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<span class="m-breadcrumb"><a href="cudaFlowAlgorithms.html">cudaFlow Algorithms</a> »</span>
Parallel Scan
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<h3>Contents</h3>
<ul>
<li><a href="#CUDAParallelScanIncludeTheHeader">Include the Header</a></li>
<li><a href="#cudaFlowScanARangeOfItems">Scan a Range of Items</a></li>
<li><a href="#cudaFlowScanTransformedItems">Scan a Range of Transformed Items</a></li>
<li><a href="#cudaFlowScanMiscellaneousItems">Miscellaneous Items</a></li>
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<p>cudaFlow provides template methods to create parallel scan tasks on a CUDA GPU.</p><section id="CUDAParallelScanIncludeTheHeader"><h2><a href="#CUDAParallelScanIncludeTheHeader">Include the Header</a></h2><p>You need to include the header file, <code>taskflow/cuda/algorithm/scan.hpp</code>, for creating a parallel-scan task.</p></section><section id="cudaFlowScanARangeOfItems"><h2><a href="#cudaFlowScanARangeOfItems">Scan a Range of Items</a></h2><p><a href="classtf_1_1cudaFlow.html#a062cc98a0b2d2199b50c3cbad16f5fb8" class="m-doc">tf::<wbr />cudaFlow::<wbr />inclusive_scan</a> computes an inclusive prefix sum operation using the given binary operator over a range of elements specified by <code>[first, last)</code>. The term "inclusive" means that the i-th input element is included in the i-th sum. The following code computes the inclusive prefix sum over an input array and stores the result in an output array.</p><pre class="m-code"><span class="k">const</span><span class="w"> </span><span class="kt">size_t</span><span class="w"> </span><span class="n">N</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">1000000</span><span class="p">;</span><span class="w"></span>
<span class="kt">int</span><span class="o">*</span><span class="w"> </span><span class="n">input</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">tf</span><span class="o">::</span><span class="n">cuda_malloc_shared</span><span class="o"><</span><span class="kt">int</span><span class="o">></span><span class="p">(</span><span class="n">N</span><span class="p">);</span><span class="w"> </span><span class="c1">// input vector</span>
<span class="kt">int</span><span class="o">*</span><span class="w"> </span><span class="n">output</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">tf</span><span class="o">::</span><span class="n">cuda_malloc_shared</span><span class="o"><</span><span class="kt">int</span><span class="o">></span><span class="p">(</span><span class="n">N</span><span class="p">);</span><span class="w"> </span><span class="c1">// output vector</span>
<span class="c1">// initializes the data</span>
<span class="k">for</span><span class="p">(</span><span class="kt">size_t</span><span class="w"> </span><span class="n">i</span><span class="o">=</span><span class="mi">0</span><span class="p">;</span><span class="w"> </span><span class="n">i</span><span class="o"><</span><span class="n">N</span><span class="p">;</span><span class="w"> </span><span class="n">input</span><span class="p">[</span><span class="n">i</span><span class="o">++</span><span class="p">]</span><span class="o">=</span><span class="n">rand</span><span class="p">());</span><span class="w"></span>
<span class="w"> </span>
<span class="c1">// creates a cudaFlow of one task to perform inclusive scan </span>
<span class="n">tf</span><span class="o">::</span><span class="n">cudaFlow</span><span class="w"> </span><span class="n">cf</span><span class="p">;</span><span class="w"></span>
<span class="n">tf</span><span class="o">::</span><span class="n">cudaTask</span><span class="w"> </span><span class="n">task</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">cf</span><span class="p">.</span><span class="n">inclusive_scan</span><span class="p">(</span><span class="w"></span>
<span class="w"> </span><span class="n">input</span><span class="p">,</span><span class="w"> </span><span class="n">input</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="n">N</span><span class="p">,</span><span class="w"> </span><span class="n">output</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="w"> </span><span class="n">a</span><span class="p">,</span><span class="w"> </span><span class="kt">int</span><span class="w"> </span><span class="n">b</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="n">a</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="n">b</span><span class="p">;</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
<span class="p">);</span><span class="w"></span>
