Number of threads available seems random (using @spawn)

New to Julia
14

Try this:

julia> using Threads; using Future: randjump

julia> const RNGS = [randjump(MersenneTwister(),big(10)^20)]; foreach(_ -> push!(RNGS, randjump(last(RNGS),big(10)^20)), 2:Threads.nthreads())

julia> function f3()
         s = 0.
         RNG = RNGS[Threads.threadid()]
         for i in 1:10^8
           s += rand(RNG)
         end
         return s
       end
 f3 (generic function with 1 method)

This is what I get:

f0: rand()
  286.134 ms (112 allocations: 9.22 KiB)
f1: RNG inside f
  131.979 ms (238 allocations: 359.38 KiB)
f2: using const RNG = ...
  9.223 s (111 allocations: 9.19 KiB)
f3: using const RNGS = ...
  132.231 ms (111 allocations: 9.19 KiB)

The cost of creating the MersenneTwister is amortized over the long 10^8 iterations. f3 should be the fastest with fewer iterations.
Using 10^3 iterations instead, I get this:

f0: rand()
  22.492 μs (110 allocations: 9.16 KiB)
f1: RNG inside f
  27.087 μs (236 allocations: 359.31 KiB)
f2: using const RNG = ...
  78.150 μs (108 allocations: 9.09 KiB)
f3: using const RNGS = ...
  21.343 μs (110 allocations: 9.16 KiB)
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