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	<title>Colloquium 2024 Accelerating Graph Analysis on GPUs - Revision history</title>
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	<updated>2026-04-03T22:19:19Z</updated>
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		<title>Syam: Created page with &quot;Graph analysis plays a critical role in many applications across various domains, ranging from social network analysis to bioinformatics, to fraud detection, to cybersecurity,...&quot;</title>
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		<updated>2024-03-27T16:14:16Z</updated>

		<summary type="html">&lt;p&gt;Created page with &amp;quot;Graph analysis plays a critical role in many applications across various domains, ranging from social network analysis to bioinformatics, to fraud detection, to cybersecurity,...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;Graph analysis plays a critical role in many applications across various domains, ranging from social network analysis to bioinformatics, to fraud detection, to cybersecurity, to recommendation systems, etc.  NetworkX is the go-to library for graph analysis in Python. However, when dataset and graph sizes grow, the performance of using NetworkX becomes a significant concern. This webinar introduces NVIDIA cuGraph for accelerating graph analysis on GPUs. Moreover, a recent integration of NetworkX with cuGraph, named nx-cugraph, allows accelerating workflows in NetworkX on GPUs with zero code changes. A live demo will be done on the clusters.&lt;/div&gt;</summary>
		<author><name>Syam</name></author>
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