Parallel hypergraph partitioning for scientific computing

By Karen D. Devine, E. Boman, R. Heaphy, Rob H. Bisseling, Ümit V. Çatalyürek. Proceedings 20th IEEE International Parallel & Distributed Processing Symposium, 2006

295 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering, Hardware and Architecture

View Paper: https://www.semanticscholar.org/paper/0a0f2a5051652839e0b8176182a9ca4a1bc1e9e6

Citations in the corpus

• Proposal Scaling Distributed Machine Learning with System and Algorithm Co-design (2016, unknown): “On several large scale datasets, we show that the proposed algorithm outperforms the state-of-the-art methods, including METIS [73], PaToH [28] and Zoltan [47], in terms of both partition quality and speed.”
• PowerGraph: Distributed Graph-Parallel Computation on Natural Graphs (2012, unknown): “The vertex-cut approach to distributed graph placement is related to work [9, 13] in hypergraph partitioning.”