Davide Ferre'
I'm a PhD student in Computer Science at Université Côte d’Azur, working within the COATI team, a joint group between Inria and CNRS. My research focuses on machine learning and graph theory, and I enjoy working at the intersection of theory and practice. As a 2025 Google Summer of Code contributor with the Julia organization, I'm working on integrating GPU-accelerated sparse operations into the GraphNeuralNetworks.jl package to support more efficient implementations of graph neural network layers.
Session
Graph Neural Networks (GNNs) are powerful models for learning from graph-structured data, but their performance can depend critically on how message passing is implemented. In this talk, I will present my Google Summer of Code project with the Julia organization, aimed at accelerating GNNs by improving support for sparse computations on GPUs. By leveraging sparse-dense matrix multiplications—rather than the traditional gather-scatter paradigm—for layers such as graph convolutions, we can reduce memory overhead and improve performance. These enhancements are integrated into the GraphNeuralNetworks.jl package, helping bring Julia’s GNN ecosystem closer to state-of-the-art frameworks in other languages.