Performance penalty using anonymous function in Julia

Question

I have noticed that there is a performance penalty associated with using anonymous functions in Julia. To illustrate I have two implementations of quicksort (taken from the micro performance benchmarks in the Julia distribution). The first sorts in ascending order

function qsort!(a,lo,hi)
    i, j = lo, hi
    while i < hi
        pivot = a[(lo+hi)>>>1]
        while i <= j
            while a[i] < pivot; i += 1; end
            while pivot < a[j]; j -= 1; end
            if i <= j
                a[i], a[j] = a[j], a[i]
                i, j = i+1, j-1
            end
        end
        if lo < j; qsort!(a,lo,j); end
        lo, j = i, hi
    end
    return a
end

The second takes an additional parameter: an anonymous function that can be used to specify ascending or descending sort, or comparison for more exotic types

function qsort_generic!(a,lo,hi,op=(x,y)->x<y)
    i, j = lo, hi
    while i < hi
        pivot = a[(lo+hi)>>>1]
        while i <= j
            while op(a[i], pivot); i += 1; end
            while op(pivot, a[j]); j -= 1; end
            if i <= j
                a[i], a[j] = a[j], a[i]
                i, j = i+1, j-1
            end
        end
        if lo < j; qsort_generic!(a,lo,j,op); end
        lo, j = i, hi
    end
    return a
end

There is a significant performance penalty when sorting Arrays of Int64, with the default version an order of magnitude faster. Here are times for sorting arrays of length N in seconds:

N       qsort_generic   qsort
2048    0.00125         0.00018
4096    0.00278         0.00029
8192    0.00615         0.00061
16384   0.01184         0.00119
32768   0.04482         0.00247
65536   0.07773         0.00490

The question is: Is this due to limitations in the compiler that will be ironed out in time, or is there an idiomatic way to pass functors/anonymous functions that should be used in cases like this?

update From the answers it looks like this is something that will be fixed up in the compiler.

In the mean time, there were two suggested work arounds. Both approaches are fairly straightforward, though they do start to feel like the sort of jiggery-pokery that you have to use in C++ (though not on the same scale of awkward).

The first is the FastAnon package suggested by @Toivo Henningsson. I didn't try this approach, but it looks good.

I tried out the second method suggested by @simonstar, which gave me equivalent performance to the non-generic qsort! implementation:

abstract OrderingOp
immutable AscendingOp<:OrderingOp end
immutable DescendingOp<:OrderingOp end
evaluate(::AscendingOp, x, y) = x<y
evaluate(::DescendingOp, x, y) = x>y

function qsort_generic!(a,lo,hi,op=AscendingOp())
    i, j = lo, hi
    while i < hi
        pivot = a[(lo+hi)>>>1]
        while i <= j
            while evaluate(op, a[i], pivot); i += 1; end
            while evaluate(op, pivot, a[j]); j -= 1; end
            if i <= j
                a[i], a[j] = a[j], a[i]
                i, j = i+1, j-1
            end
        end
        if lo < j; qsort_generic!(a,lo,j,op); end
        lo, j = i, hi
    end
    return a
end

Thanks everyone for the help.

Answer 1

It's a problem and will be fixed with an upcoming type system overhaul.

Update: This has now been fixed in the 0.5 version of Julia.