Raw speed. Although julia has several nice features (multiple dynamic dispatch, ...

stabbles · on Aug 9, 2018

You don't even need to annotate things with types!

    > square(x) = x * x

    > @code_typed square(2.0)
    CodeInfo(
    1 1 ─ %1 = Base.mul_float(%%x, %%x)::Float64
    └──        return %1
    ) => Float64

    > @code_typed square(2)
    CodeInfo(
    1 1 ─ %1 = Base.mul_int(%%x, %%x)::Int64
    └──        return %1
    ) => Int64

Functions specialize automatically to the arguments you pass in.

ChrisFoster · on Aug 9, 2018

Or, to see what's really going on at a low level you have immediate access to the native assembly from the REPL:

    julia> square(x) = x^2 
    square (generic function with 1 method) 
 
    julia> @code_native square(1) 
        .text 
    Filename: REPL[3] 
        pushq       %rbp 
        movq        %rsp, %rbp 
    Source line: 1 
        imulq       %rdi, %rdi 
        movq        %rdi, %rax 
        popq        %rbp 
        retq 
 
    julia> @code_native square(1.0) 
        .text 
    Filename: REPL[3] 
        pushq       %rbp 
        movq        %rsp, %rbp 
    Source line: 1 
        mulsd       %xmm0, %xmm0 
        popq        %rbp 
        retq

DNF2 · on Aug 9, 2018

You don't need to annotate function definitions with types, but you should actually annotate your composite type definitions with concrete (parametric) types for each field.

oxinabox · on Aug 9, 2018

Syntax, semantics (multiple dispatch, type system), and community (so many clever people working together sharing expertise)

ChrisRackauckas · on Aug 9, 2018

You don't need to annotate types to get the speed.