Often, especially in performance-critical code, we want to squeeze the maximum speed out of Julia. If you are working with arrays, the @inbounds macro can be used to significantly reduce access time to the elements. The drawback is that you have to be sure that you are not trying to access an out-of-bounds location.
Inspect the inbounds.jl file that contains the following contents:
using BenchmarkTools
mode = ["normal", "@inbounds"]
i = 0
for inbounds in ["", "@inbounds"]
global i += 1
eval(Meta.parse("""function f$i(x::AbstractArray{<:Real})
y = 0
$inbounds for i in eachindex(x)
y += x[i] > 0.5
end
y
end"""))
end
x = rand(10^7)
for (idx, f) in enumerate([f1, f2])
println("\n", mode[idx])
@btime $f($x)
end