parallel processing time is bigger,
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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?
Antworten (1)
Matt J
am 21 Feb. 2014
Are you running inside a script or in an mfile function? Try both.
2 Kommentare
Matt J
am 21 Feb. 2014
Bearbeitet: Matt J
am 21 Feb. 2014
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.
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