What to Do with All That Bandwidth? GPUs for Graph and Predictive Analytics – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-07-03T22:20:47Z http://www.open-lab.net/blog/feed/ Brad Bebee <![CDATA[What to Do with All That Bandwidth? GPUs for Graph and Predictive Analytics]]> http://www.open-lab.net/blog/parallelforall/?p=6484 2022-08-21T23:37:48Z 2016-03-22T04:49:17Z [caption id="attachment_6509" align="alignright" width="300"] Figure 1: Graph algorithms exhibit non-locality and data-dependent parallelism. Large graphs, such...]]> [caption id="attachment_6509" align="alignright" width="300"] Figure 1: Graph algorithms exhibit non-locality and data-dependent parallelism. Large graphs, such...Figure 1: Graph algorithms exhibit non-locality and data-dependent parallelism. Large graphs, such as this map of the internet, represent billion-edge challenges that push the bandwidth limits of existing hardware architectures.

Did you see the White House��s recent initiative on Precision Medicine and how it is transforming the ways we can treat cancer? Have you avoided clicking on a malicious website based on OpenDNS��s SecureRank predictive analytics? Are you using the Wikidata Query Service to gather data to use in your machine learning or deep learning application? If so, you have seen the power of graph applications.

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