Democratizing Large-Scale Graph Analytics: From Supercomputing to Societal Impact

Abstract

In this talk, I explore the evolution and impact of large-scale graph analytics, from my pioneering work in Linux supercomputing to today’s democratization of massive data science capabilities. The presentation highlights how the open-source Arachne framework, built on Arkouda, enables researchers and organizations to process and analyze graphs containing terabytes of data through an accessible Python interface, while the heavy computational work occurs on powerful backend systems. I discuss three critical application domains of this technology: national security (detecting malicious network activity through relationship patterns), computational neuroscience (analyzing connectomes containing millions of neurons and synapses), and scientometrics (mapping research collaboration networks). These examples demonstrate how graph analytics can solve complex problems that were previously inaccessible due to computational limitations. The talk emphasizes the parallel between my 1998 development of the first Linux-based supercomputer—now the architecture for 100% of the world’s top supercomputers with an estimated economic impact of $100 trillion—and my current mission to democratize access to sophisticated graph analytics capabilities. Through open-source tools and frameworks, my work continues to bridge the gap between cutting-edge computing resources and real-world applications, making powerful data analysis accessible to researchers and practitioners across disciplines.

David A. Bader

Distinguished Professor and Director of the Institute for Data Science

David A. Bader is a Distinguished Professor in the Department of Computer Science at New Jersey Institute of Technology.