Machine Learning with Graphs in High-Performance Computing Environments

Abstract

The intent of this workshop is to bring together researchers, practitioners, and scientific communities to discuss methods that utilize extreme scale systems for learning graph data. This workshop will focus on the greatest challenges in utilizing high-performance computing (HPC) for machine learning with graphs and methods for exploiting extreme scale parallelism for data, computation, and model optimization. We invite researchers and practitioners to participate in this workshop to discuss the challenges in using HPC for machine learning with graphs and to share the wide range of applications that would benefit from HPC-powered machine learning with graphs.