User`s guide

2 Parallel for-Loops (parfor)
2-8
Reductions: Cumulative Values Updated by Each Iteration
These two examples show parfor-loops using reduction assignments. A reduction is an
accumulation across iterations of a loop. The example on the left uses x to accumulate a
sum across 10 iterations of the loop. The example on the right generates a concatenated
array, 1:10. In both of these examples, the execution order of the iterations on the
workers does not matter: while the workers calculate individual results for each
iteration, the client properly accumulates and assembles the final loop result.
x = 0;
parfor i = 1:10
x = x + i;
end
x
x =
55
x2 = [];
n = 10;
parfor i = 1:n
x2 = [x2, i];
end
x2
x2 =
1 2 3 4 5 6 7 8 9 10
If the loop iterations operate in random sequence, you might expect the concatenation
sequence in the example on the right to be nonconsecutive. However, MATLAB
recognizes the concatenation operation and yields deterministic results.
The next example, which attempts to compute Fibonacci numbers, is not a valid parfor-
loop because the value of an element of f in one iteration depends on the values of other
elements of f calculated in other iterations.
f = zeros(1,50);
f(1) = 1;
f(2) = 2;
parfor n = 3:50
f(n) = f(n-1) + f(n-2);
end
When you are finished with your loop examples, clear your workspace and delete your
parallel pool of workers:
clear
delete(gcp)
Related Examples
• “Create a parfor-Loop” on page 2-4