Abstract

Our talk discusses the development and origin of LightGraphs, current features, and future developments. We introduce the package’s major design choices in a historical context as a compromise between the three core LightGraphs goals of simplicity, performance, and flexibility. We highlight several areas where specific features of Julia have led to flexible and efficient implementations of graph algorithms. We will highlight our work in centrality measures, graph traversals, and spectral graph algorithms as examples of areas where Julia’s performance and design decisions have allowed LightGraphs to provide best-in-class implementations of graph algorithms. We also discuss integration with other organizations – JuliaOpt for matching and flow problems, and the Julia data visualization ecosystem – and highlight specifically LightGraphs’ potential to provide leadership on performant graph visualization. Finally, we speculate on the influence of Julia’s focus on elegant parallel processing to future development of the package.