parallel processing time is bigger,

I have a code comparing a to process using parfor and for, but the time of the parfor is bigger thans using "for". here below the program:

Count=12000000;
MSB=A(2:2:Count);
LSB=A(1:2:Count);
DiffB=zeros(Count/2,1);
B=DiffB;
tic
for i=2:2:Count
    B(i/2)=A(i)*256 + A(i-1);

end
for j=1:size(B,2)-1
    if((B(j+1)==0) && (B(j)==4095))
        DiffB(j)=1;
    else
        DiffB(j)=B(j+1)-B(j);
    end
end
t1=toc
tic
parfor i = 1:Count/2           
    B(i)=MSB(i)*256 + LSB(i);
end
C=B;
parfor j=1:size(B,2)-1
    if((B(j+1)==0) && (C(j)==4095))
           DiffB(j)=1
    else
        DiffB(j)=B(j+1)-C(j);
    end
end
t2=toc
matlabpool close
disp('Tiempo differencia')
t2-t1

time for "FOR" is 0.6016 sec and the time for "PARFOR" 5.5039 sec can someone can tell me what did I make wrong?

[Julio]

NOte: before execute the code, I execute matlabpool('open',2); and it works

Answer 1

[Matt J]

Are you running inside a script or in an mfile function? Try both.

[Matt J]

But aside from that, your compute-to-memory-access ratio looks very small. You are doing very little computation inside the loops for every element of data (LSB(i), MSB(i), etc...) that you are sending to the workers. PARFOR is intended for a situations where you are doing a lot more computational work inside the loops.

[Julio]

Thanks for your answer, so the fact my process is very simple ,"PARFOR" is not usefull. thanks