GPU Accelerated Graph Analysis in Python using cuGraph- Brad Rees | SciPy 2022

Graph analysis is used in a wide range of applications, from computational social science (social network analysis) to fraud detection and marketing. Just like within Machine Learning (ML), being able to load and analyze data quickly is the key to getting to a solution faster. Additionally, like ML, there is a lot of data prep, which we call graph ETL, that needs to be done. Join us for a talk on using RAPIDS and cuGraph to accelerate the full end-to-end graph analysis pipeline. We will dive into a COVID-19 social network example to illustrate the performance gains of using GPUs.