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<!DOCTYPE html>

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<title>Taskflow Algorithms » Parallel Transforms | Taskflow QuickStart</title>

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<h1>

<a href="Algorithms.html">Taskflow Algorithms</a> »

Parallel Transforms

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<h3>Contents</h3>

<ul>

<li><a href="#ParallelTransformsInclude">Include the Header</a></li>

<li><a href="#ParallelTransformsOverARange">Create a Unary Parallel-Transform Task</a></li>

<li><a href="#ParallelTransformsCaptureIteratorsByReference">Capture Iterators by Reference</a></li>

<li><a href="#ParallelBinaryTransformsOverARange">Create a Binary Parallel-Transform Task</a></li>

<li><a href="#ParallelTransformsCfigureAPartitioner">Configure a Partitioner</a></li>

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Taskflow provides template functions for constructing tasks to perform parallel transforms over ranges of items.<section id="ParallelTransformsInclude"><h2><a href="#ParallelTransformsInclude">Include the Header</a></h2>You need to include the header file, <code>taskflow/algorithm/transform.hpp</code>, for creating a parallel-transform task.<pre class="m-code">#include <taskflow/algorithm/transform.hpp></pre></section><section id="ParallelTransformsOverARange"><h2><a href="#ParallelTransformsOverARange">Create a Unary Parallel-Transform Task</a></h2>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 <a href="classtf_1_1FlowBuilder.html#ab2db36500ea85146772acc75fc586ced" class="m-doc">tf::Taskflow::transform(B first1, E last1, O d_first, C c, P&& part)</a> is equivalent to a parallel execution of the following loop:<pre class="m-code">while (first1 != last1) {

*d_first++ = c(*first1++);

}</pre><a href="classtf_1_1FlowBuilder.html#ab2db36500ea85146772acc75fc586ced" class="m-doc">tf::Taskflow::transform</a> simultaneously applies the callable <code>c</code> to the object obtained by dereferencing every iterator in the range <code>[first1, last1)</code> and stores the result in another range beginning at <code>d_first</code>. It is user's responsibility for ensuring the range is valid within the execution of the parallel-transform task.<pre class="m-code">std::vector<int> src = {1, 2, 3, 4, 5};

taskflow.transform(src.begin(), src.end(), tgt.begin(), [](int i){

std::cout << "transforming item " << i << " to " << i + 1 << '\n';

return i + 1;

});</pre></section><section id="ParallelTransformsCaptureIteratorsByReference"><h2><a href="#ParallelTransformsCaptureIteratorsByReference">Capture Iterators by Reference</a></h2>You can pass iterators by reference using <a href="https://en.cppreference.com/w/cpp/utility/functional/ref">std::ref</a> 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.<pre class="m-code">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.for_each(

std::ref(first), std::ref(last), std::ref(d_first),

[&](int i) {

return i+1;

}

);

init.precede(transform);</pre>When <code>init</code> finishes, the parallel-transform task <code>transform</code> will see <code>first</code> pointing to the beginning of <code>src</code> and <code>last</code> pointing to the end of <code>src</code>. Then, it simultaneously transforms these 1000 items by adding one to each element and stores the result in another range starting at <code>d_first</code>.</section><section id="ParallelBinaryTransformsOverARange"><h2><a href="#ParallelBinaryTransformsOverARange">Create a Binary Parallel-Transform Task</a></h2>You can use the overload, <a href="classtf_1_1FlowBuilder.html#a519ca8f909c86efdc70fa01f28156219" class="m-doc">tf::Taskflow::transform(B1 first1, E1 last1, B2 first2, O d_first, C c, P&& part)</a>, to perform parallel transforms on two source ranges pointed by <code>first1</code> and <code>first2</code> using the binary operator <code>c</code> and store the result in another range pointed by <code>d_first</code>. This method is equivalent to the parallel execution of the following loop:<pre class="m-code">while (first1 != last1) {

}</pre>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:<pre class="m-code">std::vector<int> src1 = {1, 2, 3, 4, 5};

std::vector<int> src2 = {5, 4, 3, 2, 1};

taskflow.transform(

src1.begin(), src1.end(), src2.begin(), tgt.begin(),

[](int i, int j){

return i + j;

}

);</pre></section><section id="ParallelTransformsCfigureAPartitioner"><h2><a href="#ParallelTransformsCfigureAPartitioner">Configure a Partitioner</a></h2>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:<pre class="m-code">tf::StaticPartitioner static_partitioner;

tf::GuidedPartitioner guided_partitioner;

std::vector<int> src1 = {1, 2, 3, 4, 5};

// create a parallel-transform task with static execution partitioner

taskflow.transform(

src1.begin(), src1.end(), src2.begin(), tgt1.begin(),

return i + j;

},

static_partitioner

);

// create a parallel-transform task with guided execution partitioner

taskflow.transform(

src1.begin(), src1.end(), src2.begin(), tgt2.begin(),

return i + j;

},

guided_partitioner

);</pre><aside class="m-note m-info"><h4>Note</h4>By default, parallel-transform tasks use <a href="namespacetf.html#a77d193108ae375fdfc554e7f10bea23e" class="m-doc">tf::DefaultPartitioner</a> if no partitioner is specified.</aside></section>

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Taskflow handbook is part of the <a href="https://taskflow.github.io">Taskflow project</a>, copyright © <a href="https://tsung-wei-huang.github.io/">Dr. Tsung-Wei Huang</a>, 2018–2023. Generated by <a href="https://doxygen.org/">Doxygen</a> 1.9.1 and <a href="https://mcss.mosra.cz/">m.css</a>.

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