Random graph models are frequently used as a controllable and versatile data source for
experimental campaigns in various research fields. Generating such data-sets at scale is a …

Techniques and apparatus to manage access to accelerator attached memory are
described. In one embodiment, an apparatus to provide coherence bias for accessing …

A novel parallel algorithm is presented for generating random scale-free networks using the
preferential attachment model. The algorithm, named cuPPA, is custom-designed for “single …

Recently, there has been substantial interest in the study of various random networks as
mathematical models of complex systems. As these complex systems grow larger, the ability …

334Random graph models are frequently used as a controllable and versatile data source
for experimental campaigns in various research fields. Generating such data-sets at scale is …

Recently, there has been substantial interest in the study of various random networks as
mathematical models of complex systems. As real-life complex systems grow larger, the …

Netzwerkmodelle spielen in verschiedenen Wissenschaftsdisziplinen eine wichtige Rolle
und dienen unter anderem der Beschreibung realistischer Graphen. Sie werden häufig als …

Epidemic simulations require the ability to sample contact networks from various random
graph models. Existing methods can simulate city-scale or even country-scale contact …

Synthetically generated, large graph networks serve as useful proxies to real-world networks
for many graph-based applications. The ability to generate such networks helps overcome …

Synthetic networks are very useful in investigations of complex systems across the scientific
spectrum, such as cyber-infrastructures, social networks, internet, and epidemiological …