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 …

We describe the engineering of the distributed-memory multilevel graph partitioner
dKaMinPar. It scales to (at least) 8192 cores while achieving partitioning quality comparable …

Graph partitioning plays a pivotal role in various distributed graph processing applications,
including graph analytics, graph neural network training, and distributed graph databases …

Distributed generation (DG) has not only electricity value, but also capacity value. The
capacity value can be represented by the credible capacity (CC) based on the equal power …

More and more distributed power generators (DG), eg, photovoltaic (PV), and various
energy storage (ES) equipment are integrated into the distribution network (DN). The …

Sparse, irregular graphs show up in various applications like linear algebra, machine
learning, engineering simulations, robotic control, etc. These graphs have a high degree of …

Recent advances in computer architecture significantly enhance the computational capacity
of multicore systems. It allows large-scale graphs to be processed inside a single machine …

Graph algorithms find several usages in industry, science, humanities, and technology. The
fast-growing size of graph datasets in the context of the processing model of the current …

Set reachability query in directed graphs has a plethora of graph-based applications such as
dependency analysis and graph centrality calculation. Given two sets and of source and …

Graph-based services are becoming integrated into everyday life through graph applications
and graph learning systems. While traditional graph processing approaches boast excellent …