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<h1>
<span class="m-breadcrumb"><a href="cudaStandardAlgorithms.html">CUDA Standard Algorithms</a> »</span>
Parallel Scan
</h1>
<div class="m-block m-default">
<h3>Contents</h3>
<ul>
<li><a href="#CUDASTDParallelScanIncludeTheHeader">Include the Header</a></li>
<li><a href="#CUDASTDScanItems">Scan a Range of Items</a></li>
<li><a href="#CUDASTDScanTransformedItems">Scan a Range of Transformed Items</a></li>
</ul>
</div>
<p>Taskflow provides standard template methods for scanning a range of items on a CUDA GPU.</p><section id="CUDASTDParallelScanIncludeTheHeader"><h2><a href="#CUDASTDParallelScanIncludeTheHeader">Include the Header</a></h2><p>You need to include the header file, <code>taskflow/cuda/algorithm/scan.hpp</code>, for using the parallel-scan algorithm.</p></section><section id="CUDASTDScanItems"><h2><a href="#CUDASTDScanItems">Scan a Range of Items</a></h2><p><a href="namespacetf.html#a2e1b44c84a09e0a8495a611cb9a7ea40" class="m-doc">tf::<wbr />cuda_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="kt">size_t</span> <span class="n">N</span> <span class="o">=</span> <span class="mi">1000000</span><span class="p">;</span>
<span class="kt">int</span><span class="o">*</span> <span class="n">input</span> <span class="o">=</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="c1">// input vector</span>
<span class="kt">int</span><span class="o">*</span> <span class="n">output</span> <span class="o">=</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="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="n">i</span><span class="o">=</span><span class="mi">0</span><span class="p">;</span> <span class="n">i</span><span class="o"><</span><span class="n">N</span><span class="p">;</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="c1">// queries the required buffer size to scan N elements using the given policy</span>
<span class="n">tf</span><span class="o">::</span><span class="n">cudaDefaultExecutionPolicy</span> <span class="n">policy</span><span class="p">;</span>
<span class="k">auto</span> <span class="n">bytes</span> <span class="o">=</span> <span class="n">tf</span><span class="o">::</span><span class="n">cuda_scan_buffer_size</span><span class="o"><</span><span class="n">tf</span><span class="o">::</span><span class="n">cudaDefaultExecutionPolicy</span><span class="p">,</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="k">auto</span> <span class="n">buffer</span> <span class="o">=</span> <span class="n">tf</span><span class="o">::</span><span class="n">cuda_malloc_device</span><span class="o"><</span><span class="n">std</span><span class="o">::</span><span class="n">byte</span><span class="o">></span><span class="p">(</span><span class="n">bytes</span><span class="p">);</span>
<span class="c1">// computes inclusive scan over input and stores the result in output</span>
<span class="n">tf</span><span class="o">::</span><span class="n">cuda_inclusive_scan</span><span class="p">(</span><span class="n">policy</span><span class="p">,</span>
<span class="n">input</span><span class="p">,</span> <span class="n">input</span> <span class="o">+</span> <span class="n">N</span><span class="p">,</span> <span class="n">output</span><span class="p">,</span> <span class="p">[]</span> <span class="n">__device__</span> <span class="p">(</span><span class="kt">int</span> <span class="n">a</span><span class="p">,</span> <span class="kt">int</span> <span class="n">b</span><span class="p">)</span> <span class="p">{</span><span class="k">return</span> <span class="n">a</span> <span class="o">+</span> <span class="n">b</span><span class="p">;},</span> <span class="n">buffer</span>
<span class="p">);</span>
<span class="c1">// synchronizes and verifies the result</span>
<span class="n">policy</span><span class="p">.</span><span class="n">synchronize</span><span class="p">();</span>
<span class="k">for</span><span class="p">(</span><span class="kt">size_t</span> <span class="n">i</span><span class="o">=</span><span class="mi">1</span><span class="p">;</span> <span class="n">i</span><span class="o"><</span><span class="n">N</span><span class="p">;</span> <span class="n">i</span><span class="o">++</span><span class="p">)</span> <span class="p">{</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="o">==</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="o">+</span> <span class="n">input</span><span class="p">[</span><span class="n">i</span><span class="p">]);</span>
<span class="p">}</span>
<span class="c1">// delete the buffer</span>
<span class="n">tf</span><span class="o">::</span><span class="n">cuda_free</span><span class="p">(</span><span class="n">buffer</span><span class="p">);</span></pre><p>The scan algorithm runs <em>asynchronously</em> through the stream specified in the execution policy. You need to synchronize the stream to obtain correct results. Since the GPU scan algorithm may require extra buffer to store the temporary results, you must provide a buffer of size at least bytes returned from <a href="namespacetf.html#afd7e7a0886352201cced5c55205f3229" class="m-doc">tf::<wbr />cuda_scan_buffer_size</a>.</p><aside class="m-note m-warning"><h4>Attention</h4><p>You must keep the buffer alive before the scan call completes.</p></aside><p>On the other hand, <a href="namespacetf.html#aeb391c40120844318fd715b8c3a716bb" class="m-doc">tf::<wbr />cuda_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">// computes exclusive scan over input and stores the result in output</span>
