We introduce NetworKit, an open-source software package for analyzing the structure of
large complex networks. Appropriate algorithmic solutions are required to handle …

Dynamic memory management on GPUs is generally understood to be a challenging topic.
On current GPUs, hundreds of thousands of threads might concurrently allocate new …

External labeling is frequently used for annotating features in graphical displays and
visualizations, such as technical illustrations, anatomical drawings, or maps, with textual …

High-performance implementations of graph algorithms are challenging to implement on
new parallel hardware such as GPUs because of three challenges:(1) the difficulty of coming …

Processing large complex networks like social networks or web graphs has attracted
considerable interest. To do this in parallel, we need to partition them into pieces of roughly …

Ahead-of-time data layout optimization by vertex reordering is a widely used technique to
improve memory access locality in graph analysis. While reordered graphs yield better …

Emerging quantum processors provide an opportunity to explore new approaches for
solving traditional problems in the post Moore's law supercomputing era. However, the …

The independent set problem is NP-hard and particularly difficult to solve in large sparse
graphs, which typically take exponential time to solve exactly using the best-known exact …

We introduce XtraPuLP, a new distributed-memory graph partitioner designed to process
trillion-edge graphs. XtraPuLP is based on the scalable label propagation community …

The most commonly used method to tackle the graph partitioning problem in practice is the
multilevel approach. During a coarsening phase, a multilevel graph partitioning algorithm …