parallel_for_each¶

[algorithms.parallel_for_each]

Function template that processes work items in parallel.

// Defined in header <tbb/parallel_for_each.h>

namespace tbb {

    template<typename InputIterator, typename Body>
    void parallel_for_each( InputIterator first, InputIterator last, Body body );
    template<typename InputIterator, typename Body>
    void parallel_for_each( InputIterator first, InputIterator last, Body body, task_group_context& group );

    template<typename Container, typename Body>
    void parallel_for_each( Container c, Body body );
    template<typename Container, typename Body>
    void parallel_for_each( Container c, Body body, task_group_context& group );

} // namespace tbb

Requirements:

The Body type shall meet the ParallelForEachBody requirements.
The InputIterator type shall meet the Input Iterator requirements from [input.iterators] ISO C++ Standard section.
The Container type shall meet the ContainerBasedSequence requirements

The parallel_for_each template has two forms.

The sequence form parallel_for_each(first, last, body) applies a function object body over a sequence [first,last). Items may be processed in parallel.

The container form parallel_for_each(c, body) is equivalent to parallel_for_each(std::begin(c), std::end(c), body).

All overloads can accept a task_group_context object so that the algorithm’s tasks are executed in this group. By default the algorithm is executed in a bound group of its own.

feeder Class¶

Additional work items can be added by body if it has a second argument of type feeder. The function terminates when body(x) returns for all items x that were in the input sequence or added by method feeder::add.

feeder

Example¶

The following code sketches a body with the two-argument form of operator().

struct MyBody {
    void operator()(item_t item, parallel_do_feeder<item_t>& feeder ) {
        for each new piece of work implied by item do {
            item_t new_item = initializer;
            feeder.add(new_item);
        }
    }
};