Julia benchmark from slack

bm.jl

using Random: rand!
using LoopVectorization: @turbo

function test_fct(vec_, r1, r2)
    xx = vec_
    rand!(r1)
    rand!(r2)
    for j in 1:11
        @turbo for i in eachindex(xx, r1, r2)
            xx[i] = xx[i] < r1[i] ? r2[i] : xx[i]
        end
    end
    return xx
end

function sim_test(vec_, L::Int)
    xx = vec_
    r1 = Vector{Float32}(undef, L)
    r2 = similar(r1)
    for i in 1:250
        xx = test_fct(vec_, r1, r2)
    end
    return xx
end

function main(L=500_000)
    test_vect = Vector{Float32}(undef, L)
    rand!(test_vect)
    sim_test(test_vect, L)
end

#=
julia> @benchmark main()
BenchmarkTools.Trial: 23 samples with 1 evaluation.
 Range (min … max):  210.521 ms … 228.047 ms  ┊ GC (min … max): 0.00% … 0.00%
 Time  (median):     219.803 ms               ┊ GC (median):    0.00%
 Time  (mean ± σ):   220.048 ms ±   3.735 ms  ┊ GC (mean ± σ):  0.03% ± 0.13%

  ▁            ▁       ▁ █  ▁ ▁▁▁██▁ ▁   ▁█▁▁        ▁ ▁      ▁
  █▁▁▁▁▁▁▁▁▁▁▁▁█▁▁▁▁▁▁▁█▁█▁▁█▁██████▁█▁▁▁████▁▁▁▁▁▁▁▁█▁█▁▁▁▁▁▁█ ▁
  211 ms           Histogram: frequency by time          228 ms <

 Memory estimate: 5.72 MiB, allocs estimate: 6.

shell> head /proc/cpuinfo
processor       : 0
vendor_id       : AuthenticAMD
cpu family      : 23
model           : 113
model name      : AMD Ryzen 7 3700X 8-Core Processor
stepping        : 0
microcode       : 0x8701013
cpu MHz         : 3594.207
cache size      : 512 KB
physical id     : 0
=#