<span class="n">cf</span><span class="p">.</span><span class="n">offload</span><span class="p">();</span><span class="w"></span>
<span class="c1">// verifies the result</span>
<span class="k">for</span><span class="p">(</span><span class="kt">size_t</span><span class="w"> </span><span class="n">i</span><span class="o">=</span><span class="mi">1</span><span class="p">;</span><span class="w"> </span><span class="n">i</span><span class="o"><</span><span class="n">N</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">assert</span><span class="p">(</span><span class="n">output</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="n">output</span><span class="p">[</span><span class="n">i</span><span class="mi">-1</span><span class="p">]</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="n">input</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>On the other hand, <a href="classtf_1_1cudaFlow.html#a8d59da7369a8634fea307219c7eb17c4" class="m-doc">tf::<wbr />cudaFlow::<wbr />exclusive_scan</a> computes an exclusive prefix sum operation. The term "exclusive" means that the i-th input element is <em>NOT</em> included in the i-th sum.</p><pre class="m-code"><span class="c1">// creates a cudaFlow of one task to perform exclusive scan </span>
<span class="n">tf</span><span class="o">::</span><span class="n">cudaFlow</span><span class="w"> </span><span class="n">cf</span><span class="p">;</span><span class="w"></span>
<span class="n">tf</span><span class="o">::</span><span class="n">cudaTask</span><span class="w"> </span><span class="n">task</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">cf</span><span class="p">.</span><span class="n">exclusive_scan</span><span class="p">(</span><span class="w"></span>
<span class="w"> </span><span class="n">input</span><span class="p">,</span><span class="w"> </span><span class="n">input</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="n">N</span><span class="p">,</span><span class="w"> </span><span class="n">output</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="w"> </span><span class="n">a</span><span class="p">,</span><span class="w"> </span><span class="kt">int</span><span class="w"> </span><span class="n">b</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="n">a</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="n">b</span><span class="p">;</span><span class="w"> </span><span class="p">}</span><span class="w"></span>
<span class="p">);</span><span class="w"></span>
<span class="n">cf</span><span class="p">.</span><span class="n">offload</span><span class="p">();</span><span class="w"></span>
<span class="c1">// verifies the result</span>
<span class="k">for</span><span class="p">(</span><span class="kt">size_t</span><span class="w"> </span><span class="n">i</span><span class="o">=</span><span class="mi">1</span><span class="p">;</span><span class="w"> </span><span class="n">i</span><span class="o"><</span><span class="n">N</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">assert</span><span class="p">(</span><span class="n">output</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="n">output</span><span class="p">[</span><span class="n">i</span><span class="mi">-1</span><span class="p">]</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="n">input</span><span class="p">[</span><span class="n">i</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="cudaFlowScanTransformedItems"><h2><a href="#cudaFlowScanTransformedItems">Scan a Range of Transformed Items</a></h2><p><a href="classtf_1_1cudaFlow.html#a5028579479a2393ce57ad37a7a809588" class="m-doc">tf::<wbr />cudaFlow::<wbr />transform_inclusive_scan</a> transforms each item in the range <code>[first, last)</code> and computes an inclusive prefix sum over these transformed items. The following code multiplies each item by 10 and then compute the inclusive prefix sum over 1000000 transformed items.</p><pre class="m-code"><span class="k">const</span><span class="w"> </span><span class="kt">size_t</span><span class="w"> </span><span class="n">N</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">1000000</span><span class="p">;</span><span class="w"></span>
<span class="kt">int</span><span class="o">*</span><span class="w"> </span><span class="n">input</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">tf</span><span class="o">::</span><span class="n">cuda_malloc_shared</span><span class="o"><</span><span class="kt">int</span><span class="o">></span><span class="p">(</span><span class="n">N</span><span class="p">);</span><span class="w"> </span><span class="c1">// input vector</span>
