Performance tuning in Julia

Slow code can be written in any language

Julia concepts

put your code performance critical code into a function
type stability (@code_warntype is your friend)
only use const globals in performance critical code
benchmark your code: use @time (run twice to compile it) or better @btime from BenchmarkTools.jl
profile your code:
- https://docs.julialang.org/en/v1/manual/profile/#Profiling
- https://github.com/timholy/ProfileView.jl
before starting performance tuning, it's good to setup tests to make sure your code outputs the same

Use the $ trick with the @btime macro:

a = rand(5)
@btime sin.($a)

First and foremost: Performance Tips in the Julia documentation
Dirty trick: go on Julia Discourse and state that you ported code from Matlab/Python/R to Julia and it's now slower... (do use resources of other people very sparingly!)

Take your Game of Life code and improve its performance.

If you did not code a solution, take the one here