[julia-users] dispatch slowdown when iterating over array with abstract values

[Tim Wheeler]

Hello Julia Users.

I ran into a weird slowdown issue and reproduced a minimal working example. 
Maybe someone can help shed some light.

abstract Feature

type A <: Feature end
evaluate(f::A) = 1.0

type B <: Feature end
evaluate(f::B) = 0.0

function slow(features::Vector{Feature})
    retval = 0.0
    for i in 1 : length(features)
        retval += evaluate(features[i])
    end
    retval
end

function fast(features::Vector{Feature})
    retval = 0.0
    for i in 1 : length(features)
        if isa(features[i], A)
            retval += evaluate(features[i]::A)
        else
            retval += evaluate(features[i]::B)
        end
    end
    retval
end

using ProfileView

features = Feature[]
for i in 1 : 10000
    push!(features, A())
end

slow(features)
@time slow(features)
fast(features)
@time fast(features)

The output is:

0.000136 seconds (10.15 k allocations: 166.417 KB)
0.000012 seconds (5 allocations: 176 bytes)


This is a HUGE difference! Am I missing something big? Is there a good way to 
inspect code to figure out where I am going wrong?


Thank you in advance for any guidance.


-Tim