQ Useful links: Git/GitHub for Researchers: https://www.youtube.com/watch?v=CuOmaUS1FnM Course Information Website: https://jamiemair.github.io/mpags-high-performance-computing/overview/ Julia Documentation: https://docs.julialang.org/en/v1/ MPAGS Registration: https://warwick.ac.uk/fac/sci/physics/mpags/registration/ Course Notes: https://jamiemair.co.uk/courses/hpc