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namespace tf {
/** @page ParallelTransforms Parallel Transforms
%Taskflow provides template functions for constructing tasks to
perform parallel transforms over ranges of items.
@tableofcontents
@section ParallelTransformsInclude Include the Header
You need to include the header file, <tt>taskflow/algorithm/transform.hpp</tt>,
for creating a parallel-transform task.
@code{.cpp}
#include <taskflow/algorithm/transform.hpp>
@endcode
@section ParallelTransformsOverARange Create a Unary Parallel-Transform Task
Parallel-transform transforms a range of items, possibly
with a different type for the transformed data, and stores the result in another range.
The task created by tf::Taskflow::transform(B first1, E last1, O d_first, C c, P&& part)
is equivalent to a parallel execution of the following loop:
@code{.cpp}
while (first1 != last1) {
*d_first++ = c(*first1++);
}
@endcode
tf::Taskflow::transform
simultaneously applies the callable @c c to the object obtained by dereferencing
every iterator in the range <tt>[first1, last1)</tt> and stores
the result in another range beginning at @c d_first.
It is user's responsibility for ensuring the range is valid
within the execution of the parallel-transform task.
@code{.cpp}
std::vector<int> src = {1, 2, 3, 4, 5};
std::vector<int> tgt(src.size());
taskflow.transform(src.begin(), src.end(), tgt.begin(), [](int i){
std::cout << "transforming item " << i << " to " << i + 1 << '\n';
return i + 1;
});
@endcode
@section ParallelTransformsCaptureIteratorsByReference Capture Iterators by Reference
You can pass iterators by reference using @std_ref
to marshal parameter update between dependent tasks.
This is especially useful when the range is unknown
at the time of creating a parallel-transform task,
but needs initialization from another task.
@code{.cpp}
std::vector<int> src, tgt;
std::vector<int>::iterator first, last, d_first;
tf::Task init = taskflow.emplace([&](){
src.resize(1000);
tgt.resize(1000);
first = src.begin();
last = src.end();
d_first = tgt.begin();
});
tf::Task transform = taskflow.transform(
std::ref(first), std::ref(last), std::ref(d_first),
[&](int i) {
std::cout << "transforming item " << i << " to " << i + 1 << '\n';
return i+1;
}
);
init.precede(transform);
@endcode
When @c init finishes, the parallel-transform task @c transform
will see @c first pointing to the beginning of @c src and
@c last pointing to the end of @c src.
Then, it simultaneously transforms these 1000 items
by adding one to each element and stores the result
in another range starting at @c d_first.
@section ParallelBinaryTransformsOverARange Create a Binary Parallel-Transform Task
You can use the overload,
tf::Taskflow::transform(B1 first1, E1 last1, B2 first2, O d_first, C c, P&& part),
to perform parallel transforms on two source ranges pointed by
@c first1 and @c first2 using the binary
operator @c c
and store the result in another range pointed by @c d_first.
This method is equivalent to the parallel execution of the following loop:
@code{.cpp}
while (first1 != last1) {
*d_first++ = c(*first1++, *first2++);
}
@endcode
The following example creates a parallel-transform task
that adds two ranges of elements one by one
and stores the result in a target range:
@code{.cpp}
std::vector<int> src1 = {1, 2, 3, 4, 5};
std::vector<int> src2 = {5, 4, 3, 2, 1};
std::vector<int> tgt(src1.size());
taskflow.transform(
src1.begin(), src1.end(), src2.begin(), tgt.begin(),
[](int i, int j){
return i + j;
}
);
@endcode
@section ParallelTransformsCfigureAPartitioner Configure a Partitioner
You can configure a partitioner for parallel-transform tasks to run with different
scheduling methods, such as guided partitioning, dynamic partitioning, and static partitioning.
The following example creates two parallel-transform tasks using two different
partitioners, one with the static partitioning algorithm and
another one with the guided partitioning algorithm:
@code{.cpp}
tf::StaticPartitioner static_partitioner;
tf::GuidedPartitioner guided_partitioner;
std::vector<int> src1 = {1, 2, 3, 4, 5};
std::vector<int> src2 = {5, 4, 3, 2, 1};
std::vector<int> tgt1(src1.size());
std::vector<int> tgt2(src2.size());
// create a parallel-transform task with static execution partitioner
taskflow.transform(
src1.begin(), src1.end(), src2.begin(), tgt1.begin(),
[](int i, int j){
return i + j;
},
static_partitioner
);
// create a parallel-transform task with guided execution partitioner
taskflow.transform(
src1.begin(), src1.end(), src2.begin(), tgt2.begin(),
[](int i, int j){
return i + j;
},
guided_partitioner
);
@endcode
@attention
By default, parallel-transform tasks use tf::DefaultPartitioner
if no partitioner is specified.
*/
}
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