NAME¶

std::experimental::parallel::transform_reduce - std::experimental::parallel::transform_reduce

Synopsis¶

Defined in header <experimental/numeric>
template< class InputIt, class UnaryOp, class T, class BinaryOp
>

T transform_reduce( InputIt first, InputIt last, (1) (parallelism TS)

UnaryOp unary_op, T init, BinaryOp
binary_op );
template< class ExecutionPolicy,

class InputIt, class UnaryOp, class T, class BinaryOp
>
T transform_reduce( ExecutionPolicy&& policy, (2) (parallelism TS)
InputIt first, InputIt last,

UnaryOp unary_op, T init, BinaryOp
binary_op );

Applies unary_op to each element in the range [first, last) and reduces the results
(possibly permuted and aggregated in unspecified manner) along with the initial
value init over binary_op.

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

The behavior is undefined if unary_op or 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
unary_op - unary FunctionObject that will be applied to each element of the input
range. The return type must be acceptable as input to binary_op
binary_op - binary FunctionObject that will be applied in unspecified order to the
results of unary_op, the results of other binary_op and init

Type requirements¶

-
InputIt must meet the requirements of LegacyInputIterator.

Return value¶

Generalized sum of init and unary_op(*first), unary_op(*(first + 1)), ...
unary_op(*(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 results of unary_op may be grouped and arranged in arbitrary
order.

Complexity¶

O(last - first) applications each of unary_op and 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¶

unary_op is not applied to init.

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¶

transform_reduce can be used to parallelize std::inner_product:

// Run this code

#include <boost/iterator/zip_iterator.hpp>
#include <boost/tuple.hpp>
#include <experimental/execution_policy>
#include <experimental/numeric>
#include <functional>
#include <iostream>
#include <iterator>
#include <vector>

int main()
{
std::vector<double> xvalues(10007, 1.0), yvalues(10007, 1.0);

double result = std::experimental::parallel::transform_reduce(
std::experimental::parallel::par,
boost::iterators::make_zip_iterator(
boost::make_tuple(std::begin(xvalues), std::begin(yvalues))),
boost::iterators::make_zip_iterator(
boost::make_tuple(std::end(xvalues), std::end(yvalues))),
[](auto r) { return boost::get<0>(r) * boost::get<1>(r); }
0.0,
std::plus<>()
);
std::cout << result << '\n';
}

Output:¶

10007

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)
reduce similar to std::accumulate, except out of order
(parallelism TS) (function template)