We consider the problem of graph analytics on evolving graphs (ie, graphs that change over
time). In this scenario, a query typically needs to be applied to different snapshots of the …

Graph analytics is the basis for many modern applications, eg, machine learning and
streaming data problems. With an unprecedented increase in data size of many emerging …

Graph Processing is at the core of many critical emerging workloads operating on
unstructured data, including social network analysis, bioinformatics, and many others. Many …

Non-relational database systems (NRDS) such as graph and key-value have gained
attention in various trending business and analytical application domains. However, while …

The single-source shortest path (SSSP) problem is one of the most important and well-
studied graph problems widely used in many application domains, such as road navigation …

Field-programmable gate arrays (FPGAs) have become popular means of hardware
acceleration since they offer massive parallelism, flexible configurability, and potentially …

Streaming graph has been broadly employed across various application domains. It
involves updating edges to the graph and then performing analytics on the updated graph …

Dynamic graph convolutional networks (DGCNs) have emerged as an effective approach to
analyzing graph data that is constantly changing. The typical DGCNs incorporate not only …

Software and hardware development cycles have traditionally been quite distinct. Software
allows post-deployment patches, which leads to a rapid development cycle. In contrast …

Dynamic Graph Neural Network (DGNN) has recently attracted a significant amount of
research attention from various domains, because most real-world graphs are inherently …