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<compounddef id="CUDASTDTransform" kind="page">

<compoundname>CUDASTDTransform</compoundname>

<title>Parallel Transforms</title>

<tableofcontents>

<tocsect>

<name>Include the Header</name>

<reference>CUDASTDTransform_1CUDASTDParallelTransformsIncludeTheHeader</reference>

</tocsect>

<tocsect>

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

<reference>CUDASTDTransform_1CUDASTDTransformARangeOfItems</reference>

</tocsect>

<tocsect>

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

<reference>CUDASTDTransform_1CUDASTDTransformTwoRangesOfItems</reference>

</tocsect>

</tableofcontents>

<briefdescription>

</briefdescription>

<detaileddescription>

<para>Taskflow provides template methods for transforming ranges of items to different outputs.</para>

<sect1 id="CUDASTDTransform_1CUDASTDParallelTransformsIncludeTheHeader">

<title>Include the Header</title>

<para>You need to include the header file, <computeroutput>taskflow/cuda/algorithm/transform.hpp</computeroutput>, for using the parallel-transform algorithm.</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="CUDASTDTransform_1CUDASTDTransformARangeOfItems">

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

<para>Parallel-transform algorithm 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="namespacetf_1a3ed764530620a419e3400e1f9ab6c956" kindref="member">tf::cuda_transform(P&amp;&amp; p, 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="normal"><ref refid="classtf_1_1cudaExecutionPolicy" kindref="compound">tf::cudaDefaultExecutionPolicy</ref><sp/>policy;</highlight></codeline>

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

<codeline><highlight class="normal"></highlight><highlight class="comment">//<sp/>output[i]<sp/>=<sp/>input[i]*10</highlight><highlight class="normal"></highlight></codeline>

<codeline><highlight class="normal"><ref refid="namespacetf_1a3ed764530620a419e3400e1f9ab6c956" kindref="member">tf::cuda_transform</ref>(</highlight></codeline>

<codeline><highlight class="normal"><sp/><sp/>policy,<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*10;<sp/>}</highlight></codeline>

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

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

<codeline><highlight class="normal"></highlight><highlight class="comment">//<sp/>synchronize<sp/>the<sp/>execution</highlight><highlight class="normal"></highlight></codeline>

<codeline><highlight class="normal">policy.synchronize();</highlight></codeline>

</programlisting></para>

<para>Each iteration is independent of each other and is assigned one kernel thread to run the callable. The transform algorithm runs <emphasis>asynchronously</emphasis> through the stream specified in the execution policy. You need to synchronize the stream to obtain correct results.</para>

</sect1>

<sect1 id="CUDASTDTransform_1CUDASTDTransformTwoRangesOfItems">

<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="namespacetf_1abdcb5b755f7ace2aa452541d5bf93b5f" kindref="member">tf::cuda_transform(P&amp;&amp; p, 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="normal"><ref refid="classtf_1_1cudaExecutionPolicy" kindref="compound">tf::cudaDefaultExecutionPolicy</ref><sp/>policy;</highlight></codeline>

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

<codeline><highlight class="normal"></highlight><highlight class="comment">//<sp/>output[i]<sp/>=<sp/>input1[i]<sp/>+<sp/>inpu2[i]</highlight><highlight class="normal"></highlight></codeline>

<codeline><highlight class="normal"><ref refid="namespacetf_1a3ed764530620a419e3400e1f9ab6c956" kindref="member">tf::cuda_transform</ref>(policy,</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>

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

<codeline><highlight class="normal"></highlight><highlight class="comment">//<sp/>synchronize<sp/>the<sp/>execution</highlight><highlight class="normal"></highlight></codeline>

<codeline><highlight class="normal">policy.synchronize();</highlight></codeline>

</programlisting> </para>

</sect1>

</detaileddescription>

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