Speed Optimization on Fix Matrix Looping

[Ben Abbott]

On May 4, 2008, at 2:31 PM, lain.ux wrote:

> Hi,
>
> I have tried to run my octave code with following two test cases and
> gotten the elapsed time. As the result, test case 2 is executed much
> faster than case 1.
>
> Case 1:
> b = [];
> for i = 1:N
>        b(i, 1:P) = i * ones (1, P);
> endfor
>
> Case 2:
> b = 1.0 * ones (N, P);  # this line doesn't effect the final matrix b
>                        # value. but with this line, the execution time
>                        # becomes much-much faster
> for i = 1:N
>        b(i, 1:P) = i * ones (1, P);
> endfor
>
> My platform:
> - Processor: Intel Core 2 Duo
> - Operating System: Debian GNU/Linux 4
> - Octave Version: 3.0.1
>
> My questions are:
> 1) Is the test result correct?
> 2) Has anyone test about it?
>
> Suggestion:
> I see that b = []; is mostly used on Octave codes. If the result is
> correct (can improve the speed), I think, it better to be changed
> automatically during the parsing step so needless for user to change  
> the
> line manually.
>
> Please find the complete test code and result from my blog:
> http://l411v.blogspot.com/2008/04/octave-speed- 
> optimization-080426.html
>
> Thanks,
> lain.ux

In the faster one, you have preallocated memory for "b".

In the first case, allocation/reallocation takes place on each loop.

You might compare to

> for i = N:-1:1
>        b(i, 1:P) = i * ones (1, P);
> endfor


which should be just as fast as when preallocated.

Regarding an automatic preallocation, I don't think it is possible to  
do so it a universally robust way.

Ben