Convert for-Loops Into parfor-Loops

Convert `for`-Loops Into `parfor`-Loops

In some cases, you must modify the code to convert for-loops to parfor-loops. This example shows how to diagnose and fix parfor-loop problems using a simple nested for-loop. 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 for-loops to parfor-loops. Observe that this code produces errors.

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 for-loops to 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 for-loops to parfor-loops.

To solve these problems, you must modify the code to use parfor. 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 of the parfor-loop:

The body of the parfor-loop must 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;
```
is not independent, and therefore you cannot use parfor. For next steps in dealing with independence issues, see Ensure That parfor-Loop Iterations are Independent.
You cannot nest a parfor-loop inside another parfor-loop. The example has two nested for-loops, and therefore you can replace only one for-loop with a parfor-loop. Instead, you can call a function that uses a parfor-loop inside the body of the other parfor-loop. However, such nested 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
```
has non-integer loop variables, and therefore you cannot use parfor here. 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 parfor-loop early, as you can in a for-loop. Do not include a return or break statement in the body of your parfor-loop. Without communication, the other MATLAB instances running the loop do not know when to stop. As an alternative, consider parfeval.
If you still have problems converting for-loops to parfor-loops, see Troubleshoot Variables in parfor-Loops.

Tip

You can profile a parfor-loops using tic and toc to measure the speedup compared to the corresponding for-loop. Use ticBytes and 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.

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Convert `for`-Loops Into `parfor`-Loops

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Parallel Computing Toolbox Documentation

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