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.The
InputIterator
type must meet the Input Iterator requirements from the [input.iterators] ISO C++ Standard section.The
Container
type must 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 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);
}
}
};