Prof. Ahmed Louri received a National Science Foundation award for the project “Holistic Design of High-performance and Energy-efficient Accelerators for Graph Neural Networks”.
Prof. Ahmed Louri has been awarded a three-year, $500,000 National Science Foundation grant for the project “Holistic Design of High-performance and Energy-efficient Accelerators for Graph Neural Networks.” Graph Neural Networks (GNNs) have recently emerged as one of the most powerful techniques for next generation learning systems, and they are gaining attention in many high-impact domains such as graph mining (graph machine, graph clustering), biology (drug discovery, disease classification), traffic networks (traffic prediction), recommendation systems, autonomous systems, and security, among many others. In this project, Dr. Louri will develop a holistic design framework spanning architecture study, Network-on-Chip (NoC) design, machine learning algorithms development, and algorithm-architecture co-optimization, with the aim of designing energy-efficient and high-performance scalable accelerator architectures for GNNs. Such a framework will have far-reaching implications for future machine learning architectures and applications. The project will also play a major role in education by integrating discovery with teaching and training.