NAME¶

std::experimental::parallel::reduce - std::experimental::parallel::reduce

Synopsis¶

Defined in header <experimental/numeric>
template< class InputIt >

typename std::iterator_traits<InputIt>::value_type reduce( (1) (parallelism TS)

InputIt first, InputIt last );
template< class ExecutionPolicy, class InputIterator >

typename std::iterator_traits<InputIt>::value_type reduce( (2) (parallelism TS)

ExecutionPolicy&& policy, InputIt first, InputIt last );
template< class InputIt, class T > (3) (parallelism TS)
T reduce( InputIt first, InputIt last, T init );
template< class ExecutionPolicy, class InputIt, class T >
T reduce( ExecutionPolicy&& policy, InputIt first, InputIt (4) (parallelism TS)
last, T init );
template< class InputIt, class T, class BinaryOp >
T reduce( InputIt first, InputIt last, T init, BinaryOp (5) (parallelism TS)
binary_op );
template< class ExecutionPolicy, class InputIt, class T, class
BinaryOp >

T reduce( ExecutionPolicy&& policy, (6) (parallelism TS)

InputIt first, InputIt last, T init, BinaryOp
binary_op );

1) Same as reduce(first, last, typename
std::iterator_traits<InputIt>::value_type{}).
3) Same as reduce(first, last, init, std::plus<>()).
5) Reduces the range [first, last), possibly permuted and aggregated in unspecified
manner, along with the initial value init over binary_op.
2,4,6) Same as (1,3,5), but executed according to policy.

The behavior is non-deterministic if binary_op is not associative or not
commutative.

The behavior is undefined if binary_op modifies any element or invalidates any
iterator in [first, last).

Parameters¶

first, last - the range of elements to apply the algorithm to
init - the initial value of the generalized sum
policy - the execution policy
binary FunctionObject that will be applied in unspecified order to the
binary_op - result of dereferencing the input iterators, the results of other
binary_op and init

Type requirements¶

-
InputIt must meet the requirements of LegacyInputIterator.

Return value¶

Generalized sum of init and *first, *(first + 1), ... *(last - 1) over binary_op,

where generalized sum GSUM(op, a
1, ..., a
N) is defined as follows:

* if N=1, a
1
* if N > 1, op(GSUM(op, b
1, ..., b
K), GSUM(op, b
M, ..., b
N)) where

* b
1, ..., b
N may be any permutation of a1, ..., aN and
* 1 < K+1 = M ≤ N

in other words, the elements of the range may be grouped and rearranged in arbitrary
order.

Complexity¶

O(last - first) applications of binary_op.

Exceptions¶

* If execution of a function invoked as part of the algorithm throws an exception,

* if policy is parallel_vector_execution_policy, std::terminate is called.
* if policy is sequential_execution_policy or parallel_execution_policy, the
algorithm exits with an exception_list containing all uncaught exceptions. If
there was only one uncaught exception, the algorithm may rethrow it without
wrapping in exception_list. It is unspecified how much work the algorithm will
perform before returning after the first exception was encountered.
* if policy is some other type, the behavior is implementation-defined.
* If the algorithm fails to allocate memory (either for itself or to construct an
exception_list when handling a user exception), std::bad_alloc is thrown.

Notes¶

If the range is empty, init is returned, unmodified.

* If policy is an instance of sequential_execution_policy, all operations are
performed in the calling thread.
* If policy is an instance of parallel_execution_policy, operations may be
performed in unspecified number of threads, indeterminately sequenced with each
other.
* If policy is an instance of parallel_vector_execution_policy, execution may be
both parallelized and vectorized: function body boundaries are not respected and
user code may be overlapped and combined in arbitrary manner (in particular,
this implies that a user-provided Callable must not acquire a mutex to access a
shared resource).

Example¶

reduce is the out-of-order version of std::accumulate:

// Run this code

#include <chrono>
#include <experimental/execution_policy>
#include <experimental/numeric>
#include <iostream>
#include <numeric>
#include <vector>

int main()
{
std::vector<double> v(10'000'007, 0.5);

{
auto t1 = std::chrono::high_resolution_clock::now();
double result = std::accumulate(v.begin(), v.end(), 0.0);
auto t2 = std::chrono::high_resolution_clock::now();
std::chrono::duration<double, std::milli> ms = t2 - t1;
std::cout << std::fixed << "std::accumulate result " << result
<< " took " << ms.count() << " ms\n";
}

{
auto t1 = std::chrono::high_resolution_clock::now();
double result = std::experimental::parallel::reduce(
std::experimental::parallel::par,
v.begin(), v.end());
auto t2 = std::chrono::high_resolution_clock::now();
std::chrono::duration<double, std::milli> ms = t2 - t1;
std::cout << "parallel::reduce result "
<< result << " took " << ms.count() << " ms\n";
}
}

Possible output:¶

std::accumulate result 5000003.50000 took 12.7365 ms
parallel::reduce result 5000003.50000 took 5.06423 ms

See also¶

accumulate sums up or folds a range of elements
(function template)
applies a function to a range of elements, storing results in a
transform destination range
(function template)
transform_reduce applies a functor, then reduces out of order
(parallelism TS) (function template)