While there has been significant work on parallel graph processing, there has been very surprisingly little work on high-performance hypergraph processing. This paper presents a collection of efficient parallel algorithms for hypergraph processing, including algorithms for computing hypertrees, hyperpaths, betweenness centrality, maximal independent sets, $k$-core decomposition, connected components, PageRank, and single-source shortest paths. For these problems, we either provide new parallel algorithms or more efficient implementations than prior work. Furthermore, our algorithms are theoretically-efficient in terms of work and depth. To implement our algorithms, we extend the Ligra graph processing framework to support hypergraphs, and our implementations benefit from graph optimizations including switching between sparse and dense traversals based on the frontier size, edge-aware parallelization, using buckets to prioritize processing of vertices, and compression. Our experiments on a 72-core machine and show that our algorithms obtain excellent parallel speedups, and are significantly faster than algorithms in existing hypergraph processing frameworks.
Tue 25 Feb Times are displayed in time zone: Tijuana, Baja California change
14:00 - 15:15: Graph (Mediterranean Ballroom)Main Conference Chair(s): Jiajia LiPacific Northwest National Laboratory | |||
14:00 - 14:25 Talk | Practical Parallel Hypergraph Algorithms Main Conference Julian ShunMIT | ||
14:25 - 14:50 Talk | A Supernodal All-Pairs Shortest Path Algorithm Main Conference piyush kumar saoOak Ridge National Lab, Ramki KannanOak Ridge National Laboratory, Prasun GeraGeorgia Institute of Technology, Rich VuducGeorgia Institute of Technology | ||
14:50 - 15:15 Talk | Increasing the Parallelism of Graph Coloring via Shortcutting Main Conference Ghadeer AlabandiTexas State University, Evan PowersTexas State University, Martin BurtscherTexas State University |