[GH-PAGES] Updated website
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@@ -17,6 +17,7 @@
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<link rel="stylesheet" href="../../_static/gallery-binder.css" type="text/css" />
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<link rel="stylesheet" href="../../_static/gallery-dataframe.css" type="text/css" />
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<link rel="stylesheet" href="../../_static/gallery-rendered-html.css" type="text/css" />
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<link rel="stylesheet" href="../../_static/css/custom.css" type="text/css" />
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@@ -106,6 +107,12 @@
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</ul>
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</li>
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</ul>
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<p class="caption"><span class="caption-text">Programming Guide</span></p>
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<ul>
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<li class="toctree-l1"><a class="reference internal" href="../../programming-guide/introduction.html">Introduction</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../../programming-guide/related-work.html">Related Work</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../../programming-guide/triton-c.html">The Triton-C Language</a></li>
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</ul>
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@@ -397,7 +404,7 @@ This means that – when temporary data is too large to fit entirely in the GPU
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Note that our Triton kernel is not only faster than PyTorch’s CUDA kernel, it is also <strong>easier to read, understand and maintain</strong>.</p></li>
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</ul>
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</div></blockquote>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 19.896 seconds)</p>
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<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes 20.299 seconds)</p>
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<div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-getting-started-tutorials-02-fused-softmax-py">
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<div class="sphx-glr-download sphx-glr-download-python docutils container">
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<p><a class="reference download internal" download="" href="../../_downloads/d91442ac2982c4e0cc3ab0f43534afbc/02-fused-softmax.py"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Python</span> <span class="pre">source</span> <span class="pre">code:</span> <span class="pre">02-fused-softmax.py</span></code></a></p>
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