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parallel_for_each

parallel_for_each#

[algorithms.parallel_for_each]

Function template that processes work items in parallel.

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

namespace oneapi {
    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& context );

        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& context );

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

    } // namespace tbb
} // namespace oneapi

Requirements:

  • The Body type must meet the ParallelForEachBody requirements. Since C++17, Body may also be a pointer to a member function in Index.

  • The InputIterator type must meet the Input Iterator requirements from the [input.iterators] section of the ISO C++ Standard.

  • If InputIterator type does not meet the Forward Iterator requirements from the [forward.iterators] section of the ISO C++ Standard, the std::iterator_traits<InputIterator>::value_type type must be constructible from std::iterator_traits<InputIterator>::reference.

  • The Container type must meet the ContainerBasedSequence requirements.

  • The type returned by Container::begin() must meet the same requirements as the InputIterator type above.

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 context. By default, the algorithm is executed in a bound context 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.

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);
        }
    }
};
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