parallel_reduce¶
[algorithms.parallel_reduce]
Function template that computes reduction over a range.
// Defined in header <oneapi/tbb/parallel_reduce.h>
namespace oneapi {
namespace tbb {
template<typename Range, typename Value, typename Func, typename Reduction>
Value parallel_reduce(const Range& range, const Value& identity, const Func& func, const Reduction& reduction, /* see-below */ partitioner, task_group_context& context);
template<typename Range, typename Value, typename Func, typename Reduction>
Value parallel_reduce(const Range& range, const Value& identity, const Func& func, const Reduction& reduction, /* see-below */ partitioner);
template<typename Range, typename Value, typename Func, typename Reduction>
Value parallel_reduce(const Range& range, const Value& identity, const Func& func, const Reduction& reduction, task_group_context& context);
template<typename Range, typename Value, typename Func, typename Reduction>
Value parallel_reduce(const Range& range, const Value& identity, const Func& func, const Reduction& reduction);
template<typename Range, typename Body>
void parallel_reduce(const Range& range, Body& body, /* see-below */ partitioner, task_group_context& context);
template<typename Range, typename Body>
void parallel_reduce(const Range& range, Body& body, /* see-below */ partitioner);
template<typename Range, typename Body>
void parallel_reduce(const Range& range, Body& body, task_group_context& context);
template<typename Range, typename Body>
void parallel_reduce(const Range& range, Body& body);
} // namespace tbb
} // namespace oneapi
A partitioner
type may be one of the following entities:
const auto_partitioner&
const simple_partitioner&
const static_partitioner&
affinity_partitioner&
Requirements:
The
Range
type must meet the Range requirements.The
Body
type must meet the ParallelReduceBody requirements.The
Func
type must meet the ParallelReduceFunc requirements.The
Reduction
types must meet :ParallelReduceReduction requirements.
The function template parallel_reduce
has two forms:
The functional form is designed to be easy to use in conjunction with lambda expressions.
The imperative form is designed to minimize copying of data.
The functional form parallel_reduce(range, identity, func, reduction)
performs a parallel reduction by applying func to
subranges in range and reducing the results with the binary operator reduction.
It returns the result of the reduction. The identity parameter specifies the left identity element for func’s operator()
.
Parameters func and reduction can be lambda expressions.
The imperative form parallel_reduce(range,body)
performs parallel reduction of body over each value in range.
A parallel_reduce
recursively splits the range into subranges to the point such that is_divisible()
is false for each subrange.
A parallel_reduce
uses the splitting constructor to make one or more copies of the body for each thread.
It may copy a body while the body’s operator()
or method join
runs concurrently.
You are responsible for ensuring the safety of such concurrency. In typical usage, the safety requires no extra effort.
parallel_reduce
may invoke the splitting constructor for the body.
For each such split of the body, it invokes the join
method to merge the results from the bodies.
Define join
to update this to represent the accumulated result for this and rhs.
The reduction operation should be associative, but does not have to be commutative.
For a noncommutative operation op, left.join(right)
should update left to be the result of left op right.
A body is split only if the range is split, but the converse is not necessarily to be so.
The user must neither rely on a particular choice of body splitting nor on the subranges processed by a
given body object being consecutive. parallel_reduce
makes the choice of body splitting nondeterministically.
When executed serially parallel_reduce
run sequentially from left to right in the same sense as for parallel_for
.
Sequential execution never invokes the splitting constructor or method join.
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.
Complexity
If the range and body take O(1) space, and the range splits into nearly equal pieces, the space complexity is O(P×log(N)), where N is the size of the range and P is the number of threads.
Example (Imperative Form)¶
The following code sums the values in an array.
#include "oneapi/tbb/parallel_reduce.h"
#include "oneapi/tbb/blocked_range.h"
using namespace oneapi::tbb;
struct Sum {
float value;
Sum() : value(0) {}
Sum( Sum& s, split ) {value = 0;}
void operator()( const blocked_range<float*>& r ) {
float temp = value;
for( float* a=r.begin(); a!=r.end(); ++a ) {
temp += *a;
}
value = temp;
}
void join( Sum& rhs ) {value += rhs.value;}
};
float ParallelSum( float array[], size_t n ) {
Sum total;
parallel_reduce( blocked_range<float*>( array, array+n ), total );
return total.value;
}
The example generalizes to reduction for any associative operation op as follows:
Replace occurrences of 0 with the identity element for op
Replace occurrences of += with op= or its logical equivalent.
Change the name
Sum
to something more appropriate for op.
The operation may be noncommutative. For example, op could be matrix multiplication.
Example with Lambda Expressions¶
The following is similar to the previous example, but written using lambda
expressions and the functional form of parallel_reduce
.
#include "oneapi/tbb/parallel_reduce.h"
#include "oneapi/tbb/blocked_range.h"
using namespace oneapi::tbb;
float ParallelSum( float array[], size_t n ) {
return parallel_reduce(
blocked_range<float*>( array, array+n ),
0.f,
[](const blocked_range<float*>& r, float init)->float {
for( float* a=r.begin(); a!=r.end(); ++a )
init += *a;
return init;
},
[]( float x, float y )->float {
return x+y;
}
);
}
See also: