Hypergraphs are a generalization of graphs where edges (aka nets) are allowed to connect
more than two vertices. They have a similarly wide range of applications as graphs. This …

We present the design and a first performance evaluation of Thrill-a prototype of a general
purpose big data processing framework with a convenient data-flow style programming …

Data structures for efficient sampling from a set of weighted items are an important building
block of many applications. However, few parallel solutions are known. We close many of …

Recent work has shown that perfect hashing and retrieval of data values associated with a
key can be done in such a way that there is no need to store the keys and that only a few bits …

We consider the problem of sampling n numbers from the range {1,…, N} without
replacement on modern architectures. The main result is a simple divide-and-conquer …

Previous parallel sorting algorithms do not scale to the largest available machines, since
they either have prohibitive communication volume or prohibitive critical path length. We …

String sorting is an important part of tasks such as building index data structures.
Unfortunately, current string sorting algorithms do not scale to massively parallel distributed …

We investigate distributed memory parallel sorting algorithms that scale to the largest
available machines and are robust with respect to input size, duplicate keys, and distribution …

Recent literature shows a growing interest in the integration of federated learning (FL) and
multilevel stochastic compositional optimization (MSCO), which arises in meta-learning and …

The advent of executable contents such as Java applets exposes WWW users to a new
class of attacks that were not possible before. Serious security breach incidents due to …