std::experimental::parallel::reduce
From cppreference.com
< cpp | experimental
Defined in header <experimental/numeric>
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template<class InputIt> typename std::iterator_traits<InputIt>::value_type reduce( |
(1) | (parallelism TS) |
template<class ExecutionPolicy, class InputIterator> typename std::iterator_traits<InputIt>::value_type reduce( |
(2) | (parallelism TS) |
template<class InputIt, class T> T reduce(InputIt first, InputIt last, T init); |
(3) | (parallelism TS) |
template<class ExecutionPolicy, class InputIt, class T> T reduce(ExecutionPolicy&& policy, InputIt first, InputIt last, T init); |
(4) | (parallelism TS) |
template<class InputIt, class T, class BinaryOp> T reduce(InputIt first, InputIt last, T init, BinaryOp binary_op); |
(5) | (parallelism TS) |
template<class ExecutionPolicy, class InputIt, class T, class BinaryOp> T reduce(ExecutionPolicy&& policy, |
(6) | (parallelism TS) |
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_op | - | binary FunctionObject that will be applied in unspecified order to the result of dereferencing the input iterators, the results of other binary_op and init .
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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
- b
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
isparallel_vector_execution_policy
, std::terminate is called - if
policy
issequential_execution_policy
orparallel_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 inexception_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
- 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 ofsequential_execution_policy
, all operations are performed in the calling thread. - If
policy
is an instance ofparallel_execution_policy
, operations may be performed in unspecified number of threads, indeterminately sequenced with each other - If
policy
is an instance ofparallel_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 <iostream> #include <chrono> #include <vector> #include <numeric> #include <experimental/execution_policy> #include <experimental/numeric> 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
sums up a range of elements (function template) | |
applies a function to a range of elements (function template) | |
(parallelism TS) |
applies a functor, then reduces out of order (function template) |