Originally published at: https://developer.nvidia.com/blog/intersection-large-scale-graph-analytics-deep-learning/
Figure 1: An example graph in which entities are represented by nodes and relationships are represented by edges. Suppose you want to find the most influential user of Twitter. You would need to know not only how many followers everyone has, but also who those followers are, who the followers of those followers are, and…
Great article. Very good explanation of the partitioning of graphs. FUNL sounds very interesting and will help to implement many graph algorithms on the GPU much faster. Will there be an open source license of FUNL for academia or non-commercial use?
We are actively looking at releasing a license for academia and want to do it in partnership with the academic organization that might find it useful. Contact us if you would like to discuss your project.
Thank you for very interested topic. Did you release the open source for FUNL and DeepInsight..؟
im interested to get a license for an academia like me. I want to study more about graph and supply chain networks.