Get rid of ThreadsX?

[gdalle]

We can speed up loading of InferOpt by replacing ThreadsX with built-in threads:

res = ThreadsX.map(f(i) for i in 1:n)

would become

f1 = f(1)
res = Vector{typeof(f1)}(undef, n)
res[1] = f1
@threads for i in 2:n
    res[i] = f(i)
end

Downsides:

• less readable code
• performance hit due to the first element: complexity 1 + (n-1)/t instead of n/t for t threads

Upsides:

• less dependencies, faster loading of InferOpt
• improved type stability?

[gdalle]

Also beware that @threads sometimes introduces type instabilities due to boxing

https://github.com/JuliaLang/julia/issues/41731