Graph neural networks (GNNs) emerge as a powerful approach to process non-euclidean
data structures and have been proved powerful in various application domains such as …

Simple graph algorithms such as PageRank have been the target of numerous hardware
accelerators. Yet, there also exist much more complex graph mining algorithms for problems …

Graph analytics power a range of applications in areas as diverse as finance, networking
and business logistics. A common property of graphs used in the domain of graph analytics …

The irregular adjacency matrix and the mismatched computation patterns of Aggregation
and Combination phases make Graph Neural Networks (GNNs) challenging to compute …

Computations on irregular graph structures are important for many fields, including social
sciences, bioinformatics, chemistry, medicine, cybersecurity, healthcare, web graph …

Last-Level Cache (LLC) represents the bulk of a modern CPU processor's transistor budget
and is essential for application performance as LLC enables fast access to data in contrast …