3 papers
cs.DM2022
Parallel coarsening of graph data with spectral guarantees
Christopher Brissette, Andy Huang, George Slota
Finding coarse representations of large graphs is an important computational problem in the fields of scientific computing, large scale graph partitioning, and the reduction of geo…
cs.DC2021
Parallel Graph Coloring Algorithms for Distributed GPU Environments
Ian Bogle, Erik G Boman, Karen D Devine +2
Graph coloring is often used in parallelizing scientific computations that run in distributed and multi-GPU environments; it identifies sets of independent data that can be updated…
cs.SI2021
A simple method for improving the accuracy of Chung-Lu random graph generation
Christopher Brissette, George Slota
Random graph models play a central role in network analysis. The Chung-Lu model, which connects nodes based on their expected degrees is of particular interest. It is widely used t…