Looking for code to solve (surely common) 'embarrassing parallelism' multithreading use-case

General Usage Performance
,
10

yes, I see you are right!

using .Threads, BenchmarkTools

# a silly function taking some time, returning its thread
f(n) = (sum((i for i in 1:n) .^ 2); threadid())

function show_load(threads)
    res = fill("", nthreads())
    foreach(i->res[i]*="*", threads)
    res
end

then

julia> @btime f(2_000)
  1.174 μs (2 allocations: 31.50 KiB)
1

julia> fetch.(map((_->Threads.@spawn f(2000)), 1:nthreads()))
8-element Array{Int64,1}:
 3
 2
 4
 5
 6
 7
 8
 1

If we put the same load on all tasks, all threads are employed. Even with unbalanced load (if M >> N | M: number of tasks, N: nthreads) the balance is quite good:

julia> show_load(fetch.(map(_->(Threads.@spawn f(rand(1:2000))), 1:500)))
8-element Array{String,1}:
 "****************************************************"
 "****************************************************************************************"
 "**************************************************************************"
 "*********************************"
 "********************************************************"
 "***********************************************************"
 "***********************************************************************"
 "*******************************************************************"

I first had an other impression because in my applications/tasks usually I read first from a channel. In that case the load is very imbalanced:

g(n) = (yield(); f(n))

julia> show_load(fetch.(map(_->(Threads.@spawn g(rand(1:2000))), 1:500)))
8-element Array{String,1}:
 "*"
 "*************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************************"
 "*"
 "*"
 "*"
 "*"
 "*"
 "*"
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