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<compoundname>ParallelTransformsCUDA</compoundname>

<title>Parallel Transforms</title>

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<briefdescription>

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<detaileddescription>

<para><ref refid="classtf_1_1cudaFlow" kindref="compound">tf::cudaFlow</ref> provides template methods for transforming ranges of items to different outputs.</para><sect1 id="ParallelTransformsCUDA_1CUDAParallelTransformsIncludeTheHeader">

<title>Include the Header</title>

<para>You need to include the header file, <computeroutput>taskflow/cuda/algorithm/transform.hpp</computeroutput>, for creating a parallel-transform task.</para><para><programlisting filename=".cpp"><codeline><highlight class="preprocessor">#include<sp/>&lt;<ref refid="transform_8hpp" kindref="compound">taskflow/cuda/algorithm/transform.hpp</ref>&gt;</highlight></codeline>

</programlisting></para></sect1>

<sect1 id="ParallelTransformsCUDA_1cudaFlowTransformARangeOfItems">

<title>Transform a Range of Items</title>

<para>Iterator-based parallel-transform applies the given transform function to a range of items and store the result in another range specified by two iterators, <computeroutput>first</computeroutput> and <computeroutput>last</computeroutput>. The task created by <ref refid="classtf_1_1cudaFlow_1af89a9bda182272462a0eda2581536cd8" kindref="member">tf::cudaFlow::transform(I first, I last, O output, C op)</ref> represents a parallel execution for the following loop:</para><para><programlisting filename=".cpp"><codeline><highlight class="keywordflow">while</highlight><highlight class="normal"><sp/>(first<sp/>!=<sp/>last)<sp/>{</highlight></codeline>

<codeline><highlight class="normal"><sp/><sp/>*output++<sp/>=<sp/>op(*first++);</highlight></codeline>

<codeline><highlight class="normal">}</highlight></codeline>

</programlisting></para><para>The following example creates a transform kernel that transforms an input range of <computeroutput>N</computeroutput> items to an output range by multiplying each item by 10.</para><para><programlisting filename=".cpp"><codeline><highlight class="comment">//<sp/>output[i]<sp/>=<sp/>input[i]<sp/>*<sp/>10</highlight><highlight class="normal"></highlight></codeline>

<codeline><highlight class="normal">cudaflow.<ref refid="classtf_1_1cudaFlow_1af89a9bda182272462a0eda2581536cd8" kindref="member">transform</ref>(</highlight></codeline>

<codeline><highlight class="normal"><sp/><sp/>input,<sp/>input<sp/>+<sp/>N,<sp/>output,<sp/>[]<sp/>__device__<sp/>(</highlight><highlight class="keywordtype">int</highlight><highlight class="normal"><sp/>x)<sp/>{<sp/></highlight><highlight class="keywordflow">return</highlight><highlight class="normal"><sp/>x<sp/>*<sp/>10;<sp/>}</highlight></codeline>

<codeline><highlight class="normal">);<sp/></highlight></codeline>

</programlisting></para><para>Each iteration is independent of each other and is assigned one kernel thread to run the callable. Since the callable runs on GPU, it must be declared with a <computeroutput>__device__</computeroutput> specifier.</para></sect1>

<sect1 id="ParallelTransformsCUDA_1cudaFlowTransformTwoRangesOfItems">

<title>Transform Two Ranges of Items</title>

<para>You can transform two ranges of items to an output range through a binary operator. The task created by <ref refid="classtf_1_1cudaFlow_1abab2bfdfc86ef3a764ece4743fdede76" kindref="member">tf::cudaFlow::transform(I1 first1, I1 last1, I2 first2, O output, C op)</ref> represents a parallel execution for the following loop:</para><para><programlisting filename=".cpp"><codeline><highlight class="keywordflow">while</highlight><highlight class="normal"><sp/>(first1<sp/>!=<sp/>last1)<sp/>{</highlight></codeline>

<codeline><highlight class="normal"><sp/><sp/>*output++<sp/>=<sp/>op(*first1++,<sp/>*first2++);</highlight></codeline>

<codeline><highlight class="normal">}</highlight></codeline>

</programlisting></para><para>The following example creates a transform kernel that transforms two input ranges of <computeroutput>N</computeroutput> items to an output range by summing each pair of items in the input ranges.</para><para><programlisting filename=".cpp"><codeline><highlight class="comment">//<sp/>output[i]<sp/>=<sp/>input1[i]<sp/>+<sp/>inpu2[i]</highlight><highlight class="normal"></highlight></codeline>

<codeline><highlight class="normal">cudaflow.<ref refid="classtf_1_1cudaFlow_1af89a9bda182272462a0eda2581536cd8" kindref="member">transform</ref>(</highlight></codeline>

<codeline><highlight class="normal"><sp/><sp/>input1,<sp/>input1+N,<sp/>input2,<sp/>output,<sp/>[]__device__(</highlight><highlight class="keywordtype">int</highlight><highlight class="normal"><sp/>a,<sp/></highlight><highlight class="keywordtype">int</highlight><highlight class="normal"><sp/>b)<sp/>{<sp/></highlight><highlight class="keywordflow">return</highlight><highlight class="normal"><sp/>a+b;<sp/>}</highlight></codeline>

<codeline><highlight class="normal">);<sp/></highlight></codeline>

</programlisting></para></sect1>

<sect1 id="ParallelTransformsCUDA_1ParallelTransformCUDAMiscellaneousItems">

<title>Miscellaneous Items</title>

<para>The parallel-transform algorithms are also available in <ref refid="classtf_1_1cudaFlowCapturer" kindref="compound">tf::cudaFlowCapturer</ref>. </para></sect1>

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