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 ...

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 ...

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 ...

“This dovetails with a widely held belief in computer science about graphs as they exist in the real world—the belief that large-scale graphs are always sparse,” he explains. “But I have an ...

As graph database adoption accelerates, new data infrastructures will emerge to eliminate many of the scale struggles of graph database models. Written by eWEEK content and product recommendations ...

Despite shiny new AI and data science tools, the problem of data integration at scale hasn't gone away. But promising new approaches from vendors like StreamSets and FlureeDB are worth a closer look.