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)