In this intermediate-level Julia Programming Language coding tutorial, you'll learn about Julia's Performance Tips and Tools to help you convert your code into high-performance code.
You'll learn how to use the @time macro to measure your code's performance and you'll learn how to use Julia's profiler, both in the REPL and in VS Code.
Series Prerequisites:
Basic knowledge about coding with the Julia Programming Language is required.
Students should also know how to perform basic data analysis and data visualization using Julia.
Students should also be comfortable using Julia in VS Code and Pluto notebooks.
00:00 Intro
00:32 Overview
01:48 AXPY1: Write Naive Code
07:01 AXPY2: Wrap Code in Function
09:54 AXPY3: Use Arithmetic Operators
13:58 AXPY4: Use Broadcasting
16:16 AXPY5: Use Broadcasting + 32-bit Numbers
18:41 AXPY6: Use LinearAlgebra.axpy!() + 32-bit Numbers
22:40 Profiling
31:41 Recap
33:44 Outro
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# Links for this tutorial
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# Code for this tutorial (GitHub):
https://github.com/julia4ta/tutorials/tree/master/Series%2008/Tutorial%2008x02
# Julia Documentation -- Performance Tips
https://docs.julialang.org/en/v1/manual/performance-tips/
# Julia Documentation -- Profiling
https://docs.julialang.org/en/v1/manual/profile/
# Julia in VS Code - What's New | David Anthoff, Sebastian Pfitzner | JuliaCon 2022. July 27, 2022. (YouTube video)
https://youtu.be/Okn_HKihWn8
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# Links for this series
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# Link to Series 8 Playlist [Intro to Scientific Computing in Julia]
https://www.youtube.com/watch?v=_iQr9lNCTpY&list=PLhQ2JMBcfAsjQzwp2j97uZjNOMi7Ed4CG
# The Julia Programming Language
https://julialang.org/
https://docs.julialang.org/en/v1/
https://www.youtube.com/@TheJuliaLanguage
# VS Code
https://code.visualstudio.com/
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