MATLAB: Optimize the ordering of nested loop for speed

nested loopsspeed

Suppose I have the following code. Will it be faster version 1 or version 2? What changes is the ordering of the two nested loops

VERSION 1

% bigArray has dim: [npolv,nz,nsv]

% npolv=68961 > nsv=200 > nz=81

% zgrid is [nz,1], kgrid is [nsv,1]

for j=1:nz
   for qq=1:nsv
       % the output of fun is a vector dim npolv
       bigArray(:,j,qq) = fun(zgrid(j),kgrid(qq));
   end
end

or VERSION 2

% bigArray has dim: [npolv,nz,nsv]
% npolv=68961 > nsv=200 > nz=81
% zgrid is [nz,1], kgrid is [nsv,1]
for qq=1:nsv
    for j=1:nz
        % the output of fun is a vector with dim npolv
        bigArray(:,j,qq) = fun(zgrid(j),kgrid(qq));
    end
end

Best Answer

Why not use tic before the loop, and toc after the loop?

Because MATLAB is column major, you'll find it's best to put the right most indexes innermost, and the left indexes outermost:

for slice = 1 : slices
        for col = 1 : numColumns
                for row = 1 : numRows
                       array(row, col, slice) = ......
                end
        end
end

Related Solutions

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.

MATLAB: Extract specific rows or columns containing letters (xxx) From dat File in Matlab

The code below reads the xlsx file as a table t using readtable and converts it to a cell array C with table2cell . It uses cellfun and regexp to determine which cells in C contain 'NSV'. Find is used to determine the row and column of each entry in tokens in the cell array C.

If you need to match three different combinations of letters, replace 'NSV' in the regexp with said combination. If you need to do it programmatically, you can use strcat to obtain the expression string used for the regexp.

 t = readtable('dta.xlsx','ReadVariableNames',false);
 C = table2cell(t);
 [tokens,matches] = cellfun(@(x) (regexp((x),'(.+)(?<=NSV)(.+)','match','tokens')),C,'un',0);
 [row,col] = find(cellfun(@(x) ~isempty(x),tokens));
 data = C(row:end,col);

The first row of data is the char vectors which contain 'NSV', where the following rows contain all the corresponding data.

Sample output, first column of data:

 'BCS_PHY/FUN_OUT/ENV/HYD_NSV1_COIL1_CURRENT_OVERRIDE_OUTPUT'
 '0'
 '0'
 '0.012293'
 '0.012293'
 '-0.024586'
 ...
 ...
 ...

Sample output, second column of data:

 'BCS_PHY/FUN_OUT/ENV/HYD_NSV1_COIL2_CURRENT_OVERRIDE_OUTPUT'
 '0.012305'
 '0'
 '0.012305'
 '0'
 '-0.024611'
 ...
 ...
 ...

Best Answer

Related Solutions

MATLAB: For-loop order

MATLAB: Extract specific rows or columns containing letters (xxx) From dat File in Matlab

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