A System Integrating Echo State Graph Neural Networks And Analogue Random Resistive Memory Arrays

Researchers from the University of Hong Kong, the Chinese Academy of Sciences, InnoHK Centers and other institutes worldwide have developed a software-hardware system that combines a Graph Neural Network (GNN) architecture with a resistive memory. This system has been tested on a variety of real-world applications, such as drug discovery, social network design, and recommender systems, and has achieved promising results. The paper, published in Nature Machine Intelligence, demonstrates the potential of new hardware solutions based on GNNs.