Recent demands for storing and querying big data have revealed various shortcomings of
traditional relational database systems. This, in turn, has led to the emergence of a new kind …

In recent years, significant advances have been made in the design and evaluation of
balanced (hyper) graph partitioning algorithms. We survey trends of the past decade in …

Numerous irregular graph datasets, for example social networks or web graphs, may contain
even trillions of edges. Often, their structure changes over time and they have domain …

In recent years, significant advances have been made in the design and analysis of fully
dynamic algorithms. However, these theoretical results have received very little attention …

The world is becoming a more conjunct place and the number of data sources such as
social networks, online transactions, web search engines, and mobile devices is increasing …

This paper studies incremental graph partitioning. Given a (vertex-cut or edge-cut) partition
C (G) of a graph G and updates ΔG to G, it is to compute changes ΔO to C (G), yielding a …

Graph processing has become an important part of various areas of computing, including
machine learning, medical applications, social network analysis, computational sciences …

Graphs are a tremendously suitable data representations that model the relationships of
entities in many application domains, such as recommendation systems, machine learning …

Graph processing has become an important part of various areas of computing, including
machine learning, medical applications, social network analysis, computational sciences …

We report a systematic performance study of streaming graph partitioning algorithms. Graph
partitioning plays a crucial role in overall system performance as it has a significant impact …