<span class="kt">int</span><span class="o">*</span><span class="w"> </span><span class="n">output</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">tf</span><span class="o">::</span><span class="n">cuda_malloc_shared</span><span class="o"><</span><span class="kt">int</span><span class="o">></span><span class="p">(</span><span class="n">N</span><span class="p">);</span><span class="w"> </span><span class="c1">// output vector</span>
<span class="c1">// initializes the data</span>
<span class="k">for</span><span class="p">(</span><span class="kt">size_t</span><span class="w"> </span><span class="n">i</span><span class="o">=</span><span class="mi">0</span><span class="p">;</span><span class="w"> </span><span class="n">i</span><span class="o"><</span><span class="n">N</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="w"> </span><span class="n">input</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">rand</span><span class="p">();</span><span class="w"></span>
<span class="p">}</span><span class="w"> </span>
<span class="c1">// creates a cudaFlow of one task to inclusively scan over transformed input </span>
<span class="n">tf</span><span class="o">::</span><span class="n">cudaFlow</span><span class="w"> </span><span class="n">cf</span><span class="p">;</span><span class="w"></span>
<span class="n">tf</span><span class="o">::</span><span class="n">cudaTask</span><span class="w"> </span><span class="n">task</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">cf</span><span class="p">.</span><span class="n">transform_inclusive_scan</span><span class="p">(</span><span class="w"></span>
<span class="w"> </span><span class="n">input</span><span class="p">,</span><span class="w"> </span><span class="n">input</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="n">N</span><span class="p">,</span><span class="w"> </span><span class="n">output</span><span class="p">,</span><span class="w"> </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="w"> </span><span class="n">a</span><span class="p">,</span><span class="w"> </span><span class="kt">int</span><span class="w"> </span><span class="n">b</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="n">a</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="n">b</span><span class="p">;</span><span class="w"> </span><span class="p">},</span><span class="w"> </span><span class="c1">// binary scan operator</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="w"> </span><span class="n">a</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="n">a</span><span class="o">*</span><span class="mi">10</span><span class="p">;</span><span class="w"> </span><span class="p">}</span><span class="w"> </span><span class="c1">// unary transform operator</span>
<span class="p">);</span><span class="w"></span>
<span class="n">cf</span><span class="p">.</span><span class="n">offload</span><span class="p">();</span><span class="w"></span>
<span class="c1">// verifies the result</span>
<span class="k">for</span><span class="p">(</span><span class="kt">size_t</span><span class="w"> </span><span class="n">i</span><span class="o">=</span><span class="mi">1</span><span class="p">;</span><span class="w"> </span><span class="n">i</span><span class="o"><</span><span class="n">N</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">assert</span><span class="p">(</span><span class="n">output</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="n">output</span><span class="p">[</span><span class="n">i</span><span class="mi">-1</span><span class="p">]</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="n">input</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="mi">10</span><span class="p">);</span><span class="w"></span>
<span class="p">}</span><span class="w"></span></pre><p>Similarly, <a href="classtf_1_1cudaFlow.html#ae80df494109b0dc6db77111917207e6b" class="m-doc">tf::<wbr />cudaFlow::<wbr />transform_exclusive_scan</a> performs an exclusive prefix sum over a range of transformed items. The following code computes the exclusive prefix sum over 1000000 transformed items each multipled by 10.</p><pre class="m-code"><span class="k">const</span><span class="w"> </span><span class="kt">size_t</span><span class="w"> </span><span class="n">N</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="mi">1000000</span><span class="p">;</span><span class="w"></span>
<span class="kt">int</span><span class="o">*</span><span class="w"> </span><span class="n">input</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">tf</span><span class="o">::</span><span class="n">cuda_malloc_shared</span><span class="o"><</span><span class="kt">int</span><span class="o">></span><span class="p">(</span><span class="n">N</span><span class="p">);</span><span class="w"> </span><span class="c1">// input vector</span>