<span class="n">tf</span><span class="o">::</span><span class="n">cuda_exclusive_scan</span><span class="p">(</span><span class="n">policy</span><span class="p">,</span>
<span class="n">input</span><span class="p">,</span> <span class="n">input</span> <span class="o">+</span> <span class="n">N</span><span class="p">,</span> <span class="n">output</span><span class="p">,</span> <span class="p">[]</span> <span class="n">__device__</span> <span class="p">(</span><span class="kt">int</span> <span class="n">a</span><span class="p">,</span> <span class="kt">int</span> <span class="n">b</span><span class="p">)</span> <span class="p">{</span><span class="k">return</span> <span class="n">a</span> <span class="o">+</span> <span class="n">b</span><span class="p">;},</span> <span class="n">buffer</span>
<span class="p">);</span>
<span class="c1">// synchronizes the execution and verifies the result</span>
<span class="n">policy</span><span class="p">.</span><span class="n">synchronize</span><span class="p">();</span>
<span class="k">for</span><span class="p">(</span><span class="kt">size_t</span> <span class="n">i</span><span class="o">=</span><span class="mi">1</span><span class="p">;</span> <span class="n">i</span><span class="o"><</span><span class="n">N</span><span class="p">;</span> <span class="n">i</span><span class="o">++</span><span class="p">)</span> <span class="p">{</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="o">==</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="o">+</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="p">}</span></pre></section><section id="CUDASTDScanTransformedItems"><h2><a href="#CUDASTDScanTransformedItems">Scan a Range of Transformed Items</a></h2><p><a href="namespacetf.html#afa4aa760ddb6efbda1b9bab505ad5baf" class="m-doc">tf::<wbr />cuda_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="kt">size_t</span> <span class="n">N</span> <span class="o">=</span> <span class="mi">1000000</span><span class="p">;</span>
<span class="kt">int</span><span class="o">*</span> <span class="n">input</span> <span class="o">=</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="c1">// input vector</span>
<span class="kt">int</span><span class="o">*</span> <span class="n">output</span> <span class="o">=</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="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="n">i</span><span class="o">=</span><span class="mi">0</span><span class="p">;</span> <span class="n">i</span><span class="o"><</span><span class="n">N</span><span class="p">;</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="c1">// queries the required buffer size to scan N elements using the given policy</span>
<span class="n">tf</span><span class="o">::</span><span class="n">cudaDefaultExecutionPolicy</span> <span class="n">policy</span><span class="p">;</span>
<span class="k">auto</span> <span class="n">bytes</span> <span class="o">=</span> <span class="n">tf</span><span class="o">::</span><span class="n">cuda_scan_buffer_size</span><span class="o"><</span><span class="n">tf</span><span class="o">::</span><span class="n">cudaDefaultExecutionPolicy</span><span class="p">,</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="k">auto</span> <span class="n">buffer</span> <span class="o">=</span> <span class="n">tf</span><span class="o">::</span><span class="n">cuda_malloc_device</span><span class="o"><</span><span class="n">std</span><span class="o">::</span><span class="n">byte</span><span class="o">></span><span class="p">(</span><span class="n">bytes</span><span class="p">);</span>
<span class="c1">// computes inclusive scan over transformed input and stores the result in output</span>
<span class="n">tf</span><span class="o">::</span><span class="n">cuda_transform_inclusive_scan</span><span class="p">(</span><span class="n">policy</span><span class="p">,</span>
<span class="n">input</span><span class="p">,</span> <span class="n">input</span> <span class="o">+</span> <span class="n">N</span><span class="p">,</span> <span class="n">output</span><span class="p">,</span>
<span class="p">[]</span> <span class="n">__device__</span> <span class="p">(</span><span class="kt">int</span> <span class="n">a</span><span class="p">,</span> <span class="kt">int</span> <span class="n">b</span><span class="p">)</span> <span class="p">{</span> <span class="k">return</span> <span class="n">a</span> <span class="o">+</span> <span class="n">b</span><span class="p">;</span> <span class="p">},</span> <span class="c1">// binary scan operator</span>
