numpy performance and random numbers

[Steven D'Aprano]

On Sat, 19 Dec 2009 02:05:17 -0800, Carl Johan Rehn wrote:

> Dear friends,
> 
> I plan to port a Monte Carlo engine from Matlab to Python. However, when
> I timed randn(N1, N2) in Python and compared it with Matlab's randn,

What's randn? I don't know that function. I know the randint, random, and 
randrange functions, but not randn. Where does it come from?


> Matlab came out as a clear winner with a speedup of 3-4 times. This was
> truly disappointing. I ran tthis test on a Win32 machine and without the
> Atlas library.
> 
> Why is there such a large difference in speed and how can I improve the
> speed of randn in Python! Any help with this matter is truly appreciated
> since I really would like to get away from Matlab and move over to
> Python instead.

Could be many reasons. Python could be generally slower than Matlab. Your 
timing code might have been faulty and you weren't comparing equal 
amounts of work (if your Python code was doing four times as much work as 
the Matlab code, then naturally it will be four times slower). Perhaps 
the Matlab random number generator is a low-quality generator which is 
fast but not very random. Python uses a very high quality RNG which is 
not cheap.

But does it really matter if the RNG is slower? Your Monte Carlo engine 
is a lot more than just a RNG. What matters is whether the engine as a 
whole is faster or slower, not whether one small component is slower.


-- 
Steven