A research team has introduced a new out-of-core mechanism, Capsule, for large-scale GNN training, which can achieve up to a 12.02× improvement in runtime efficiency, while using only 22.24% of ...

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph partitioning, has been developed by researchers at the ...

Google’s New Graph Foundation Model Improves Precision By Up To 40X Google's new Graph Foundation Model delivers up to 40 times greater precision and has been tested at scale on spam detection.

BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph partitioning, has been developed by researchers at ...