<span class="p">[]</span> <span class="n">__device__</span> <span class="p">(</span><span class="kt">int</span> <span class="n">a</span><span class="p">)</span> <span class="p">{</span> <span class="k">return</span> <span class="n">a</span><span class="o">*</span><span class="mi">10</span><span class="p">;</span> <span class="p">},</span> <span class="c1">// unary transform operator</span>
<span class="n">buffer</span>
<span class="p">);</span>
<span class="n">policy</span><span class="p">.</span><span class="n">synchronize</span><span class="p">();</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="n">i</span><span class="o">=</span><span class="mi">1</span><span class="p">;</span> <span class="n">i</span><span class="o"><</span><span class="n">N</span><span class="p">;</span> <span class="n">i</span><span class="o">++</span><span class="p">)</span> <span class="p">{</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="o">==</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="o">+</span> <span class="n">input</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">*</span> <span class="mi">10</span><span class="p">);</span>
<span class="p">}</span></pre><p>Similarly, <a href="namespacetf.html#a2e739895c1c73538967af060ca714366" class="m-doc">tf::<wbr />cuda_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="kt">size_t</span> <span class="n">N</span> <span class="o">=</span> <span class="mi">1000000</span><span class="p">;</span>
<span class="kt">int</span><span class="o">*</span> <span class="n">input</span> <span class="o">=</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="c1">// input vector</span>
<span class="kt">int</span><span class="o">*</span> <span class="n">output</span> <span class="o">=</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="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="n">i</span><span class="o">=</span><span class="mi">0</span><span class="p">;</span> <span class="n">i</span><span class="o"><</span><span class="n">N</span><span class="p">;</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="c1">// queries the required buffer size to scan N elements using the given policy</span>
<span class="n">tf</span><span class="o">::</span><span class="n">cudaDefaultExecutionPolicy</span> <span class="n">policy</span><span class="p">;</span>
<span class="k">auto</span> <span class="n">bytes</span> <span class="o">=</span> <span class="n">tf</span><span class="o">::</span><span class="n">cuda_scan_buffer_size</span><span class="o"><</span><span class="n">tf</span><span class="o">::</span><span class="n">cudaDefaultExecutionPolicy</span><span class="p">,</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="k">auto</span> <span class="n">buffer</span> <span class="o">=</span> <span class="n">tf</span><span class="o">::</span><span class="n">cuda_malloc_device</span><span class="o"><</span><span class="n">std</span><span class="o">::</span><span class="n">byte</span><span class="o">></span><span class="p">(</span><span class="n">bytes</span><span class="p">);</span>
<span class="c1">// computes exclusive scan over transformed input and stores the result in output</span>
<span class="n">tf</span><span class="o">::</span><span class="n">cuda_transform_exclusive_scan</span><span class="p">(</span><span class="n">policy</span><span class="p">,</span>
<span class="n">input</span><span class="p">,</span> <span class="n">input</span> <span class="o">+</span> <span class="n">N</span><span class="p">,</span> <span class="n">output</span><span class="p">,</span>
<span class="p">[]</span> <span class="n">__device__</span> <span class="p">(</span><span class="kt">int</span> <span class="n">a</span><span class="p">,</span> <span class="kt">int</span> <span class="n">b</span><span class="p">)</span> <span class="p">{</span> <span class="k">return</span> <span class="n">a</span> <span class="o">+</span> <span class="n">b</span><span class="p">;</span> <span class="p">},</span> <span class="c1">// binary scan operator</span>
<span class="p">[]</span> <span class="n">__device__</span> <span class="p">(</span><span class="kt">int</span> <span class="n">a</span><span class="p">)</span> <span class="p">{</span> <span class="k">return</span> <span class="n">a</span><span class="o">*</span><span class="mi">10</span><span class="p">;</span> <span class="p">},</span> <span class="c1">// unary transform operator</span>
<span class="n">buffer</span>
<span class="p">);</span>
<span class="n">policy</span><span class="p">.</span><span class="n">synchronize</span><span class="p">();</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="n">i</span><span class="o">=</span><span class="mi">1</span><span class="p">;</span> <span class="n">i</span><span class="o"><</span><span class="n">N</span><span class="p">;</span> <span class="n">i</span><span class="o">++</span><span class="p">)</span> <span class="p">{</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="o">==</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="o">+</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="o">*</span> <span class="mi">10</span><span class="p">);</span>
<span class="p">}</span></pre></section>
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