MATLAB: Improving performance of for loop and function calls

for loopmatlab functionperformance

I have this matlab code as part of my matlab project, as the info. i got from the 'profreport' most of the time is spent in the 'while' line. any help regarding how can i improve the efficency. or generally how can i make the for loops more efficient. Thank you!

% p is 2D matrix of big size

s=size(p); pp=p; p=zeros(s(1),s(2));

 while(norm(p-pp)>0.05 )
       p=pp;
       for n=1:N 
                  z=0;
                  for miu=1:C
                       z = z + p(n,miu) * funQ(n,miu,p,R,N,C); % call function funQ

                  end 
         for lambda=1:C                            
                  pp(n,lambda) = (p(n,lambda) * funQ(n,lambda,p,R,N,C))/z; % call function funQ
          end 
       end   
 end

Best Answer

Try switching the order. MATLAB likes to go down rows first, then over to the next column and down its rows. So you want the inner index to be the inner iterator. So swap the order of the loops over miu and n. Have n be the inner loop. See if that's any faster. A for loop by itself is pretty fast -- I can do tens of millions of iterations in a fraction of a second. What can take time is accessing the memory and if adjacent iterations need to access far flung memory locations, then that's what will slow it down. It's faster if the next memory location it needs is close to the one you accessed last.

Related Solutions

MATLAB: How to store data from the IF loop

Well, you don't have a loop at the moment. 'if' is not a loop, it is just a single statement.

Something similar to the following is what you need. I went off your words rather than code for the criteria in the if statements as your code does not match what you state as the conditions.

for n = 1:numel( q )
...
if q(n) < q1(n)
   p(n) = p1(n);
elseif q(n) <= q2(n) + g1(n)
   p(n) = p2(n);
else
   p(n) = p3(n);
end
end

MATLAB: For-loop order

For the m-code loop itself it probably doesn't matter since the total number of iterations is the same. The stuff inside the for loops can easily dominate the run-time so it may be a moot point. But for memory access, it is often good practice to transverse an array in memory order to take advantage of memory caching. E.g.,

A = some MxN matrix
for i=1:M
    for j=1:N
        % some stuff involving A(i,j) here

    end
end

The above does not access the elements of A in linear order since A is stored in column order. So the memory access pattern for A jumps around in memory.

A = some MxN matrix
for j=1:N
    for i=1:M
        % some stuff involving A(i,j) here
    end
end

The above does access A in linear order in memory, so it would take better advantage of the memory cache.

All that being said, the m-code for-loop stuff and what you are doing inside the for-loops may easily dominate the A memory access times so in practice you may not see much difference between the two.

E.g., take this code

A = rand(5000);
disp('Access jumping around in memory');
tic
for i=1:5000
    for j=1:5000
        A(i,j);
    end
end
toc
disp('Access in linear order');
tic
for j=1:5000
    for i=1:5000
        A(i,j);
    end
end
toc

And run it:

Access jumping around in memory
Elapsed time is 1.542680 seconds.
Access in linear order
Elapsed time is 0.802103 seconds.

Best Answer

Related Solutions

MATLAB: How to store data from the IF loop

MATLAB: For-loop order

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