Smpd - Slower than Serial

Hi everybody,

I am new to parallel computing. Therefore the solution to the problem might be easy.

I have a grid and I need to evaluate a function at each grid point. Therefore I wanted to assign some part of the grid to different workers in order to have speedup. However when I run the code in parallel I cannot see a difference in the computation time compared to serial computation. I also tested the case while changing the number of workers. In order to avoid overhead computations I run the code long enough. So what is my mistake?

My code is like this:

matlabpool ( 'open' , 4 )

Xpos = 10:0.1:25;
Ypos = 1:0.1:10;

n_x = length(Xpos);
n_y = length(Ypos);

     spmd
        i_x=codistributed(1:n_x);
        i_y=codistributed(1:n_y);
     end

 tic;
 for i_x  = 1:n_x 
    for i_y  = 1:n_y 

 output = myfunction(Xpos(i_x),Ypos(i_y));

    end
 end

 Time=toc;

 matlabpool('close')

[Jill Reese]

What operations are you performing on the Xpos and Ypos variables within myfunction?

[Jason Ross]

Which scheduler are you using? (I assume "local")

How many compute cores (not hyperthreaded cores) does your machine have? (I assume 4)

How much RAM does your machine have? Do you use it all up and go to swap?

What is "long enough"? Seconds? Minutes? Hours? Days?