Graph Analytics and AI: A Break Through Approach to Analyze Massive Data Sets

Talk:

• Graphs are playing a key role in big data analytics, providing insights in many domains through traditional graph algorithms and graph neural networks.
• As the size of these data sets increase, the computing power needed also increases, and the software techniques to manage it becomes ever more critical. For example, there are Intel-based single-node systems which can have up to 16TB of main memory with Optane DC PMM, large clusters of machines are available with thousands of cores, and specialized hardware for processing large-scale graphs is being developed.
• Intel and Katana Graph are collaborating to produce an efficient and scalable graph analytics and AI library that works across this wide variety of platforms.