A typical use case for nested loops is to step through an array using one loop variable to index through one dimension, and a nested loop variable to index another dimension. The basic form looks like this:
X = zeros(n,m); for a = 1:n for b = 1:m X(a,b) = fun(a,b) end end
The following code shows an extremely simple example, with results you can easily view.
M1 = magic(5); for x = 1:5 for y = 1:5 M2(x,y) = x*10 + y + M1(x,y)/10000; end end M2
Although you can parallelize either of the nested loops, you cannot run both in parallel. This is because the workers in a parallel pool cannot start or access further parallel pools.
If the loop counted by x is converted to
a parfor-loop, then each worker in the pool executes
the nested loops using the y loop counter, and
the y loops themselves cannot run as a parfor on
each worker. So if you convert only the outer loop to a parfor,
it looks like this:
M1 = magic(5); parfor a = 1:5 for b = 1:5 M2(a,b) = a*10 + b + M1(a,b)/10000; end end M2
Should you consider converting only the inner loop to a parfor? While it might be programmatically simpler in your case to do this, it might not be advisable. The converted code looks like this:
M1 = magic(5); for a = 1:5 parfor b = 1:5 M2(a,b) = a*10 + b + M1(a,b)/10000; end end M2
In this case, each iteration of the outer loop in MATLAB, initiates
a parfor-loop. That is, this code creates five parfor-loops.
There is generally more overhead to a parfor-loop
than a for-loop, so you might find that this approach
does not perform optimally.