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Presenter: Jinhui Qin, SHARCNET
Graph analysis plays a critical role in many applications across various domains, ranging from social network analysis to bioinformatics, to fraud detection, to cybersecurity, to recommendation systems, etc. NetworkX is the go-to library for graph analysis in Python. However, when dataset and graph sizes grow, the performance of using NetworkX becomes a significant concern. This webinar introduces NVIDIA cuGraph for accelerating graph analysis on GPUs. Moreover, a recent integration of NetworkX with cuGraph, named nx-cugraph, allows accelerating workflows in NetworkX on GPUs with zero code changes. A live demo will be done on the clusters.