Accelerating Graph Neural Networks on Amazon Deep Graph Library (DGL) with NVIDIA GPU on AWS EC2 instance

Learning from graph and relational data plays a major role in many applications. In the last few years, Graph Neural Networks (GNNs) have emerged as a promising new machine learning framework, capable of bringing the power of deep representation learning to graph and relational data. This ever-growing body of research has shown that GNNs achieve state-of-the-art performance for problems such as link prediction, fraud detection, target-ligand binding activity prediction, knowledge-graph completion, and product recommendations. In this session, we’ll discuss Deep Graph Library (DGL), a DL library with efficient implementations for GNNs and demonstrate the speedup for GNN training and inference on NVIDIA GPUs on AWS EC2 instances.