All Listable functions can be parallelized with ParallelCombine:

If the function is not Listable use an explicit Map:

Many functional programming constructs can be parallelized with ParallelCombine:

The result need not have the same length as the input:

Evaluate the elements of a list in parallel:

The overall count of matching elements is equal to the sum of the partial counts:

An element appears in a list if it appears in at least one of the pieces:

An element does not appear on a list if it appears in none of the pieces:

Each subkernel performs a smaller number of additions and the combiner combines the results:

Automatically pick the combiner for Flat functions:

Typical Flat functions:

Break the computation into the smallest possible subunits:

Break the computation into as many pieces as there are available kernels:

Break the computation into at most 2 evaluations per kernel for the entire job:

Break the computation into evaluations of at most 5 elements each:

The default option setting balances evaluation size and number of evaluations:

Visualize the number of evaluations per kernel and items per evaluation:

By default, definitions in the current context are distributed automatically:

Do not distribute any definitions of functions:

Distribute definitions for all symbols in all contexts appearing in a parallel computation:

Distribute only definitions in the given contexts:

Restore the value of the DistributedContexts option to its default: