Why does Julia run a function faster than the non-function equivalent?

Question

So, today I decided to try Julia and I came across something odd I couldn't quite understand the reason for nor find a decent answer to with my search queries so here I am...

First, I wanted to have something to benchmark Python against, I settled for this very simple piece of code.

def test():            
    start = time()     
    a = 1              
    while a < 10000000:
        a+=1           
    print(time() - start)

This took ~0.9s to execute in Python 3.3 on my machine. Then I ran the following in Julia.

start = time()
a = 1
while a < 10000000
    a+=1
end
print(time() - start)

It took ~0.7s to execute. So I concluded that simple arithmetic performance in Julia is ~= to Python.

However, when I made it into a function, I stumbled upon the weirdness I wasn't expecting which turned my result on its head.

function test_arithmetic()
    start = time()
    a = 1
    while a < 10000000
        a+=1
    end
    print(time() - start)
end

test_arithmetic()

This codesnippet took only ~0.1s to execute, why is this?

Answer 1

The reason is that a global variable can have its type changed at any point, which makes it hard for the compiler to optimize. This is mentioned in the Performance Tips section of the manual.