As I have suspected, the numbers I got for execution time of the Haskell fibonacci program (look at my previous posts) are wrong, in the sense that I compiled the program without optimisation, as most normal users will do in real applications. That is why I feel that I should redeem myself and give the numbers for the program with optimisation turned on. So, when compiling the program using
ghc -O2 fib.hs -o fib -no-recomp (thanks to Don Stewart)
execution time is 0.64s (mean time of five runs). This time is much closer to the one reported on the Haskell blog (0.48s). Ok, so my hat goes off to Haskell---it really is faster than Python some 50 times.
But, being a Python fan, I couldn't help but feel that something is wrong here. Is Haskell really that good? It's fast, easy to parallelize, pure functional and it probably cooks for you after a hard day at work. So, why should I use Python?
Well, the first thing that comes to my mind is the fact that ghc generated a 925kB exe file from a 1kB file that computes fibonacci numbers. In comparison, gcc (3.4.2) generated 16 kB for a fibonacci program that ran 0.75s (compiled using -O2). While it is still impresive that Haskell was faster than C, I cannot help but think that it is just too much to have an exe file almost 1000 times larger than the source. While this is certainly a drawback of Haskell, it still wasn't enough to return my faith in Python. Then, another thing came to my mind---if Haskell can use optimisations, why can't Python? I mean, if I used -O2 in ghc, why can't I do somehting similar in Python?
Of course, running Python with -OO gave no real speedup---it shook off about one second in execution time. Instead of 26s, I got 25s for the non-parallel case, and instead of 18s, I got 17s for the non-parallel case. But, the great thing about Python are its packages. I remember a friend of mine telling me about a thing called Psyco. It was some kind of a package that optimised execution of Python code, so I decided to give it a shot. After downloading and installing Psyco (http://psyco.sourceforge.net/), I just added two lines to my source (I give the full source here):
from time import time
if n == 0 or n == 1:
return fib(n-1) + fib(n-2)
if __name__ == "__main__":
start_time = time()
for i in range(36):
print "n=%d => %d" % (i, fib(i))
print "Time elapsed: %f" % (time() - start_time)
So, the lines I added were import psyco, and psyco.full(). I ran this thing and voila---the time of execution was 1.93s (mean time of five runs). Wow! That was all I could think. Remember, this was the non-parallel case, so it went from 25 seconds to 1.9s. Or, in terms of Haskell speed, Haskell now beat Python by on 3x. And with no extra effort (ok, adding two lines to the source) and no parallelization.
Unfortunately, psyco didn't help the parallel version---it still took 18s. But still, I think this is pretty amazing and it definitely brought back faith in Python. So, it's three times slower, but the synatx is much cleaner and it doesn't generate a thousand times bigger executable. I'm sticking to Python :)
(Note: some parts of this post are biased and down right offensive to Haskell fans (just kidding about the last one:) ). My intention is not to start a flame war or anything like that, I just felt that someone should stand up and take Python's side:). Seriously though, if you have any objections on my methodology, I would like to hear from you.)