In some cases, you must modify the code to convert
parfor-loops. This example shows how to diagnose
parfor-loop problems using a simple nested
Run this code in MATLAB® and examine the results.
for x = 0:0.1:1 for k = 2:10 x(k) = x(k-1) + k; end x end
To speed up the code, try to convert the
parfor-loops. Observe that this code produces
parfor x = 0:0.1:1 parfor k = 2:10 x(k) = x(k-1) + k; end x end
In this case you cannot simply convert the
parfor-loops without modification. To make
this work, you must change the code in several places. To diagnose
the problems, look for Code Analyzer messages in the MATLAB Editor.
This code shows common problems when you try to convert
To solve these problems, you must modify the code to use
The body of the
parfor-loop is executed in a
parallel pool using multiple MATLAB workers in a nondeterministic
order. Therefore, you have to meet these requirements for the body
The body of the
be independent. One loop iteration cannot depend on a previous iteration,
because the iterations are executed in parallel in a nondeterministic
order. In the example,
x(k) = x(k-1) + k;
parfor. For next steps in dealing with independence issues, see Ensure That parfor-Loop Iterations are Independent.
You cannot nest a
parfor-loop. The example has two
for-loops, and therefore you can replace
for-loop with a
Instead, you can call a function that uses a
inside the body of the other
parfor-loops give you no computational
benefit, because all workers are used to parallelize the outermost
loop. For help dealing with nested loops, see Nested parfor-Loops and for-Loops.
parfor-loop variables must be
consecutive increasing integers. In the example,
parfor x = 0:0.1:1
parforhere. You can solve this problem by changing the value of the loop variable to integer values required by the algorithm. For next steps in troubleshooting
parfor-loop variables, see Ensure That parfor-Loop Variables Are Consecutive Increasing Integers.
You cannot break out of a
early, as you can in a
for-loop. Do not include
a return or break statement in the body of your
Without communication, the other MATLAB instances running the loop
do not know when to stop. As an alternative, consider
If you still have problems converting
parfor-loops, see Troubleshoot Variables in parfor-Loops.
You can profile a
measure the speedup compared to the corresponding
tocBytes to measure how much data is
transferred to and from the workers in the parallel pool. For more
information and examples, see Profiling parfor-loops.