<span class="kt">int</span><span class="o">*</span><span class="w"> </span><span class="n">output</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">tf</span><span class="o">::</span><span class="n">cuda_malloc_shared</span><span class="o"><</span><span class="kt">int</span><span class="o">></span><span class="p">(</span><span class="n">N</span><span class="p">);</span><span class="w"> </span><span class="c1">// output vector</span>
<span class="c1">// initializes the data</span>
<span class="k">for</span><span class="p">(</span><span class="kt">size_t</span><span class="w"> </span><span class="n">i</span><span class="o">=</span><span class="mi">0</span><span class="p">;</span><span class="w"> </span><span class="n">i</span><span class="o"><</span><span class="n">N</span><span class="p">;</span><span class="w"> </span><span class="n">input</span><span class="p">[</span><span class="n">i</span><span class="o">++</span><span class="p">]</span><span class="o">=</span><span class="n">rand</span><span class="p">());</span><span class="w"> </span>
<span class="c1">// creates a cudaFlow of one task to exclusively scan over transformed input </span>
<span class="n">tf</span><span class="o">::</span><span class="n">cudaFlow</span><span class="w"> </span><span class="n">cf</span><span class="p">;</span><span class="w"></span>
<span class="n">tf</span><span class="o">::</span><span class="n">cudaTask</span><span class="w"> </span><span class="n">task</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="n">cf</span><span class="p">.</span><span class="n">transform_exclusive_scan</span><span class="p">(</span><span class="w"></span>
<span class="w"> </span><span class="n">input</span><span class="p">,</span><span class="w"> </span><span class="n">input</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="n">N</span><span class="p">,</span><span class="w"> </span><span class="n">output</span><span class="p">,</span><span class="w"> </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="w"> </span><span class="n">a</span><span class="p">,</span><span class="w"> </span><span class="kt">int</span><span class="w"> </span><span class="n">b</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="n">a</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="n">b</span><span class="p">;</span><span class="w"> </span><span class="p">},</span><span class="w"> </span><span class="c1">// binary scan operator</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="w"> </span><span class="n">a</span><span class="p">)</span><span class="w"> </span><span class="p">{</span><span class="w"> </span><span class="k">return</span><span class="w"> </span><span class="n">a</span><span class="o">*</span><span class="mi">10</span><span class="p">;</span><span class="w"> </span><span class="p">}</span><span class="w"> </span><span class="c1">// unary transform operator</span>
<span class="p">);</span><span class="w"></span>
<span class="n">cf</span><span class="p">.</span><span class="n">offload</span><span class="p">();</span><span class="w"></span>
<span class="c1">// verifies the result</span>
<span class="k">for</span><span class="p">(</span><span class="kt">size_t</span><span class="w"> </span><span class="n">i</span><span class="o">=</span><span class="mi">1</span><span class="p">;</span><span class="w"> </span><span class="n">i</span><span class="o"><</span><span class="n">N</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">assert</span><span class="p">(</span><span class="n">output</span><span class="p">[</span><span class="n">i</span><span class="p">]</span><span class="w"> </span><span class="o">==</span><span class="w"> </span><span class="n">output</span><span class="p">[</span><span class="n">i</span><span class="mi">-1</span><span class="p">]</span><span class="w"> </span><span class="o">+</span><span class="w"> </span><span class="n">input</span><span class="p">[</span><span class="n">i</span><span class="mi">-1</span><span class="p">]</span><span class="w"> </span><span class="o">*</span><span class="w"> </span><span class="mi">10</span><span class="p">);</span><span class="w"></span>
<span class="p">}</span><span class="w"></span></pre></section><section id="cudaFlowScanMiscellaneousItems"><h2><a href="#cudaFlowScanMiscellaneousItems">Miscellaneous Items</a></h2><p>Parallel scan algorithms are also available in <a href="classtf_1_1cudaFlowCapturer.html" class="m-doc">tf::<wbr />cudaFlowCapturer</a> with the same API.</p></section>
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