<!DOCTYPE html><html lang="en"><head><meta charset="UTF-8" /><title>cudaFlow Algorithms » Parallel Iterations | Taskflow QuickStart</title><link rel="stylesheet" href="https://fonts.googleapis.com/css?family=Source+Sans+Pro:400,400i,600,600i%7CSource+Code+Pro:400,400i,600" /><link rel="stylesheet" href="m-dark+documentation.compiled.css" /><link rel="icon" href="favicon.ico" type="image/vnd.microsoft.icon" /><meta name="viewport" content="width=device-width, initial-scale=1.0" /><meta name="theme-color" content="#22272e" /></head><body><header><nav id="navigation"><div class="m-container"><div class="m-row"><span id="m-navbar-brand" class="m-col-t-8 m-col-m-none m-left-m"><a href="https://taskflow.github.io"><img src="taskflow_logo.png" alt="" />Taskflow</a> <span class="m-breadcrumb">|</span> <a href="index.html" class="m-thin">QuickStart</a></span><div class="m-col-t-4 m-hide-m m-text-right m-nopadr"><a href="#search" class="m-doc-search-icon" title="Search" onclick="return showSearch()"><svg style="height: 0.9rem;" viewBox="0 0 16 16"><path id="m-doc-search-icon-path" d="m6 0c-3.31 0-6 2.69-6 6 0 3.31 2.69 6 6 6 1.49 0 2.85-0.541 3.89-1.44-0.0164 0.338 0.147 0.759 0.5 1.15l3.22 3.79c0.552 0.614 1.45 0.665 2 0.115 0.55-0.55 0.499-1.45-0.115-2l-3.79-3.22c-0.392-0.353-0.812-0.515-1.15-0.5 0.895-1.05 1.44-2.41 1.44-3.89 0-3.31-2.69-6-6-6zm0 1.56a4.44 4.44 0 0 1 4.44 4.44 4.44 4.44 0 0 1-4.44 4.44 4.44 4.44 0 0 1-4.44-4.44 4.44 4.44 0 0 1 4.44-4.44z"/></svg></a><a id="m-navbar-show" href="#navigation" title="Show navigation"></a><a id="m-navbar-hide" href="#" title="Hide navigation"></a></div><div id="m-navbar-collapse" class="m-col-t-12 m-show-m m-col-m-none m-right-m"><div class="m-row"><ol class="m-col-t-6 m-col-m-none"><li><a href="pages.html">Handbook</a></li><li><a href="namespaces.html">Namespaces</a></li></ol><ol class="m-col-t-6 m-col-m-none" start="3"><li><a href="annotated.html">Classes</a></li><li><a href="files.html">Files</a></li><li class="m-show-m"><a href="#search" class="m-doc-search-icon" title="Search" onclick="return showSearch()"><svg style="height: 0.9rem;" viewBox="0 0 16 16"><use href="#m-doc-search-icon-path" /></svg></a></li></ol></div></div></div></div></nav></header><main><article><div class="m-container m-container-inflatable"><div class="m-row"><div class="m-col-l-10 m-push-l-1"><h1><span class="m-breadcrumb"><a href="cudaFlowAlgorithms.html">cudaFlow Algorithms</a> »</span>Parallel Iterations</h1><nav class="m-block m-default"><h3>Contents</h3><ul><li><a href="#CUDAForEachIncludeTheHeader">Include the Header</a></li><li><a href="#ForEachCUDAIndexBasedParallelFor">Index-based Parallel Iterations</a></li><li><a href="#ForEachCUDAIteratorBasedParallelIterations">Iterator-based Parallel Iterations</a></li><li><a href="#ForEachCUDAMiscellaneousItems">Miscellaneous Items</a></li></ul></nav><p><a href="classtf_1_1cudaFlow.html" class="m-doc">tf::<wbr />cudaFlow</a> provides two template methods, <a href="classtf_1_1cudaFlow.html#a1a681f6223853b6445dcfdad07e4d0fd" class="m-doc">tf::<wbr />cudaFlow::<wbr />for_each</a> and <a href="classtf_1_1cudaFlow.html#a34f1ea89e5651faa6e8af522a42556ac" class="m-doc">tf::<wbr />cudaFlow::<wbr />for_each_index</a>, for creating tasks to perform parallel iterations over a range of items.</p><section id="CUDAForEachIncludeTheHeader"><h2><a href="#CUDAForEachIncludeTheHeader">Include the Header</a></h2><p>You need to include the header file, <code>taskflow/cuda/algorithm/for_each.hpp</code>, for creating a parallel-iteration task.