Use parfor
-Loops for Reduction Assignments
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 a nondeterministic 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)