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{"documenter":{"julia_version":"1.10.4","generation_timestamp":"2024-06-10T23:30:12","documenter_version":"1.4.1"}}
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docs-navbar-link fa-solid fa-bars is-hidden-desktop" id="documenter-sidebar-button" href="#"></a><nav class="breadcrumb"><ul class="is-hidden-mobile"><li><a class="is-disabled">Manual</a></li><li class="is-active"><a href>Accumulate</a></li></ul><ul class="is-hidden-tablet"><li class="is-active"><a href>Accumulate</a></li></ul></nav><div class="docs-right"><a class="docs-navbar-link" href="https://github.com/anicusan/AcceleratedKernels.jl" title="View the repository on GitHub"><span class="docs-icon fa-brands"></span><span class="docs-label is-hidden-touch">GitHub</span></a><a class="docs-navbar-link" href="https://github.com/anicusan/AcceleratedKernels.jl/blob/main/docs/src/api/accumulate.md" title="Edit source on GitHub"><span class="docs-icon fa-solid"></span></a><a class="docs-settings-button docs-navbar-link fa-solid fa-gear" id="documenter-settings-button" href="#" title="Settings"></a><a class="docs-article-toggle-button fa-solid fa-chevron-up" id="documenter-article-toggle-button" href="javascript:;" title="Collapse all docstrings"></a></div></header><article class="content" id="documenter-page"><h3 id="Accumulate-/-Prefix-Sum-/-Scan"><a class="docs-heading-anchor" href="#Accumulate-/-Prefix-Sum-/-Scan">Accumulate / Prefix Sum / Scan</a><a id="Accumulate-/-Prefix-Sum-/-Scan-1"></a><a class="docs-heading-anchor-permalink" href="#Accumulate-/-Prefix-Sum-/-Scan" title="Permalink"></a></h3><div class="markdown"><p>Compute accumulated running totals along a sequence by applying a binary operator to all elements up to the current one; often used in GPU programming as a first step in finding / extracting subsets of data.</p>
<ul>
<li><p><code>accumulate&#33;</code> &#40;in-place&#41;, <code>accumulate</code> &#40;allocating&#41;; inclusive or exclusive.</p>
</li>
<li><p><strong>Other names</strong>: prefix sum, <code>thrust::scan</code>, cumulative sum; inclusive &#40;or exclusive&#41; if the first element is included in the accumulation &#40;or not&#41;.</p>
</li>
</ul>
<p>Function signature:</p>
<pre><code class="language-julia">accumulate&#33;&#40;op, v::AbstractGPUVector; init, inclusive::Bool&#61;true,
block_size::Int&#61;128,
temp_v::Union&#123;Nothing, AbstractGPUVector&#125;&#61;nothing,
temp_flags::Union&#123;Nothing, AbstractGPUVector&#125;&#61;nothing&#41;
accumulate&#40;op, v::AbstractGPUVector; init, inclusive::Bool&#61;true,
block_size::Int&#61;128,
temp_v::Union&#123;Nothing, AbstractGPUVector&#125;&#61;nothing,
temp_flags::Union&#123;Nothing, AbstractGPUVector&#125;&#61;nothing&#41;</code></pre>
<p>Example computing an inclusive prefix sum &#40;the typical GPU &quot;scan&quot;&#41;:</p>
<pre><code class="language-julia">import AcceleratedKernels as AK
using oneAPI

v &#61; oneAPI.ones&#40;Int32, 100_000&#41;
AK.accumulate&#33;&#40;&#43;, v, init&#61;0&#41;</code></pre>
<p>The temporaries <code>temp_v</code> and <code>temp_flags</code> should both have at least <code>&#40;length&#40;v&#41; &#43; 2 * block_size - 1&#41; ÷ &#40;2 * block_size&#41;</code> elements; <code>eltype&#40;v&#41; &#61;&#61;&#61; eltype&#40;temp_v&#41;</code>; the elements in <code>temp_flags</code> can be any integers, but <code>Int8</code> is used by default to reduce memory usage. </p>
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