</p><pre class="m-code"><span class="cp">#include</span><span class="w"> </span><span class="cpf"><taskflow/cuda/algorithm/for_each.hpp></span><span class="cp"></span></pre></section><section id="ForEachCUDAIndexBasedParallelFor"><h2><a href="#ForEachCUDAIndexBasedParallelFor">Index-based Parallel Iterations</a></h2><p>Index-based parallel-for performs parallel iterations over a range <code>[first, last)</code> with the given <code>step</code> size. The task created by <a href="classtf_1_1cudaFlow.html#a34f1ea89e5651faa6e8af522a42556ac" class="m-doc">tf::<wbr />cudaFlow::<wbr />for_each_index(I first, I last, I step, C callable)</a> represents a kernel of parallel execution for the following loop:</p><pre class="m-code"><span class="c1">// positive step: first, first+step, first+2*step, ...</span><span class="k">for</span><span class="p">(</span><span class="k">auto</span><span class="w"> </span><span class="n">i</span><span class="o">=</span><span class="n">first</span><span class="p">;</span><span class="w"> </span><span class="n">i</span><span class="o"><</span><span class="n">last</span><span class="p">;</span><span class="w"> </span><span class="n">i</span><span class="o">+=</span><span class="n">step</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span><span class="w"> </span><span class="n">callable</span><span class="p">(</span><span class="n">i</span><span class="p">);</span><span class="w"></span><span class="p">}</span><span class="w"></span><span class="c1">// negative step: first, first-step, first-2*step, ...</span><span class="k">for</span><span class="p">(</span><span class="k">auto</span><span class="w"> </span><span class="n">i</span><span class="o">=</span><span class="n">first</span><span class="p">;</span><span class="w"> </span><span class="n">i</span><span class="o">></span><span class="n">last</span><span class="p">;</span><span class="w"> </span><span class="n">i</span><span class="o">+=</span><span class="n">step</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span><span class="w"> </span><span class="n">callable</span><span class="p">(</span><span class="n">i</span><span class="p">);</span><span class="w"></span><span class="p">}</span><span class="w"></span></pre><p>Each iteration <code>i</code> 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 <code>__device__</code> specifier. The following example creates a kernel that assigns each entry of <code>gpu_data</code> to 1 over the range [0, 100) with step size 1.</p><pre class="m-code"><span class="c1">// assigns each element in gpu_data to 1 over the range [0, 100) with step size 1</span><span class="n">cudaflow</span><span class="p">.</span><span class="n">for_each_index</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="w"> </span><span class="mi">100</span><span class="p">,</span><span class="w"> </span><span class="mi">1</span><span class="p">,</span><span class="w"> </span><span class="p">[</span><span class="n">gpu_data</span><span class="p">]</span><span class="w"> </span><span class="n">__device__</span><span class="w"> </span><span class="p">(</span><span class="kt">int</span><span class="w"> </span><span class="n">idx</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span><span class="w"> </span><span class="n">gpu_data</span><span class="p">[</span><span class="n">idx</span><span class="p">]</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">1</span><span class="p">;</span><span class="w"></span><span class="p">});</span><span class="w"></span></pre></section><section id="ForEachCUDAIteratorBasedParallelIterations"><h2><a href="#ForEachCUDAIteratorBasedParallelIterations">Iterator-based Parallel Iterations</a></h2><p>Iterator-based parallel-for performs parallel iterations over a range specified by two STL-styled iterators, <code>first</code> and <code>last</code>. The task created by <a href="classtf_1_1cudaFlow.html#a1a681f6223853b6445dcfdad07e4d0fd" class="m-doc">tf::<wbr />cudaFlow::<wbr />for_each(I first, I last, C callable)</a> represents a parallel execution of the following loop:</p><pre class="m-code"><span class="k">for</span><span class="p">(</span><span class="k">auto</span><span class="w"> </span><span class="n">i</span><span class="o">=</span><span class="n">first</span><span class="p">;</span><span class="w"> </span><span class="n">i</span><span class="o"><</span><span class="n">last</span><span class="p">;</span><span class="w"> </span><span class="n">i</span><span class="o">++</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span><span class="w"> </span><span class="n">callable</span><span class="p">(</span><span class="o">*</span><span class="n">i</span><span class="p">);</span><span class="w"></span><span class="p">}</span><span class="w"></span></pre><p>The two iterators, <code>first</code> and <code>last</code>, are typically two raw pointers to the first element and the next to the last element in the range in GPU memory space. The following example creates a <code>for_each</code> kernel that assigns each element in <code>gpu_data</code> to 1 over the range <code>[gpu_data, gpu_data + 1000)</code>.</p><pre class="m-code"><span class="c1">// assigns each element to 1 over the range [gpu_data, gpu_data + 1000)</span><span class="n">cudaflow</span><span class="p">.</span><span class="n">for_each</span><span class="p">(</span><span class="n">gpu_data</span><span class="p">,</span><span class="w"> </span><span class="n">gpu_data</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="mi">1000</span><span class="p">,</span><span class="w"> </span><span class="p">[]</span><span class="w"> </span><span class="n">__device__</span><span class="w"> </span><span class="p">(</span><span class="kt">int</span><span class="o">&</span><span class="w"> </span><span class="n">item</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"></span><span class="w"> </span><span class="n">item</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">1</span><span class="p">;</span><span class="w"></span><span class="p">});</span><span class="w"> </span></pre><p>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 <code>__device__</code> specifier.</p></section><section id="ForEachCUDAMiscellaneousItems"><h2><a href="#ForEachCUDAMiscellaneousItems">Miscellaneous Items</a></h2><p>The parallel-iteration algorithms are also available in <a href="classtf_1_1cudaFlowCapturer.html#a0b2f1bcd59f0b42e0f823818348b4ae7" class="m-doc">tf::<wbr />cudaFlowCapturer::<wbr />for_each</a> and <a href="classtf_1_1cudaFlowCapturer.html#aeb877f42ee3a627c40f1c9c84e31ba3c" class="m-doc">tf::<wbr />cudaFlowCapturer::<wbr />for_each_index</a>.</p></section></div></div></div></article></main><div class="m-doc-search" id="search"><a href="#!" onclick="return hideSearch()"></a><div class="m-container"><div class="m-row"><div class="m-col-m-8 m-push-m-2"><div class="m-doc-search-header m-text m-small"><div><span class="m-label m-default">Tab</span> / <span class="m-label m-default">T</span> to search, <span class="m-label m-default">Esc</span> to close</div><div id="search-symbolcount">…</div></div><div class="m-doc-search-content"><form><input type="search" name="q" id="search-input" placeholder="Loading …" disabled="disabled" autofocus="autofocus" autocomplete="off" spellcheck="false" /></form><noscript class="m-text m-danger m-text-center">Unlike everything else in the docs, the search functionality <em>requires</em> JavaScript.</noscript><div id="search-help" class="m-text m-dim m-text-center"><p class="m-noindent">Search for symbols, directories, files, pages ormodules. 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