Improving Performance with Parallel Computing - MATLAB & Simulink (original) (raw)

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Factors That Affect Speed

Some factors may affect the speed of execution of parallel processing:

Factors That Affect Results

Some factors may affect numerical results when using parallel processing. There are more caveats related to parfor listed in Parallel for-Loops (parfor) (Parallel Computing Toolbox).

Searching for Global Optima

To search for global optima, one approach is to evaluate a solver from a variety of initial points. If you distribute those evaluations over a number of processors using the parfor function, you disable parallel gradient estimation, since parfor loops cannot be nested. Your optimization usually runs more quickly if you distribute the evaluations over all the processors, rather than running them serially with parallel gradient estimation, so disabling parallel estimation probably won't slow your computation. If you have more processors than initial points, though, it is not clear whether it is better to distribute initial points or to enable parallel gradient estimation.

If you have a Global Optimization Toolbox license, you can use the MultiStart (Global Optimization Toolbox) solver to examine multiple start points in parallel. SeeParallel Computing (Global Optimization Toolbox) andParallel MultiStart (Global Optimization Toolbox).

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