Adisorn Owatsiriwong
Practical Approach:
Converting a serial to parallel for loop must ensure each worker (cpu) handles an independent task. Some useful techniques can be applied as follows:
1. Test Independence:
• Remove the loop and examine whether each iteration’s code can function independently without needing any results or changes made by other iterations.
2. Check for Overlapping Writes:
• Ensure that each iteration writes to a distinct part of any output variables, so that there is no conflict when parallel threads attempt to write to memory.
3. Reduction Operations:
• If you need to accumulate a result across iterations (e.g., summing values), use reduction variables in parfor, which MATLAB handles safely.
Summary:
If you remove the loop and the statements inside can still run properly (independently), then it’s likely that you can use parfor. This approach ensures that the loop can be parallelized safely and efficiently, leveraging MATLAB’s parallel computing capabilities.